Emerging Technologies in Healthcare and Medicine

AHFE International

Accelerating Open Access Science in Human Factors Engineering and Human-Centered Computing

Emerging Technologies in Healthcare and Medicine

book-cover

Editors: Jay Kalra

Topics: Healthcare and Medical Devices

Publication Date: 2023

ISBN: 978-1-958651-92-6

DOI: 10.54941/ahfe1004351

Articles

Automatic Classification of Infant Sleeping Postures Using an Infrared Camera

The sleeping posture is crucial determinant of infant growth and development. Sleeping in the prone position is associated with a higher risk of sudden infant death syndrome. Therefore, medical recommendations advocate placing infants in the supine position during sleep. Furthermore, certain medical conditions, such as cranial deformity, hip dislocation, and torticollis, may manifest as head-turn preferences, wherein infants consistently face a specific direction, either right or left. Detecting and addressing these sleeping postures are critical for preventing accidental infant deaths during sleep and identifying potential underlying health issues. In this study, we present an automatic method for classifying infant sleeping postures into four categories: supine, prone, right lateral, and left lateral, using only videos. Although various methods exist for classifying sleeping postures during infancy, such as those involving acceleration and pressure seat sensors, they often require physical attachments that may cause discomfort to the infants. To address this limitation, we present a contactless approach that employs video images recorded using an infrared camera. The camera was positioned to record the entire infant bedding area without imposing restrictions on the installation angle. We analyzed the video data collected from the home of each participant and classified the sleeping postures of the participants into four categories. Subsequently, the classification accuracy was calculated for each night. The participants of the experiment were two infants under one year of age. To evaluate data accuracy, we excluded instances of data involving individuals other than the participants and data outside the field of view of the camera. “Vision Pose,” a skeleton estimation software capable of detecting joint points in images, was employed for body position analysis. Specifically, we extracted the two-dimensional coordinates of eight joint points: both shoulders, both elbows, both hips, shoulder center, and hip center. We classified the infant sleeping postures by measuring the distance between these joint points. A linear support vector machine was applied to the features, and classification was conducted in two steps. In the initial step, the sleep data were categorized into two groups: supine or prone and right lateral or left lateral. Subsequently, each of these categories was further divided into two classifications, yielding four types of sleeping postures. Our proposed model demonstrates an impressive average accuracy of 92.3% in estimating the four sleeping postures: supine, prone, right lateral, and left lateral. Our study establishes the feasibility of non-contact sleeping posture classification using an infrared camera. This approach holds promising potential for real-life home environments and childcare facilities, where continuous monitoring of infant sleeping postures can significantly contribute to promoting safe sleep practices and early identification of potential health concerns.

Yuina Ninomiya, Shima Okada, Masaaki Makikawa, Masanobu Manno, Yusuke Sakaue, Watanabe Tamami, Fukuda Yuko

Conference Proceedings

Analysis of Stair-Ascent Activities with Handrail Use in Daily Living Space and Motion Features using RGBD Camera

The geriatric population has increased worldwide over the past few decades. Older adults rarely make a sudden transition from a healthy state to a state requiring nursing care; more often they transition through an intermediate stage called frailty. To assess frailty quantitatively using ambient sensing technology, our group developed a system to automatically and continuously measure and analyze human ascent and descent motions and handrail-use behaviors in homes, using an RGBD camera. This study developed a whole-body motion feature analysis method using principal component analysis (PCA), and analyzed the features of whole-body motions related to handrail use when ascending stairs. Daily stair-ascent motion was measured in two houses, with two participants in their 20s and two in their 50s in the first house, and two in their 70s in the second house. A method for extracting the characteristic motion of ascending stairs while using a handrail was developed using principal component analysis of whole-body skeleton data. The results showed that the third principal component was the characteristic motion of holding the handrail. The developed method makes it possible to evaluate dependence on handrails and clarify the characteristics of movements associated with changes in physical function, through continuous measurement and motion feature extraction techniques for daily stair ascent.

Yusuke Miyazaki, Kohei Shoda, Koji Kitamura, Yoshifumi Nishida

Conference Proceedings

Body Movement Support System for Prevent Disability and Promote Progress

For knowledge transmission, it is important to construct structured knowledge that clearly describes the knowledge. The purpose of this study is to propose a method of structuring instructional knowledge through the approach of conveying ideal body movements, and to develop a system using the knowledge. To achieve the purpose, we structured the knowledge of ideal motions through interviews and constructed computer-readable instructional knowledge. Then, we created a transmission system to utilize the knowledge and instruct the motions, and a veteran instructor confirmed the feedback from the system. From the results, we found that knowledge structured by interviews can be computer readable and incorporated into the system. The results also showed that new knowledge can be extracted by using the proposed method. The results suggested that the proposed method can clarify the instructor's knowledge and share instructional techniques with others.

Wataru Sato, Aoi Yamamoto, Sayuri Kumagai, Yasuyuki Yoshida, Koki Ijuin, Chiaki Oshiyama, Tsutomu Fujinami, Takuichi Nishimura

Conference Proceedings

Shaping a device for Anti-viral disinfection and checking health of people moving in public space

The main goal of the project is to develop a product innovation consisting in the implementation of a new type of disinfection device that combines functionality with the ability to monitor health and detect potentially infected people. The de-signed device for virucidal disinfection, together with monitoring the health of us-ers in public spaces, is part of the strategy of preventive measures to limit the spread of the pandemic, with particular emphasis on the SARS-CoV-2 virus. The device is intended to improve the safety of the public in epidemiological threats, as well as a long-term strategy to protect and counteract subsequent waves of pandemics and other, so far unrecognized viruses. For the needs of the research task, the concepts of the device varied in terms of size and ergonomics were de-signed. Initial analyzes concerned solutions based on a prism structure in an or-thogonal system. For the above solutions, 1:1 scale test benches have been pre-pared in order to conduct advanced ergonomic, functional and accessibility anal-yses. In order to carry out preliminary spatial and functional analyzes of the sup-port, 2D and 3D tests were carried out using simplified human models containing anthropometric data. Percentile models of women and men of European descent were used. In addition, accessibility variants for the reach of the arms of a person moving in a wheelchair were examined in terms of the assumptions of universal design. As a result of ergonomic analyses, the distribution of components in the space of the shaped device was assumed.For irregular shapes of the device housing, it is required to test the rod elements of the internal structure, which builds the device's rigidity. Parametric shaping of bar systems requires the implementation of tools useful in mastering the geometry of chaotic structures. One of the more practical methods is the Contracting meth-od taken from topological graph theory. This action, on the one hand, reduces the number of structure nodes, and on the other hand, has ordering properties in the space of geometric irregular structures. The use of the contracting method should not lead to a reduction in the role of the designer, who should maintain a direct impact on the aesthetics and technical parameters of the created structure at every design stage. An important problem to be solved is the scaling of the density of the device's frame in terms of technology and optimization of material consump-tion. In order to assess the stiffness of the device housing, tests were carried out on models composed of stainless steel bars connected to the housing sheets. Due to the location of the device in an open public space, the resistance of the device to accidental dynamic impacts was tested.

WALDEMAR BOBER, Barbara Gronostajska

Conference Proceedings

Transforming the homecare offering scene: How the technology plays a role

Digital health receives more and more attention as a solution to reduce the burden of healthcare cost in today's aging society. However, compared to other types of services, digital health service projects seem to have higher rates of stopping at pilot stages and do not get integrated into the actual medical practices. Adopting digital health solutions in today's healthcare settings often requires changes of work processes that can have a significant impact on the work practices of the healthcare professionals. Thus, there is a need for understanding both the current practice and the new proposed practice in service level with a more analytical and systematic approach. We conducted a multiple case study of homecare practices. Shadowing, contextual interviews, customer journey mapping, and semi-structured in-depth interviews were conducted in homecare settings in Norway and Sweden. Document analysis allowed us to add an additional case (a remote patient monitoring at home) to our study. The results of our study show that several key components of homecare services (service worker, secondary service worker, service interaction type, and sub-service provision context) were dissimilar among different homecare settings without or with a digital health solution. Our study might be useful to gain a deeper insight of homecare services and to understand the key components and the changing actors’ roles to consider when adopting digital solutions to the homecare services.

Eunji Lee

Conference Proceedings

Improving Comfort of Shoulder and Back Health in Children's School Bags: Examining Damper Shoulder Straps and Ergonomic Factors

This paper presents a study on the implementation of a damper mechanism in the shoulder straps of children's school bags, which is known in Japan as Randsel. The increasing size of textbooks and the need to carry tablet computers further emphasized the necessity for such improvements, particularly for younger elementary school children. To evaluate the effectiveness of the damper strap, a computer vision tracking method was employed. Six schoolchildren were selected as participants and instructed to engage in jogging and walking in place while carrying the Randsel on their shoulders. Three markers were placed on the participants' shoulder and at the top and bottom of the Randsel to facilitate tracking. Results indicated that conventional Randsel designs exhibited delayed up-and-down movements in response to the participants' body motions during jogging on the spot. This resulted in a downward pull on the shoulder when the body was in an upward motion and an upward pull when the body descended to the ground, thereby disrupting the jogging walk. In contrast, the newly invented damper shoulder strap synchronized the timing of the up-and down movements with the body's motion. The delay time of Randsel’s movement from body motion was significantly reduced.

Shigekazu Ishihara, Shuichi Konno

Conference Proceedings

Tiny Titans: Acceptance of In-Vivo Capsule and Micro Robots in Healthcare Innovation

This study explores the potential and challenges of using tiny in-vivo robots for medical diagnostics and therapy. While currently experimental and costly, technological advances may soon make them more affordable and essential, given the global shortage of medical specialists. The focus is on patient perspectives, as they are central to both technology acceptance and ethical considerations. The aim is to understand the perceived pros and cons of using in-vivo robots and factors influencing individual willingness to adopt them for medical purposes.

Kerstin Haring, Claudia Ossola-haring, Andreas Schlageter, Markus Gress-heister, Joachim Woelle

Conference Proceedings

Early Characterization of Stroke Using Video Analysis and Machine Learning

Stroke is one of the leading causes of death and disability worldwide and requires an immediate attention as the longer the patient is left untreated, the more sever its outcomes are. Enhancing access to optimal treatment and reducing mortality rates require improving the accuracy of stroke characterization methods in prehospital settings. This study explores how video analysis and machine learning (ML) can be leveraged to identify stroke symptoms on the National Institute of Health Stroke Scale (NIHSS), with the goal of facilitating the prehospital management of patients with suspected stroke. A total of 888 videos were captured from the research group members, who mimicked stroke symptoms including facial palsy, leg and arm paresis, ataxia and dysarthria, following the criteria of the NIHSS. Multiple algorithms, utilized in earlier studies, were examined to predict these symptoms, and their performance was assessed using accuracy, sensitivity and specificity. The best method for detecting facial palsy was found using Histogram of Oriented Gradients (HOG) features in conjunction with Adaptive Boosting (AdaBoost), achieving an accuracy, sensitivity and specificity values of 97.8%, 98.0% and 97.0%, respectively. The identification of arm paresis reached 100% on all metrics using a combination of MediaPipe and SVM. For leg paresis, all algorithms had poor detection rates. The outcome for ataxia for both limbs varied. Google Cloud Speech-to-Text was used to detect dysarthria and reached 100% on all evaluation metrics. These findings suggest that video analysis and ML have the potential to assist early stroke diagnosis, but further research is needed to validate this.

Hoor Jalo, Andrei Borg, Elsa Thoreström, Nathalie Larsson, Marcus Lorentzon, Oskar Tryggvasson, Viktor Johansson, Petra Redfors, Bengt Arne Sjöqvist, Stefan Candefjord

Conference Proceedings

Upper trapezius muscle activity pattern at work and associated neck pain - Study protocol for analyses of a pooled EMG data set

Repetitive and monotonous work is often associated with neck pain, potentially resulting in sick leave and reduced productivity. Establishing appropriate muscle activity patterns, including duration and frequency of breaks that can prevent development of neck pain is important for providing workplace guidance. While several smaller studies of monotonous neck-loading work have indicated that such breaks can reduce the risk of neck pain, studies with a higher number of participants are necessary to confirm an association, and if so, to improve the precision of a possible association. The purpose of this protocol is to describe and discuss the background, methods and challenges of a study pooling several datasets with measurements of upper trapezius muscle activity during work and associated measurements of neck pain. Methods: Seven Scandinavian research institutes provided surface electromyographic (EMG) data of upper trapezius muscle activity recorded during working hours along with questionnaire data with information about neck pain and other health-related factors, from a total of 750 participants. The different data sets of the EMG data will be merged into a common format. Various questions on neck pain will be harmonized. Associations between EMG variables and neck pain will be examined with linear mixed model regressions controlled for various confounders. Discussion: Aiming to provide further insight into the possible association between trapezius muscle activity pattern and neck pain, this study protocol highlights the challenges that arise when creating a pooled data set. Solving these challenges may help to increase the knowledge about appropriate muscle activity patterns during work.

Markus Koch, Mikael Forsman, Henrik Enquist, Henrik Baare Olsen, Karen Søgaard, Gisela Sjøgaard, Tove Østensvik, Petter Nilsen, Lars Louis Andersen, Markus Due Jacobsen, Rolf Westgaard, Paul Jarle Mork, Xuelong Fan, Morten Wærsted, Kaj Bo Veiersted

Conference Proceedings

Use of predictive models based on biomedical signals and motion measurements for predicting extremity kinematics

Due to staff shortages among physiotherapists and an ageing society, there is a growing need for the dynamic development of robot-aided rehabilitation. An ideal solution is a therapy conducted remotely, requiring minimal supervision by a physiotherapist, thus saving time and increasing the number of people treated. To achieve this, a rehabilitation device equipped with intelligent systems to detect dangerous situations for patients is essential. The paper presents a methodology for constructing a predictive model for a control system dedicated to home kinesiotherapy with an exoskeleton. It involves NARX-type recurrent neural networks based on the patients' electromyographic (EMG) measurements while exercising. Within the study, simultaneous EMG measurements and motion capture of the upper extremity were performed on three participants. The collected data were divided into sets for learning and testing neural networks. The kinematics was calculated using a multibody model of the upper limb with five degrees of freedom. The position data obtained from markers were converted into joint angles. Subsequently, a neural network was modelled in MATLAB, with the EMG measurements as inputs and the rotation angles in the upper limb joints as outputs. A sequence of movements covering the entire workspace of the upper limb was adopted as the network training set, while the network's performance was evaluated based on trajectory data from five simple exercises. The reported accuracy of the results remained within the range of 0.05-1°. The study revealed differences in the quality of the result depending on whether the participant of the exercise changes between the training and validation. To optimize predictions and reduce computation time, several different networks with varying parameters were constructed, trained and compared. The quasi-optimal parameters of the models were identified, including the number of hidden neurons, samples of previous output signal values, and samples of prior input signal values.

Julia Wilk, Cezary Rzymkowski, Piotr Falkowski

Conference Proceedings

Feature Selection for Machine Learning-Based Core Body Temperature Estimation Using Hand-Measurable Biological Information

Core body temperature (CBT) is an important health indicator that denotes the temperature of the body core, and maintains brain and organ function. Invasive methods of CBT measurement pose challenges in assessing and monitoring human health. To address this, estimation of tympanic membrane temperature using multiple biological parameters often referenced for CBT has been attempted in previous studies. Our research focused on machine learning-based CBT estimation using hand-measurable biological data. Furthermore, while various studies have investigated machine learning models and the impact of information acquisition environments, few have compared the estimation accuracy of different biological parameters or assessed optimal feature combinations. Our proposed method entails the evaluation of indices in both normal scenarios with all variables and patterned scenarios with varying combinations of reduced explanatory variables. The comparison results reveal that when estimating the CBT based on skin conductance and pulse wave intervals excluding skin temperature, the mean absolute error, coefficient of determination, and root mean square error were 0.17 °C, 0.71, and 0.24 °C, respectively. This suggests that our approach is a feasible CBT estimation method that does not rely on skin temperature, although accuracy concerns persist. Furthermore, the estimation of the difference between CBT and skin temperature suggests that the estimation method may have accounted for individual variations within the data. Implementing the proposed method in increasingly popular smart rings and watches could facilitate the acquisition of CBT in daily life.

Ryoya Oba, Keiichi Watanuki, Kazunori Kaede, Yusuke Osawa

Conference Proceedings

The Effect of Automated Agents on Individual Performance Under Induced Stress

Induced stress is a phenomenon commonly experienced across different fields such as emergency services, healthcare, air traffic control, sports, and business - which necessitates the development of effective coping strategies and resilience for individuals or teams performing under pressure. This study aims to examine the effects of automated agents on individual performance during high-stress conditions. The design of these agents ensures they carry out identical tasks as participants based on predetermined frameworks. Participants underwent an experimentally designed task that aimed at inducing stress while measuring their performance amidst time pressure and auditory distraction. Results indicate that working with automated agents causes individuals to alter their approach by focusing narrowly on immediate concerns - making it challenging for them to consider several options or see broader contexts accurately. Regardless of ability level participants' performances were influenced by these automated agents. Future research will explore how these findings interact with physiological signals. This study highlights the importance of developing effective coping strategies and the potential impact of social factors on individual performance under induced stress.

Lokesh Singh, Sarvapali Ramchurn

Conference Proceedings

Design of strength assistance gloves for female heavy manual workers based on visualization of electromyographic signals

In recent years, due to the disappearance of the cumulative effect of fertility, low birth rates, and aging populations, labour shortages have emerged, leading to a social trend of male labour shortages in heavy labour industries, with more women starting to fill the labour gap. By investigating the situation, population characteristics, needs, and work scenarios of female heavy manual workers, user interviews were conducted, and based on the results, the design direction of wearable labour protection equipment was proposed. Based on the collection, analysis, and visualization of electromyographic signals, it is proposed to design intelligent glove products through strength assisted structural design. This product is based on female body characteristics, taking into account the usage habits of workers related to heavy physical work, and has played a role in helping women reduce their physical burden and strengthen safety protection.

Fangfei Liu, Haina Wang, Yun Chen

Conference Proceedings

Workload analysis of courier trolley push and pull for express couriers

Express couriers typically move packages by pushing and pulling trolleys as part of their duties. Rolltainers and hand carts are the most common courier trolleys. As a result of COVID-19, online shopping has expanded dramatically around the world and express courier services have become a part of everyday life. Work-related musculoskeletal disorders (WMSDs) are prevalent occupational diseases caused by repetitive pushing and pulling activities. This study investigated the physical and subjective workloads associated with straight and curved pushing/pulling of hand carts and rolltainers for express delivery. There have been many ergonomic studies conducted on pushing and pulling tasks, however, little research has been conducted on the effects of pulling and pushing directions on hand carts and rolltainers. Twenty-three professional express delivery workers participated in the study. A push and pull delivery trolley task was assessed using EMG and subjective perceived exertion in this study. A general observation was made that BIC and UT are less activated than TRI and ES when pushing and pulling delivery trolleys. Pushing a trolley is more effective than pulling one in reducing WMSD risk. A rolltainer would be preferred over a hand cart to reduce workload. The study found that hand carts generate more muscle activity when moved in a straight direction than when moved in a curved direction.

Hong-in Cheng, Jun Jie Deng

Conference Proceedings

A Comparative Evaluation of Assistance Systems for an Instrument Reprocessing Workbench

IntroductionDigital assistant systems (DAS) can support tasks by mediating between complex data and users, promoting continuous learning and on-the-job training (Jwo et al., 2021; Longo et al., 2017; Prinz et al., 2017). Integrating a DAS into surgical instrument reprocessing, where instrument-specific and complex manual tasks need to be performed strictly according to the manufacturer's instructions, can be advantageous. In Germany, reprocessing by trained on-the-job personnel is common. In addition, human factors are often neglected in the instructions for instrument reprocessing (Choi et al., 2017). A cooperative robot can be a valuable addition to mitigate health risks associated with handling contaminated surgical instruments during reprocessing, resulting in a cyber-physical assistance system (Heibeyn et al., 2021). However, it is unclear how the transition from paper-based instructions to either a DAS or a DAS supplemented with a cooperative robot assistance (“cyber-physical assistance system” – CPAS) affects usability for complex and workpiece-specific tasks in instrument reprocessing. Therefore, this study aimed to investigate the differences in usability with different assistance systems for typical tasks in instrument reprocessing for untrained personnel.MethodsWe conducted an interaction-centered user study with 13 participants unfamiliar with the reprocessing tasks. The participants were asked to complete typical reprocessing tasks three times in a random order, using different assistance approaches each time. The reference process consisted of paper-based instructions that required stepping away from the workstation to retrieve information from the storage of guidelines, simulating common set-ups of current reprocessing processes. The first assistance approach presented digital instructions right at the workstation. The second assistant combined a cooperative robot with digital instructions. The robot performed simple processing steps, while the human operator focused on the complex tasks and verified the cleaning success. We measured the required time, counted user errors and rated the criticality, measured the perceived workload using the NASA-TLX questionnaire (NASA, 2020), and documented the remarks of the participants using the thinking-out-loud method for all assistance systems.Results The NASA-TLX did not reveal any significant differences among the three systems, however, the CPAS reduced the number of critical errors. The errors included omitted processing steps and deviations from required times, which could pose risks to patients. The DAS was perceived as a suitable way to check instructions, based on the participants’ comments. However, in the case of the CPAS, some participants missed or ignored messages provided by the user interface.Discussion and ConclusionIn summary, the CPAS improved usability the most, improving effectiveness (number of errors) while maintaining the same efficiency (total duration). Although our study found promising results for integrating a DAS or CPAS into on-the-job training assistance for novice personnel, future studies should compare the results obtained from inexperienced to those of experienced users to fully assess the usability of related approaches. This study contributes to the field of human factors by providing comparative data on usability across different levels of assistance for complex and workpiece-specific tasks in surgical instrument reprocessing.ReferencesChoi, J., Seraphina, S., & Knudsen, K. (2017). The Clean and Dirty of Redesigning Reprocessing Instructions for Use. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care, 6(1), 150–153. https://doi.org/10.1177/2327857917061032Heibeyn, J., König, N., Domnik, N., Schweizer, M., Kinzius, M., Janß, A., & Radermacher, K. (2021). Design and Evaluation of a Novel Instrument Gripper for Handling of Surgical Instruments. Current Directions in Biomedical Engineering, 7(1), 1–5. https://doi.org/10.1515/cdbme-2021-1001Jwo, J.‑S., Lin, C.‑S., & Lee, C.‑H. (2021). An Interactive Dashboard Using a Virtual Assistant for Visualizing Smart Manufacturing. Mobile Information Systems, 2021, 1–9. https://doi.org/10.1155/2021/5578239Longo, F., Nicoletti, L., & Padovano, A. (2017). Smart operators in industry 4.0: A human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context. Computers & Industrial Engineering, 113, 144–159. https://doi.org/10.1016/j.cie.2017.09.016NASA (Ed.). (2020, December 15). NASA TLX: Task Load Index. https://humansystems.arc.nasa.gov/groups/TLX/Prinz, C., Kreimeier, D., & Kuhlenkötter, B. (2017). Implementation of a Learning Environment for an Industrie 4.0 Assistance System to Improve the Overall Equipment Effectiveness. Procedia Manufacturing, 9, 159–166. https://doi.org/10.1016/j.promfg.2017.04.004

Jan Heibeyn, Ju-yun Son, Armin Janß, Klaus Radermacher

Conference Proceedings

Limited training in undergarment and clothing removal techniques to expose wounds in combat care

A critical component of combat casualty care is to fully expose the patient to identify and treat injuries. Completing these actions under stressful conditions is expected to require adequate training. In this study 21 combat lifesaver trained soldiers were surveyed regarding their recent training exposing chest injuries of male and female soldiers. Nearly all participants (95.2%) reported experience in treating male simulated patients; however, only 52.4% reported any experience applying a chest seal on a male human or simulated patient and only 28.6% reported any experience removing the t-shirt of a male human or simulated patient. Seven participants (33.3%) reported experience in treating female simulated patients, 23.8% reported at least some experience applying a chest seal to a female human or simulated patient, and only 9.5% reported experience removing the female patient’s t-shirt and, similarly, a female patient’s bra. Findings suggest a pronounced gap in the CLS training curriculum.

Nichole Morris, Curtis Craig, Katelyn Schwieters, Bradley Drahos, Marshall Mabry, Eugene Floersch, William Kessler

Conference Proceedings

Comparing Brain Activity Between Sitting and Standing Positions during Optic Flow with Coinciding Auditory Cognitive Tasks

Physical therapy intervention for people with vestibular disorders often includes optic flow stimulation. Such interventions can be performed with patients in either sitting or standing positions. Yet, little is known about how these positions affect brain activation during treatment. In this study, functional near-infrared spectroscopy (fNIRS) was used to investigate the reaction time and activation patterns of the prefrontal cortex (PFC) and temporoparietal junction VEST between sitting and standing conditions in the presence of both visual (optic flow) and cognitive (reaction time tasks) stimulation. 33 healthy adults participated in this two-visit study. In the first visit, participants were instructed to perform a series of reaction time tasks while sitting and experiencing optic flow at varying speeds through the HTC ViveTM virtual reality headset. In the second visit, participants performed the same tasks while standing. When compared with sitting, increased activation was observed in the left and right VEST for some of the standing trials. However, no statistical difference was found in the right or left PFC activation between sitting and standing positions when performing the reaction time tasks. These results suggest that, when compared to a sitting position, tasks performed in a standing position with optic flow stimulation will elicit greater VEST cortex activation, allow for multisensory integration training, and enhance positive outcomes after vestibular rehabilitation.

Brian Sylcottt, Rui Wu, Shanyue Guan, Chia-Cheng Lin

Conference Proceedings

Computerized heart rate analysis in the selection of therapy for patients with arterial hypertension

According to the World Health Organization (WHO), over 1 billion people are overweight and 600 million are obese, with metabolic syndrome (MS) affecting 35% of adults in the US and 20-25% in Europe. MS patients require appropriate therapy with comorbidity in mind, which requires further study and optimization. As part of the study, we conducted Holter ECG monitoring (HM) of patients with MS. MS was diagnosed on the basis of the MTP 3rd revision criteria. Additional criteria were AH, elevated triglyceride levels, decreased HDL cholesterol levels, impaired glucose tolerance (IGT), impaired fasting glycemia (EGS), and combined EGS/IGT disorders. MS was diagnosed based on 3 criteria: 1 main and 2 additional ones.Design. A total of 154 patients were examined in in-patient setting. They were subdivided into 2 main groups: Group I - patients with MS receiving β-blockers (n-97) to treat AH; Group II - patients with MS not receiving β-blockers (n-57).Each main group was divided according to the degree of obesity according to the WHO classification. Each patient underwent HM with programmed computer analysis of the wave spectrum of the obtained data and allocation of frequencies - 0.004-0.08 Hz (very low frequency - VLF); 0.09-0.16 Hz (low frequency - LF); 0.17-0.5 Hz (high frequency - HF) more than 0.5 Hz (ultra-low frequency waves - ULF); two coefficients are calculated - LF/HF (vagosympathetic balance coefficient) - ratio of low frequency waves power (LF) to high frequency waves power (HF), and centralization index (CI) - ratio of central regulation circuit activity to autonomic one (LF+VLF/HF).Results. Analysis found changes in HF, LF, and ULF domains of HRV spectrum, indicating transition to a more energy-intensive level of control and depletion of regulatory mechanisms. ULF(%) values above 6.9 require correction with β-blockers. The study found ULF% and VLF% values to be higher in the non-β-blocker group and administration of β-blockers resulted in normalization of indexes with the index of centralization and vagosympathetic balance. In patients receiving β-blockers, the values of these parameters corresponded to those of patients with normal body weight. In MS patients not receiving β-blockers, ULF% was 50% higher and VLF was 18% higher than in the normal weight group. The centralization index was elevated to 3.5. Administration of drugs to 17 patients in group II resulted in normalization of the indexes and achievement of the same values as in group I patients. At the dynamic follow-up for 2 years, Group I patients had no cardiovascular events. The 40 patients who refused to change therapy had no change in HM values and 27% of these patients had acute cardiovascular events at 2 years.Conclusion:Daily ECG monitoring with assessment of ULF%, VLF% and IC indices is a more subtle method of investigation, which allows to detect latent disorders of regulatory mechanisms (with seeming clinical well-being) in patients with disorders of these indices the risk of acute cardiovascular events development remains high. The control of ULF%, VLF% and IC index by HM-ECG method allows to change the therapy in time and to obtain a better result.

Irina Kurnikova, Shirin Gulova, Natalia Danilina, Artyom Yurovsky, Vladimir Terekhov

Conference Proceedings

Medical Error Disclosure in Healthcare – The Scene across Canada

The quality of healthcare is an emerging concern worldwide. Despite the advancement in the medical field, adverse events resulting from medical errors are relatively common in healthcare systems. Disclosure of an adverse event is an important element in managing the consequences of a medical error. We have previously reviewed and compared various disclosure policies that are in practice in Canada and around the globe to analyze the progress made in this area and suggested a non-punitive, “no-fault” model for reporting medical errors. The purpose of this study was to review and compare the disclosure policies implemented by individual health authorities across the Canadian provinces and territories. We evaluated each policy based on the inclusion of the following key points: Apology, avoidance of blame, avoidance of speculation, immediate disclosure, patient support, provider support, provider training, team-based approach, accessibility, and documentation. The clinical significance of the study was to evaluate various health authorities’ policies of disclosure and report a practice model for medical error disclosure across Canada. The three top parameters found within the disclosure policies include an apology or expression of regret, a team-based approach and documentation of disclosure, all three averaging at 98% respectively across the provinces and territories. The bottom two parameters found within the disclosure policies include provider training and accessibility of disclosure policy through the health authorities’ website, both averaging at 34% respectively. We believe healthcare providers' top priority should be correcting flaws in the medical system and protecting patients' health. Despite the obstacles, physicians should seek to disclose medical errors to patients and their families on both ethical and pragmatic grounds. We believe that the disclosure policies can provide framework and guidelines for appropriate disclosure, which can lead to improved quality care and practices that are more transparent. We suggest that disclosure practice can be improved by creating a uniform policy, centered on honest disclosure and addressing errors in a non-punitive manner.

Jay Kalra, Anjali Saxena, Zoher Rafid-Hamed

Conference Proceedings

The Role of Emerging Technologies in Health Emergency Planning and Preparedness

Predicting and planning healthcare utilization in disaster situations is a complex and evolving challenge that requires new tools to augment existing systems of practice. Disasters and humanitarian emergencies are an inevitable threat to the health of populations across all continents and demographics. Morbidity and mortality from natural and infectious disasters are increasing at an alarming rate, leaving health systems unprepared and overwhelmed. Artificial Intelligence (AI) has emerged as a tool with tremendous capabilities in processing vast amounts of data to provide the best available evidence to inform disaster response strategies. This study described the role, implementation, and implications of AI-augmented disaster prediction and planning. Disaster prediction was previously beyond our grasp but with the advent of AI modelling and data-driven prediction technologies are becoming a growing reality. AI technologies have demonstrated the capability to incorporate, analyse, and summarize multifaceted data sources including climate factors, environmental factors, social media feeds, movements patterns, health data, and historical records. This technology can extract meaningful patterns to provide the likelihood and severity of catastrophic events. Examples include models that analyse existing earthquake data to identify patterns of seismic activity to forecast earthquake events with growing accuracy. Similarly, the Global Public Health Intelligence Network scans headlines across the globe to detect emerging health threats. Disaster planning involves optimizing resources and supports to vulnerable populations to prepare for the possibility of acute events capable of causing mass injuries and loss of life. There are insufficient resources available to prepare all health regions and populations for the possibility of disasters. By simulating different scenarios and outcomes, AI algorithms identify high risk geographic regions and populations to inform strategic resource allocation and deployment strategies. By analysing population densities, infrastructure stability, healthcare capacity, transportation networks, shelters, AI-augmented systems can optimize evacuation roots to appropriate healthcare resources while providing specific health needs assessments of affected populations. In these ways, the implementation of AI technologies can strengthen existing disaster preparedness strategies in an iterative and evidence driven way. While advancements in certain silos are being made on a consistent basis, a collaborative system has yet to be established. The accuracy of insights provided by AI systems is contingent on availability and validity of data. AI-systems are a relatively novel rapidly evolving field with inherent weakness such as assumptions, biases, lack of explainability and data privacy concerns that pose unforeseen challenges to regulatory and legislative frameworks. While evidence driven decisions may provide the highest probability of successful disaster planning and response strategies, they can not account for the ethical and social factors that are essential to effective implementation. Effective disaster planning and preparedness is a complex and iterative process that requires collaboration among medical, policy leaders, governmental programs, non-governmental organizations, communities, and other stakeholders. Only by integrating diverse perspectives and utilizing the best tools available, can we promote resiliency and health protection for vulnerable populations across the globe.

Patrick Seitzinger, Jay Kalra

Conference Proceedings

Enhancing Daily Posture Correction: Testing a Feedback-Based Assistive Technology for Individuals with Physical Disabilities

People with physical disabilities often spend a significant amount of time in a sitting position. As a result of paralysis affecting the lower body, they may be unaware that they are assuming a high-load posture, which can contribute to issues such as pressure ulcers, shoulder stiffness, back pain, muscle imbalances, and diminished physical function. While seating technologies have been proposed to correct sitting posture, most existing methods are primarily designed for hospital settings and lack interventions for daily posture. To address this gap, we have developed a mat-type pressure-sensitive sensor device that can be mounted on a wheelchair. This device comprises 32 seat sensors and 12 back sensors, which estimates sitting posture during daily activities and provides feedback to the individual through smartphone alerts, heatmap review, and expert remote advice on posture improvement and training. This study aimed to evaluate the effectiveness of the device and identify areas for improvement.Seventeen wheelchair users with physical disabilities, including individuals with spinal cord injuries or cerebral palsy, participated in a five-week user test. Ten participants received device feedback, while seven participants did not. The device's effectiveness was assessed by comparing pre- and post-intervention outcomes and comparing outcomes between the intervention and non-intervention groups. Physical function was evaluated using a reach test, changes in internal symptoms and postural awareness were investigated through a questionnaire, and sitting posture was evaluated by the device. Additionally, Semi-structured interviews were conducted with seven participants from the intervention group to gather their perspectives on device usage and potential improvements.The results of the study demonstrated that the intervention had a positive impact on several aspects of postural change, secondary health issues prevention, and physical function improvement. Statistically significant differences were observed in a limited number of items, such as the lateral reach test results and anxiety related to pressure ulcers. The wide variance in the physical and living conditions of the participants, coupled with the fact that the effects of secondary disability and physical function take time to manifest, might have contributed to the non-significance of certain results within the five-week study period.The interviews provided valuable insights into the future direction of device improvement. Participants expressed concerns about the disparity between their perceived posture and the posture indicated by the equipment, as well as the challenges in understanding how to achieve an ideal posture. There is a recognized necessity to develop a novel feedback method that allows individuals to comprehend their posture from an external perspective and guide them toward a posture with minimal strain.In conclusion, our study demonstrates the effectiveness of the wheelchair-mounted pressure-sensitive sensor device in improving sitting posture, preventing secondary disabilities, and enhancing physical function among individuals with physical disabilities. While statistically significant results were partly observed, further research is needed to establish the long-term effects of the intervention. Additionally, the findings underscore the necessity of developing a feedback method that enables individuals to understand the discrepancy between their perceived posture and the correct posture, thus facilitating targeted posture improvement in daily life.

Nao Takizawa, Mizuki Sugawara, Isamu Watabe, Hiroshi Nakamura, Shuta Murayama, Miki Saijo, Takumi Ohashi

Conference Proceedings

A novel stimulation protocol for vestibular rehabilitation

Vestibular hypofunction due to aging or disease can be severely debilitating for daily life, causing dizziness, space disorientation, imbalance, limited mobility, and increased risk of falls. Current methods and techniques for vestibular rehabilitation often fail short of achieving stable, effective results due to the lack of physiologically-based, ergonomic approaches. Here we propose a novel approach based on the application of small-amplitude random displacements of the head and body, which can lead to enhanced vestibular function. The phenomenon we studied is akin to stochastic resonance, whereby the application of a given, optimal level of noise during periodic or non-periodic stimuli can determine an increased sensitivity in nonlinear systems, such as the vestibular perceptual system. The idea is that an appropriate level of noise can raise subthreshold stimuli above threshold, thereby making them detectable by the brain. We tested the protocol in a series of experiments involving 30 healthy young participants who were asked to discriminate the direction of whole-body motion imparted by a MOOG platform. Blindfolded subjects were presented with the discrimination of forward-backward single-cycle sinusoidal motion in a two-alternative forced-choice paradigm. The procedure followed an adaptive staircase. Vestibular threshold (i.e., minimum amplitude of applied motion that was discriminated by the subjects) was then computed from the slope of the psychometric function fitting the individual performance. We compared the vestibular threshold between the baseline condition (no external noise) and the conditions when band-limited white-noise was applied by the platform in the forward-backward direction. We found that in 26/30 participants the discrimination threshold was better with at least one noise level than that at baseline. The overall response curve roughly obeyed the bell-shaped function typical of stochastic resonance. We conclude that small-amplitude noise can ameliorate vestibular perception even in healthy young subjects. The advantage of this approach is that it is non-invasive and ecological, since it involves the application of small oscillations to the patient. Moreover, the task is easily understood since it consists of a classical discrimination paradigm.

Barbara La Scaleia, Francesco Lacquaniti, Myrka Zago

Conference Proceedings

Development of a Smart Pillbox with Passive RFID to Support Prospective Memory and Medication Adherence

The economic loss due to unused medicines is estimated at be 50 billion yen, as many people do not consume or carry their prescribed medicines due to forgetfulness. One reason for this is that people forget to take or carry their medication. Many scholars have investigated smart indoor pillboxes by linking with cameras, RFID, and web applications; however, all of them are based on the condition of being at home, or requiring a human to enter the dose to be taken. The aim of this study is to evaluate the effectiveness of a new portable smart pillbox using passive RFID in the 13.56 MHz frequency band to improve medication adherence. Unprecedentedly, in this study, a critical-function prototype of a smart pillbox using a passive RFID filter in the 13.56 MHz frequency band was developed; and passive RFID was designed after conducting a solution study. An investigation was undertaken to assess the efficacy of prospective memory in enhancing medication adherence using both normal and smart pillboxes. The objective was to ascertain if the intelligent dispenser could mitigate medication discrepancies among patients newly initiated on their therapeutic regimen. 8 students in their 20s who had previously taken their medication were selected as participants. Participants performed the disengagement decision task as a background task and the action of taking medication from a pillbox as a prospective memory task. Participants were given a smartphone and were reminded by a notification if the pillbox from which they took their medication was a smart pillbox. Performance on the prospective memory task was assessed using a semi-structured questionnaire and an interview. The findings indicate that the reminder is not the precipitating factor in the diminution of prospective memory discrepancies; rather, an overestimation of one's mnemonic capabilities emerges as a salient contributor to such errors. And, the use of passive RFID in the development of smart pillboxes shows its potential contribution to reducing prospective memory errors and improving medication adherence. By examining a broader perspective, the results of the current study are promising for widespread implementation as a method to improve medication adherence.

Shunsuke Hirayama, Daigo Misaki

Conference Proceedings

Unveiling Readiness of Medical First Responders in Simulation Trainings: Insights beyond Queries

In military deployments, medical professionals face complex operational situations that are not encountered in civilian health care practice. Defence Departments invest a huge budget of time and money to the training of military medical personnel in order to ensure medical proficiency and successful care of patients in this specific context, However, these previously trained skills may have decayed through disuse. Although past research efforts have provided a greater understanding of the mechanisms underlying skill acquisition and decay, there are still no detailed models of skill acquisition and skill decay, no understanding of mediating or mitigating factors, and more importantly no mitigation strategies in military medical tasks (Perez et al., 2013). The current paper describes the methodology to quantify performance in the framework of a project addressing this need for further research in emergency military medical care, specifically understanding and quantifying medical skill acquisition and skill decay. Method In a first descriptive part, skill acquisition and practice were investigated in a qualitative way by observation and in-depth interviews with emergency medical personnel (N = 23, nurses and physicians, from civilian and military backgrounds). In a second part, a set of methodologies was designed to objectify skill acquisition, not only by measuring outcomes (e.g. the successful intubation of a patient), but also refining the technical analyses of skills and assessing the psychophysiological readiness of the performer.Results For the first, qualitative study, all the interviewees described as a major impact on performance several examples of (extreme) stressful and/or dangerous events that they experienced during mass events, accidents, events with serious injuries and/or vulnerable victims (e.g., children), the situational context in combination with extreme high workload and patient flux. In military respondents, additional war-related aspects such as difficult and dangerous working circumstances and war-specific injuries were described. Being exposed to danger was often mentioned, even in civilian participants. Overall, personnel is continuously searching to position themselves on a continuum between emotional disconnection from the patient to preserve operationality on the one hand; and remaining enough empathic to preserve humanity on the other hand. We further identified an ambivalent awareness regarding emotions and stress; which are quoted as a major impact on performance, but without the awareness of own performance degradation. Based on these results, we decided to include an assessment of the psychophysiological allostatic load during the performance of specific skills, in order to factor this variable in when quantifying performance during simulation trainings. Considering the physical load during these trainings (running to the casualty, carrying equipment), measuring individual physiological activation does not make much sense regarding signal-to-noise ratio. Hence two other methods were adopted, which rely on the systemic measures of psychophysiological functioning. These were recordings of facial expression on the one hand, and voice analysis on the other hand. Facial expression is recorded through an add-on of the recording system equipping the simulation multi-room observation lab: the Noldus-Viso (© Noldus) system (i.e., a synchronized 4 high-quality camera system) that allows for real-live observation with a marker interface system and retrospective micro-analyses (The Observer XT) based on in-depth coding of interventions and skill performance. This combination of analyses on a macro and micro level will deliver information on what (macro) went well and what went wrong but also why (micro). The Noldus suite includes an automated emotion and action unit (AU) coding software (FaceReader7). In addition, voice recording is used and our model of Voice Stress Analysis is applied (Van Puyvelde et al., 2018). Conclusion The novel content of this project is to integrate what are usually termed “hard” and “soft” skills. Indeed, emergency medicine, and especially so in military contexts, still suffers from a historical “macho” culture. The evaluation methodology designed for the current project allows for a detailed skill acquisition analysis, by coupling the macro-outcome to micro-recordings of performance coupled to facial expression and voice recordings that offer a unique insight in health care providers’ performance.References Perez RS, Skinner A, Weyhrauch P, Niehaus J, Lathan C, Schwaitzberg SD, Cao CG. Prevention of surgical skill decay. Mil Med. 2013 Oct;178(10 Suppl):76-86. doi: 10.7205/MILMED-D-13-00216. PMID: 24084308.Van Puyvelde M, Neyt X, McGlone F, Pattyn N. Voice Stress Analysis: A New Framework for Voice and Effort in Human Performance. Front Psychol. 2018 Nov 20;9:1994. doi: 10.3389/fpsyg.2018.01994. PMID: 30515113; PMCID: PMC6255927.

Annelien Malfait, Martine Van Puyvelde, Frederic DETAILLE, Xavier Neyt, Francois Waroquier, Nathalie Pattyn

Conference Proceedings

Life History Support System “LHS” - Recording Memories and Sharing Stories for Family Social Network

The world is aging rapidly, and the population of over 65 years old in Japan is 29.1% (Sep. 15, 2022, Japan Statistic Bureau of Japan), which is the highest in Japanese history. Human memory and knowledge are rapidly being digitized on an incalculable scale. While its value as a booster for monetization is now known worldwide, such private and personal heritage, especially its whereabouts remains unknown. In particular, the memory and knowledge of elders are not recorded appropriately for the next generations, we claim that the current system has shown an enormous loss of value in society, especially for the family members. Therefore, the desire to interview and document the life experiences of different generations of family members is very important. However, interviewing and documenting are difficult to achieve for various reasons, in such cases as when family members live apart from each other. Therefore, our research group has started to develop Life History Support System called “LHS”. The new system aims to solve the problem and preserve elderlies' wisdom and knowledge cultivated in turbulent times, such as during WW II and the post-war years of recovery. The LHS is designed for the Family Social Network, allowing digital information to be accessed only by the same members. LHS is an application that runs on smartphones, tablets and PC which is connected to the Internet and works as a social network system (SNS), but the main difference between conventional SNS is (1) LHS can be accessed only by the family members or designated members, (2) it mainly works as a card type database to share topic cards among members. We have developed a prototype system using Apple’s Claris FileMaker database system which runs on-premises private server. Then, to test the prototype's applicability, we have performed a preliminary interview experiment in an actual user environment (family members living together or living apart, and the elderly person living alone). The result shows that we could identified the experience of “fun” by both, an interviewer and interviewee, during the process of recall of memories with the LHS setup. Rather, we confirm the needs in longitudinal study to capture the continuous use of the LHS. Since the LHS inherently gains its value by long-term regular use, interviewing, recording and viewing by many family members, it is necessary to add new functions based on some theories. We are planning to include gamification functions to LHS. This paper describes the LHS system overview and the current development status.

Taisei Kondo, Mikihito Otani, Takako Sinzi, Megumi Aibara, Kiyoshi Kurakawa, Kazumi Sekiguchi, Atsushi Kobayashi, Aiko Takazawa, Masakazu Furuichi

Conference Proceedings

Development of an ontology that connects clinical psychology knowledge and Top Ontology

In clinical psychology, various techniques are used to improve the mental state of subjects.．In clinical psychology, there are areas for each technique, and problem-solving cases have been reported for each area. There are various approaches to solving the same problem. Some of these elements are common and some are different. However, because they have been reported separately, knowledge sharing beyond each domain has not been carried out. In recent years, ontologies related to clinical psychology have been developed. Clinical medicine ontology CONAND (Clinical Ontology in Anatomaical Structure and Disease) and The Behavior Change Intervention Ontology (BCIO) are ontologies related to medicine and behavioral change. These are very useful for searching clinical medicine and methods for behavior modification. However, it is not possible to retrieve the specific contents of actual problem solving in clinical psychology. In order to solve these problems, it is first necessary to extract knowledge from clinical psychology cases and clarify their relationships. So far, we have extracted and structured knowledge from several case studies and the practice of one psychotherapy technique, and by conducting workshops based on this knowledge, we have elaborated the structured knowledge and formalized tacit knowledge that can be verbalized. I have made knowledge and arranged it in the structure. By structuring the knowledge and actions taken to solve the problem in a goal-oriented manner, we clarified the relationship between the procedure to achieve the goal and the practice action to clear each stage. Through these activities, clinical psychologists were able to realize the meaning of actions in the activities and practice methods that they had unconsciously performed so far, and to acquire metacognition in practice. Next, we extracted important words from this knowledge and created an ontology based on them. By having this ontology scrutinized, we would like to connect it to existing ontologies related to clinical psychology, such as CONAND and BCIO. Our ultimate goal is to make it possible to retrieve structured knowledge that visualizes how problems were solved in cases from the system. There are various techniques in clinical psychology. At present, it largely depends on the ability and intuition of clinical psychologists to determine which technique is better for solving the problem. In the future, we would like to develop AI that can propose more appropriate methods by incorporating various information into this system.

Chiaki Oshiyama, Takuichi Nishimura

Conference Proceedings

Incident response exercises and methodologies to guide best practices for incident response in healthcare institutions

In recent years, the threat of cyberattacks has been increasing annually, necessitating organizations to prioritize security measures. This urgency is particularly critical in healthcare institutions, given their status as crucial infrastructures and the potential risks cyberattacks pose to human lives. However, limited IT investment in healthcare institutions has resulted in inadequate cybersecurity measures and underinvestment in IT infrastructure. Outdated and unsupported operating systems pose significant vulnerabilities, escalating the risk of security incidents. Despite the challenges imposed by limited IT investment, organizations must strive to develop resilience that enables swift recovery in the event of a security incident, even while accepting a certain level of risk. Incident response exercises play a vital role in bolstering this resilience.Previous studies on incident response exercises have employed around 40 action cards to organize organizational processes during incidents. This process aims to enhance organizational resilience by facilitating communication within the organization during exercises. However, the importance of communication, although acknowledged during the exercises, has not been fully incorporated into the content, including the creation of incident response manuals for responders and third-party stakeholders. Moreover, there is a scarcity of research papers discussing best practices for crafting incident response manuals. This paper discusses a framework for creating incident response manuals and a methodology for implementing an improvement cycle through incident response training. The incident response manual references NIST SP800-61 and the U.S. military document "Cyber Incident Handling Program," while the incident response exercises draw from reported security incident cases to consolidate key points. Additionally, for healthcare institutions, notable considerations for incident response manuals will be explored, considering past security incident reports that have occurred in healthcare institutions in the recent couple of years. These infections can result in ransom demands, but there have also been cases of double threats where the ransom is demanded alongside the threat of leaking encrypted information. Management must decide on whether to pay the ransom, considering various factors such as public relations and apologies to individuals whose personal information has been compromised and leaked. Also, since the past incident reports indicate that Business Continuity Planning (BCP), which is used in the event of a natural disaster, was useful in the event of an incident, the Incident Command System and the Regional BCP, which is designed to coordinate with other regional healthcare systems, should be included in the considerations.Furthermore, best practices for security incidents in healthcare institutions will be organized by adopting the format of the Resilience Matrix proposed in Horizon2020. The Resilience Matrix categorizes guidelines for pre-incident preparation, incident awareness and response, and post-incident recovery, focusing on broader categories rather than individual roles or technologies. In this case, the matrix will be tailored to the specific roles of healthcare professionals to facilitate further discussions.

Kenta Nakayama, Kenji Watanabe

Conference Proceedings

Exploring the potential of human-centered design combined with narrative medicine theory for children-friendly healing environment design

Applying narrative medicine theory to the design of the healing environment is a kind of HCD thinking. This paper conducts proper user research for a children-friendly healing environment, considering children's cognitive level and stakeholders, utilises general inductive topic analysis to identify key concerns and position them as design possibilities. This paper then examines the objects' existing experience and summarises three children-friendly healing narrative design strategies based on narrative design theory. Prototypes are constructed and evaluated. This paper applies design thinking and narrative medicine theory to inventive environmental design, developing a system framework and suggestions for a children-friendly healing environment.

Jinghao Hei, Jing Liang

Conference Proceedings

Generation of User Requirements for a Mental Health Mobile Application from an Online Public Forum A Topic Modelling Approach

This research paper explores the application of topic modelling algorithms to extract user requirements for a mental health-related mobile application. Specifically, the objective is to generate themes efficiently and effectively from Reddit posts related to mental health narratives, stories, calls for help, and knowledge sharing among others. Particularly, this research examines Latent Dirichlet Allocation algorithm to generate themes coming from the posts and validate using a thematic analysis process to check similarities in generated outputs. The output will be used to establish user requirements for a mental wellbeing app to be developed for the academic community. Hence, the significance of this research. The research findings demonstrate utilizing topic modelling has promising results and categorized thematic terms from the Reddit posts. By leveraging the extracted themes, the research team can gain valuable insights into the needs and preferences of their target audience. The results offer practical implications for the design and development of mobile apps that are guided by a user-centered design process that meets the needs and expectations of the target users. The qualitative analysis further validated the relevance of the generated themes.

Raymond Freth Lagria, Lorelie Grepo, Joy Ann Malapit

Conference Proceedings

Safe Patient Handling and Mobility Programs for Overweight and Obese Patients: A Cross-sectional Survey

Healthcare providers face numerous challenges in lifting and mobilizing overweight and obese patients, which often lead to musculoskeletal disorders (MSDs). To address this, hospitals implement safe patient handling and mobility (SPHM) programs, including mechanical lift equipment, policies, and training. This study surveyed 134 healthcare workers in five Veterans Administration Medical Centers who regularly used SPHM programs. According to findings, handling bariatric patients frequently correlated with higher chronic back pain risk. Injuries occurred when not using powered equipment. Improvements like sufficient time with equipment and clear policies reduced injury likelihood. Equipment was crucial in preventing musculoskeletal injuries and pain. Findings emphasize using powered equipment and updating SPHM programs based on worker feedback for better patient handling practices.

Menekse Barim, Marie A Hayden, Edward Jr Krieg, Amy Feng

Conference Proceedings

Development of a Prospective Method for Rating Surgical Task Workloads

Surgical adverse events can have serious consequences for patients ranging from temporary injuries to death. Thereby, up to 40% of surgical adverse events are preventable and over 60% of causal factors were found to be linked to human factors. To improve surgical performance and safety, computer-assisted surgical (CAS) systems can be used to reduce excessive workloads. This paper presents a method for prospective assessment of surgical task workloads. S-TAWL, developed with the support of a senior neurosurgeon and a usability engineer, consists of three parts: surgical task decomposition, workload rating scale application, and performance shaping factors characterization. For the proposed rating scales, composed of reference operators, relative workloads were determined by 11 neurosurgeons through pairwise comparison. Afterwards, one senior neurosurgeon, not involved in method development, analysed workloads of four common surgical tasks with the proposed method S-TAWL and a reference workload rating method Surg-TLX. Qualitatively, S-TAWL provides more detailed information about workloads with respect to human resources compared to the reference method. Quantitatively, however, the reliability of the results is still limited, as indicated by high standard deviations. Further research is needed to develop reliable and valid rating scales, compute compound workloads and identify overloads. Incorporating quantitative workload assessment in prospective human performance analysis will provide valuable information for targeted model-based design of assistance systems, supporting safe and successful surgery in the future.

Sergey Drobinsky, Patrick Korte, Rastislav Pjontek, Armin Janß, Verena Nitsch, Klaus Radermacher

Conference Proceedings

The Smart Cane Project: Integrating Screen Interfaces and Physiological Sensors into Mobility Devices

Integrating sensors and screen interfaces directly into mobility devices offers individuals living with mobility issues, and medical providers, the opportunity to monitor health data and offer patient-specific therapeutic feedback in real time. This paper presents a series of prototypes that were developed in order to assess how these features can be optimally integrated into common mobility devices such as the walking cane. The early prototypes explored strategies for mounting a smartphone to a cane, as a low-cost strategy for improving mobility and reducing isolation by making use of smartphone apps for wayfinding, gait tracking, and video-conferencing. The later prototypes focused on the non-invasive integration of physiological sensors, in particular a pulse oximeter, to provide instantaneous physiological data to both the user and healthcare providers. Through a process of prototyping and critique, and integrating feedback from users, we developed an iterative series of designs that explore new strategies for affordable and easily accessible assistive technology. We conclude with a discussion of how these design strategies might be further developed and combined in order to provide more opportunities for seniors living with mobility issues to age in place.

Ian Gonsher, Adriana Salazar, Shrey Mehta, Samantha Shulman, Nicholas Gaitanis, Arshiya Khosla, Denise Danielle Tamesis, Jillian Sun

Conference Proceedings

Differences in eye movements in chest X-ray diagnosis and exploration of effective diagnostic strategies: A study in annual medical checkup conditions

During the process of medical interpretation and diagnosis in medical image, doctors’ attention allocations are various depending on individuals and cases. The process of diagnosing in the medical image involves complex interplay between visual perception and effective information acquisition strategies coupled with medical knowledge. It is difficult for doctors to explicitly explain their strategies because the process is often implicit. To date, precisely what attention allocation patterns and cognitive strategies in medical image reading, remains unknown.This study aims to uncover the doctor’s attention allocation and transition patterns in reading chest X-ray image, elicit diagnostic strategies based on doctor’s eye movements and interviews, and find the differences of diagnostic strategies between expert and novice doctors. Finally, prospective suggestions for leading novice doctors to an effective diagnostic strategy in reading X-ray image can be presented.We simulate the scenario of annual medical checkup using four patients’ cases, and recruit participants with diverse medical experiences and specialties in Tokyo Medical and Dental University Hospital to compare the differences of attention allocations between doctors. Doctors are asked to identify the lesion and give diagnostic decision to four cases. Their eye movements are recorded in the whole process by eye tracker. After completing all four cases, participants are asked to attend an interview session in which their eye movements are used as cues to elicit their diagnostic strategies. And two questionnaires are answered at last. Fixation duration, the number of fixations in each are of interest (AOI) are used to visualize doctors’ attention allocation and fixation transition patterns. Both qualitative and quantitative analysis are used to describe doctors’ diagnostic strategies and compare the differences between expert and novice doctors. Each doctor has personal characteristics when diagnosing. Doctors have a significant preference to read to current image. Doctors tend to pay more attention to areas where physiological structures overlap and where doctors think suspicious. As for diagnostic strategies, four typical patterns of change of diagnostic strategies in timeline are found. Furthermore, the differences are found between expert and novice doctors in attention allocation and the use of historical image.The effective diagnostic strategy is that performing the inspection routine of the current image separate with comparison with the historical image to avoid distracting and missing information. The comparison should focus on important areas and suspicious areas rather than the whole image. The suggested important areas are the lung apex, mediastinum, heart, left lung hilar and the lower lung field. The proposed effective strategies could be included in the medical education and new doctor training to improve novice doctors’ ability to diagnose by multiple images.

Yijia Wang, Hirotaka Aoki, Koji Morishita, Marie Takahashi, Rea Machida, Atsushi Kudoh, Mitsuhiro Kishino, Tsuyoshi Shirai

Conference Proceedings

Behavior-based Understanding of Elderly People with Dementia: A Hierarchical Classification of Daily Object Use

Providing individualized daily living care is quintessentially important to ensure the quality of life for elderly individuals, especially in nursing homes. Such care involves facilitating independent living, supporting social participation within nursing home settings, and preventing unintentional injuries such as falls. To effectively implement this, caregivers need to thoroughly understand the daily living activities of elderly people and to improve their living environments. The purpose of this study is to develop a system that can assist in planning residents' daily living care through automatically summarizing the daily activities in their rooms using depth cameras that respect privacy. The developed system consists of a function for extracting how elderly individuals use daily objects and another function for classifying behaviors based on the object use activities through hierarchical clustering. This system allows caregivers to understand the daily routines of the residents without predefining behaviors to be identified. To evaluate the effectiveness of the proposed method, the authors applied the method to analyzing 9 days’ worth of activities of an 87-year-old female resident in a nursing home. The experimental results demonstrate that the system was able to detect abnormal behaviors such as the repeated, unnatural use of drawers, without any predefined criteria for abnormal behaviors. The caregivers confirmed the utility of the system in summarizing daily behavior patterns and automatically detecting abnormal behaviors typically seen in elderly individuals with dementia.

Natsuki Shimada, Kota Noto, Koji Kitamura, Yoshifumi Nishida

Conference Proceedings

Development of "EYES": A Simulator to Experience Cataract and ICL Surgery

In Japan, more than 1 million cataract surgeries were performed in 2009, mainly for elderly persons. Moreover, ICL (Implantable Contact Lens) surgery is getting popular among the young. One of the authors’ mother had cataract surgery in 2015. When the author asked her about the experience during the surgery, the author was told that it was painless because of the anesthesia and that the surgery was completed in about 15 minutes.However, in the summer of 2022, the author underwent surgery on both eyes. The author's experience as a patient was different from what he had get from his mother. During the surgery, visual information continued to enter the brain through the optic nerve, and at the same time, auditory information entered the brain through the ears, such as the doctor's instructions to change the patient's posture and the progress of the surgery, filling the patient's consciousness with this combined information. Although this was the same as the explanation given by the doctor during the preoperative informed consent, the author could not imagine in advance what kind of visual and auditory information the patient would receive and how he would feel during the approximately 15 minutes of the surgery.As a result, although there was no pain during the surgery, the visual information was uninterrupted, and the patient felt very scared and overloaded. After the patch over my eye was removed the day after the surgery, everything seemed brighter than before, so the author felt very happy to take that surgery. However, the author would like to inform the visual and auditory information experienced during the surgery to patients who are ready for operation using simulator. Therefore, we started to develop “EYES” which generate visual and audio information using VR goggles and headphones. In the paper, we will describe the system overview of EYES, and we will demonstrate the system at poster and demonstration session.

Masakazu Furuichi, Yui Sasaki, Megumi Aibara, Takako Sinzi, Aiko Takazawa

Conference Proceedings

Evaluation and Validation of Emotional Expression Mimicry Tasks for Highly Sensitive Person Assessment

In recent years, Highly Sensitive Persons (HSP) have gained increasing attention. HSP refers to individuals with heightened sensory sensitivity, making them more sensitive to stimuli and frequently more empathetic. In this study, we focused on HSPs’ high empathy and their ability to detect subtle cues from facial expressions. We hypothesized that individuals with HSP tendencies are more likely to perceive and express minor changes in facial expressions. To test this hypothesis, we created deliberate facial expressions representing nine emotional states, i.e., happiness (four levels), neutrality (one level), and sadness (four levels). We measured mouth corner movements using the MediaPipe system, which is a webcam-based motion capture system. The subjects imitated 10 facial expressions, ranging from neutral to happy and sad, each with five levels of intensity. We then examined the correlations between the subjects’ facial expressions and psychological measures, including the Highly Sensitive Person Scale (HSPS) and the Japanese version of the Interpersonal Reactivity Index. The result exhibited correlations in specific intervals. First, there was a strong correlation in the five-level range from neutral to happy (r = 0.67). Second, there was a correlation in the interval from minor expression change from neutral to the second level of happiness (r = 0.50). Third, a correlation was observed in the interval from the second to the fourth level of happiness (r = 0.61). These results suggest that individuals with higher HSPS scores (indicating HSP tendencies) exhibit greater changes in facial expressions when experiencing happiness, which suggests that those with HSP tendencies are more receptive to subtle changes in intentional facial expression mimicking stimuli, particularly happiness.

Yuuna Ishikami, Hisaya Tanaka

Conference Proceedings

Non-Contact Sleep Stage Estimation Using Wireless Millimetre-Wave Sensor

Insufficient sleep quality has significant physical and mental health impacts on humans. However, measuring sleep quality requires a Polysomnography (PSG) test at a clinical site, which requires specialised knowledge. This study used a wireless millimetre-wave, non-contact biophysical information detection sensor to estimate sleep depth. This sensor can obtain body movements and respiratory rates from millimetre-wave fluctuations. We calculated several parameters from the respiration and body movement data obtained from these sensors and applied machine learning to create a model for estimating sleep depth. In addition, we applied the sleep stage probability obtained in advance from the sleep stages of all the experimental subjects using simple PSG as one of the sleep stage estimation parameters. The actual sleep stage was obtained using a simple PSG as a reference for machine learning. The experimental subjects were 15 healthy adults, and measurements were taken over 1–3 nights. Because some of the wireless millimetre-wave sensors did not work correctly and the first night of measurement did not provide normal sleep owing to the first-night effect, we excluded some data. Finally, nine sets of data were used for training. Sleep depth was classified into four stages: waking (W), rem (R), light (L), and deep (D). The sensitivities of this machine-learning model for each sleep depth were 51.1% (W), 27.6% (R), 81.0% (L), and 47.8% (D), and the correct response rates were 73.7% (W), 53.3% (R), 59.8% (L), and 64.3% (D). The overall accuracy is 60.5%. In the future, we will implement hidden Markov state transition probabilities in the state probabilities. In addition, sensors can detect heartbeats to improve the accuracy of sleep-depth estimation.

Ozaki Shun, Shima Okada, Masanobu Manno, Yusuke Sakaue, Masaaki Makikawa

Conference Proceedings

Harnessing Online-Delivered Cognitive Behavioral Therapy and Exercise in Preventive Mental Healthcare

In the face of escalating global mental health challenges, innovative interventions that are both effective and scalable are paramount. This paper explores the synergistic potential of combining Online-Delivered Cognitive Behavioral Therapy (OD-CBT) and structured exercise as a holistic strategy in preventive mental healthcare. Preliminary findings suggest that OD-CBT offers the benefits of cognitive restructuring and behavioral change in an accessible format, while exercise enhances mental well-being through mechanisms such as neuroplasticity and endorphin release. The integration of these two approaches on online platforms provides a promising avenue for broad-reaching mental health support, especially in traditionally underserved regions. Case studies highlight the practical application and marked benefits of the combined approach, while future directions emphasize the need for large-scale randomized controlled trials, diverse participant demographics, and in-depth qualitative research. Advocacy for policy changes, technological advancements, and broader public health initiatives can further bolster the impact of this confluence. Through a concerted effort, the intersection of OD-CBT and exercise may usher in a new era of holistic, evidence-based, and widely accessible preventive mental healthcare.

Matthew Thiese

Conference Proceedings

Exploring the Influencing Factors of Personal Loyalty to Health Passbooks: Extending the Perspective of Consumption Values

As Taiwan’s society ages, chronic disease and long-term care have become more common. The National Health Insurance Administration (NHIA) in Taiwan uses health passbooks as self-health monitoring tools to assist in disease prevention. As a result, the health passbook is widely used, and its user satisfaction and numbers have greatly increased, making it an important self-health management tool. However, a high level of satisfaction does not necessarily translate into continued willingness to use the health passbook. Therefore, this study extends consumption value theory and integrates user satisfaction with subjective well-being to explain which factors affect user loyalty to health passbooks. The subjects of the study are Taiwanese citizens who are over 20 years old and have used health passbooks. The resulting 471 valid questionnaires constituted a response rate of 90.9%. The results showed that functional, emotional, epistemic, and conditional value had positive effects on user satisfaction. Moreover, user satisfaction and subjective well-being had a positive and significant impact on loyalty. The results of this study provide valuable insights into how to enhance the willingness of users to embrace health passbooks, which is helpful for governments and hospitals to increase the likelihood of user loyalty.

Pi-jung Hsieh, Hui-min Lai, Yung-ching Yang

Conference Proceedings

Characteristics of Cerebral Blood Flow during Working Memory Tasks - Comparison of the follicular and luteal phases in females and males

In this study, we aimed to clarify the characteristics of cerebral blood flow during the N-back task for males and for females in the follicular and luteal phases. Near infrared spectroscopy (NIRS) was used to measure Oxyhemoglobin (Oxy-Hb) in the prefrontal cortex during the N-back task. In the analysis, the prefrontal cortex was divided into right and left regions, and the integrated Oxy-Hb value, center of gravity value, and activation rate (initial activation) in the first 5 seconds of the task were calculated for each region. The percentage of correct responses to the N-back task was also calculated. Differences in each representative value among the three groups (follicular phase, luteal phase, and male) were examined. The task correct response rate was lowest in the luteal phase group for males and the luteal phase group (p<.05) and in the follicular phase group and the luteal phase group (p<.05). There were no significant differences between groups in integral and center-of-gravity values, and there were significant differences between groups in the initial activation of CH10-13 (left area) during the 2-back task (p<.05), with the lowest in the luteal phase group among males (p<.05), follicular phase group (p<.05) and luteal phase group (p<.05). A decrease in working memory is suggested in luteal phase women. This may be due to the presence of women with premenstrual syndrome symptoms or to sex hormone effects.

Makiko Aoki, Satoshi Suzuki

Conference Proceedings

Organizational Climate for Health to Enhance Psychological Safety in Nursing Organizations

The roles required of nurses are becoming more diverse and complex, and the number of nurses who feel mentally unwell due to stress is increasing. One of the countermeasures is psychological safety. A workplace with a high level of psychological safety is linked to the revitalization of the organization, such as improved employee engagement and performance. In addition, it is effective in terms of mental health, such as relieving stress for employees. In this study, we examined the relationship between psychological safety and organizational health promotion support for nurses, and examined the organizational climate of health that enhances psychological safety. A web questionnaire was conducted for nurses working in hospitals in Japan, using the items of attributes, health promotion support, and psychological safety. The survey was conducted in March 2022, and the data of 377 people were considered valid responses based on the time required to respond. Respondents were 17.2% male and 82.8% female, with an average age of 43.1±9.6 years and an average of 12.6±8.8 years of service. Psychological safety scores by attribute were highest for those in their 50s, followed by those in their 20s, and those in their 30s and 40s. There was a large gap between executives and staff (F(3.019) = 0.000). Many of the items related to organizational climate of health and health promotion efforts were significantly correlated with psychological safety scores (p<0.05). The items requiring priority improvement were "high interest for health and safety of hospital organizations" and "high interest in creating a healthy working environment for hospital organizations". From the above, it is important to consider how to make the health support system known and how to promote its use so that nurses can continue to work in a healthy and motivated manner. In addition, since the psychological safety of mid-career nurses and, staff nurses without titles such as chief nurse or director of nursing, it is important to consider support specialized for them.

Yuki Mizuno, Motoki Mizuno, Yasuyuki Yamada, Yasuyuki Hochi, Takumi Iwaasa, Kentaro Inaba, Emiko Togashi, Yumi Arai

Conference Proceedings

Brain Activity Difference during Watching Social Behavior Helping Other People

Sympathy for helping other people influences motivation and performance in communication tasks and collaborative work. To promote interactive sympathy within a team, this study aims to elucidate the relationship between moral consciousness and self-construal inclination by measuring brain activity. In our experiment, participants watch video stimuli, which display moral-related scenes involving helping/disturbing behavior. We found the moral consciousness of feeling good impression was associated with the significant decrement of brain activities in the left-region, particularly dorsolateral prefrontal cortex (DLPFC), and Broca’s area. For the participants who had inclination of interdependent self-construal, brain activity decreased significantly in the left-region during watching helping behavior. This finding holds potential for assessing objectively social tendencies based on cultural and value diversity by measuring prefrontal cortex.

Taiyo Kojima, Kouki Kamada, Toru Nakata, Takashi Sakamoto, Toshikazu Kato

Conference Proceedings

Can We Distinguish Driver’s Age Based on Their Eye Movements?

In this paper we present a study aimed at distinguishing elderly (over 65 years) and young (under 25) participants in driving environment by observing solely their eye movements. Selected groups of elderly and young drivers were asked to drive 30 km on suburban, urban and regional roads in a high-fidelity motion-based driving simulator. During the drive their gaze behaviour and eye movements were recorded using the Tobii Pro Glasses 2 eye tracker, providing data on gaze position, blink rate and pupil size. The data was processed with the PyGaze library, which was adapted to be compatible with the Tobii Pro data output format. In the next step, a decision tree-based binary classification method was applied to distinguish between the two age groups based solely on their eye movements and pupillary responses. The machine learning approach showed an overall accuracy of 0.8 which means that eye tracking data can be a very good predictor of driver’s age in a driving environment.

Jason Thai, Carolina Díaz Piedra, Leandro Luigi Di Stasi, Sašo Tomažič, Kristina Stojmenova, Jaka Sodnik

Conference Proceedings

Bridging the Gap: Investigating the Role of Physiological Indicators in Capturing Cognitive State Changes among Naval Personnel

This study supplements findings from traditional cognitive assessments using physiological markers—Heart Rate Variability (HRV) and Galvanic Skin Response (GSR)—in conjunction with self-report psychological measures to better understand changes in cognitive state. Forty-nine sailors and marines completed pre-experiment surveys, including the Stanford Sleepiness Scale, the Short Stress State Questionnaire (SSSQ), and a Cognitive State Survey. These assessed various psychological parameters, including arousal, distress, engagement, and sleep quality. Resting GSR and HRV data were collected using Gazepoint Biometric sensors before and after participants completed a set of cognitive tasks. BIOPAC and Kubios software analyses revealed significant changes in several psychophysiological parameters from baseline to post-task, including average skin conductance level (SCL), minimum SCL, and maximum heart rate. Notably, a strong correlation emerged between the low-frequency power feature of HRV and the task-oriented thought score from the SSSQ and between the maximum heart rate and the distress score from the SSSQ. Despite data quality challenges that reduced the sample size, the study uncovers valuable insights into the use of physiological markers in detecting cognitive state changes. These findings highlight the potential of such an approach and underscore the need for further research.

Allison Bayro, Noelle Brown, Shannon Mcgarry, Joseph Coyne, Kaylin Strong, Mikaela Aiken, Rebecca Nesmith, Ciara Sibley, Cyrus Foroughi

Conference Proceedings

Neural Network Model for Visualization of Conversational Mood with Four Adjective Pairs

In recent years, the accuracy of speech recognition has improved remarkably. Speech recognition software can be used to obtain text information from conversational speech data. Although text can be treated as surface level information, several studies have indicated that speech recognition can also be used to estimate emotions, which represent higher level information in a conversation. Several newly proposed models use LSTM or GRU to estimate emotion in conversations. However, when attempting to monitor or influence conversations conducted as part of a meeting or a chat, the mood of the conversation is more important than the emotion. In normal conversation, emotions such as anger and sadness are unlikely to be explicitly expressed for some purposes, including avoidance of getting into an unexpected argument and offending others. Thus, when attempting to control or monitor the state of a conversation during a meeting or casual discussion, it is often more important to estimate the mood than the emotion. Some researchers have examined the role of mood, as distinguished from emotion, and one called diffuse emotional states that persist over a long period of time "mood" and are usually distinguished based on duration and intensity of expression. However, these differences are rarely quantified, and no specific durations are fixed. Accurate identification of the mood of a conversation is especially important for Japanese people who are engaged in collaborative and democratic decision making. To construct the teacher data for the model designed to estimate the conversational mood, we first selected representative adjective pairs that could describe the conversational mood. We utilized a system developed by Iiba et al. to estimate 21 affective scales of adjective pairs from input text. The 21 adjective pairs were clustered into 4 groups based on the output scales. The 4 adjective pairs to be annotated were representative of the 4 clusters. We expected these 4 adjective pairs (gloomy-happy, easy-serious, calm-aggressive, tidy-messy) to capture the mood of a conversation.Based on the four adjective pairs, we constructed a new training data set containing 60 hours of conversations in Japanese. In this study, the data obtained only by microphones are used for estimation of conversational mood. The data set was annotated by the four adjective scales to learn the mood of the conversations. We de-veloped a LSTM deep neural network model that could read the "conversational mood" in real time. Furthermore, in our proposed neural network model, the amount of laughter which is generally measured by capturing facial expression with camera is also estimated together with the conversational mood. Because laughter is considered to play an important role in creating a cheerful environment, it can be used to evaluate the conversational mood. The evaluation results are shown to present the validity of our model. This model is expected to be applied to a system that can influence or control the mood of conversations in some ways, including presentation of ambient music and aromas, depending on the purpose of the discussion, such as during a conference, chatting, or business meeting.

Koichi Yamagata, Koya Kawahara, Yuto Suzuki, Yuki Nakahodo, Shunsuke Ito, Haruka Matsukura, Maki Sakamoto

Conference Proceedings

A Framework towards Subway Safety Information Design based on Passenger's Needs for Cognition

Subway safety information includes subway safety warning information, subway safety warning information and subway emergency response information. Although different countries and industries in the world have set relevant standards for subway safety information design, it remains to be considered whether it is the subway safety information can meet the needs for cognition of passengers and whether it is suitable for the cognitive characteristics of passengers. Through the methods of literature study and case study, this paper sorts out the emergencies in the subway in recent years and analyzes the passengers 'emergency psychology and emergency behavior in the context of the emergency situation, and finally puts forward a subway safety information design framework for passengers' needs for cognition. Put forward the guidance direction for the subway safety information optimization.

Chao Xu, Jinbo Xu, Zhipeng Zhang

Conference Proceedings