Healthcare and Medical Devices

book-cover

Editors: Jay Kalra

Topics: Healthcare and Medical Devices

Publication Date: 2025

ISBN: 978-1-964867-47-2

DOI: 10.54941/ahfe1005982

Articles

The Accuracy of the Eye Tracking in a Virtual Reality Headset for Possible Research and Clinical Applications

Virtual Reality (VR) headsets are widely used in various clinical and research settings. The reliability and quality of this technology heavily rely on the accuracy of data collected by the VR headsets. The specifications of the VR headsets' accuracy are normally published by the manufacturers. However, the performance claimed by the manufacturers is rarely validated by third-party organizations. Despite its importance, limited research has been focused on the data accuracy of VR headsets, even less so in eye-tracking applications. The main purpose of this project is to invest in the accuracy of eye rotation measurements recorded by the eye-tracking system built into a VR headset. A VR headset with eye-tracking capabilities (HTC Vive™ Pro Eye) was used in this study. For testing purposes, we also developed an eye model that can simulate human eye motion on a controlled pattern with a 30-degree range. The model was used to test the eye-tracking system data collection at frequencies ranging from 10 Hz to 500 Hz, with a step size of 10 Hz. A Unity program was developed to read and export the data, from which the headset’s eye tracking accuracy was assessed at each of the tested frequencies. Our experimental results suggested that the VR headset showed great potential for precise eye rotation measurement. Overall, the correlation between the VR headset measurement and the truth reference was between 0.97 and 0.99 from 10 Hz to 500 Hz. The root mean square error (RMSE) values were from 4.39 to 4.74 for the left eye and 3.63 to 3.67 for the right eye, both in degrees. We suspect that the increased RMSE values in the right eye may be due to the relative position between the VR headset and the eye system during testing. Nevertheless, the high correlation between the measurement and truth reference indicates precision in the estimation.

Ryan Hall, Rui Wu, Matthew Joyner, Zhen Zhu, Brian Sylcottt, Chia-Cheng Lin
Open Access
Article
Conference Proceedings

Human Factors in an Agile Environment: Capturing Value in Healthcare

Increasingly, healthcare systems seem to be turning to management practices and tools used in manufacturing and software industries, including lean, to structure process improvement. They focus on identifying waste and delay to reduce bottlenecks and improve flow. There are, however, challenges to deploying such tools and methods in a healthcare environment. Expanding the ways we consider attributes such as value and waste and utilizing human factors methods to better understand how people are functioning in the system can assist with the translation of these manufacturing ideas into healthcare domains. By describing different types of value, including value associated with patient-centered care and resilient behavior, we were able to better capture important functionality of the healthcare system. We illustrate the importance of explicitly considering different types of value people may add to a system by examining the activities around delivering gastrointestinal (GI) specialty care to patients via referrals from primary care providers (PCPs). These expanded ways of looking at value and methods for understanding the activities of people within systems can contribute to better comprehension of systems and support more effective process improvement methods.

Helen Fuller, Tamara Winden, Brandon Harpold, Somer Hand, Jacob Huffman, Timothy Arnold
Open Access
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Enhanced Fall Prevention in Nursing Facilities: Assisting Caregivers through Data-Driven Selective Monitoring and Notification

Falls in nursing homes predominantly occur when elderly residents are unwatched, a situation exacerbated by critical workforce shortages in Japan where 69.3% of facilities report caregiver deficits. Our research develops a selective monitoring system that strategically targets high-risk residents through three phases: targeting (identifying risk using body temperature data), monitoring (detecting risky activities in fall-prone locations), and intervening (providing multi-channel feedback). We took an approach to predict the potential occurrence of fall accidents, as well as caregivers' intuitive "sense of risk", achieving practical results despite the former proving challenging due to data imbalance. We believe the prediction of ‘sense of risk’ could serve as a valuable proxy that translates caregivers' tacit knowledge into actionable monitoring protocols in resource-constrained environments. The system delivers notifications through alarm lamps, audio instructions, and smartphone alerts to facilitate timely intervention. Future work will focus on enriching understanding of caregivers' risk assessment, implementing near-miss reporting, and expanded usability testing. This selective approach demonstrates technology's potential to augment human caregiving by focusing on resources where most needed in aging societies.

Taihe Huang, Takuma Kano, Nao Takizawa, Takumi Ohashi, Miki Saijo
Open Access
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Examining the Efficacy of an Improved CanSim for Quantifying Hemodialysis Cannulation Skills

Cannulation of a patient’s vascular access is a daily requisite procedure for initiating hemodialysis for those with End-Stage-Kidney Disease. Skills training and assessment for hemodialysis cannulation needs attention; currently, trainees lack effective teaching tools and practice on patients—leading to stress for the cannulator and potentially multiple attempts with pain and infiltration (extravasation of blood into soft tissue) for the patient. We created a cannulation simulator (CanSim) with the goal of measuring cannulation skill and tested the hypothesis that the simulator’s process metrics are able to predict cannulation outcomes on the simulator. Data collected on CanSim from a recent study with improved simulation technology was compared with a previous dataset collected on an earlier prototype. Multiple sensors were used to measure different aspects of cannulation behavior and outcome on the simulator. The infiltration rate on the improved system was less than half that of the previous prototype (20% v 53%). Additionally, only one trial included an extra attempt (1.4%) in the new group, with 15% requiring more than one attempt on the older simulator. Analysis of performance metrics revealed key predictors of successful cannulation, specifically shallower insertion angles. These results could inform design of objective, reproducible cannulation training for providers in a safe, simulated environment.

Lydia Petersen, Joe Bible, Abhijit Kshirsagar, Lee Sierad, Ravikiran Singapogu
Open Access
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Conference Proceedings

Human Factors Engineering and User- centered Design Principles in the Design and Development of Device Combination Products for Special Patients Populations

The US Food and Drug Administration (US FDA) is a global leader in the regulation of device combination products and founded the Office of Combination Products (OCP) in December 2002, Combination products range from physical or chemical combinations to products packaged together and separately packaged products that need to be used together. The OCP has developed many policies and guidance, in particular, the US FDA Human Factor Guidance, the regulatory lens for this paper (1, 2). In the Combination Product Human Factors component, the US FDA, similar to other leading agencies, in Europe, China, Japan, and WHO, stresses the importance of usability studies in medical device combination product design to promote patient ease of use and error reduction. This guidance further emphasizes the physical safety features of the device when used by the end-user. Device design flaws can cause injury to the end user and prescription compliance to the patient. End-users refer to healthcare practitioners: pharmacists, nurses, doctors administering the drug to the patient, or the patient administering it to oneself (4, 5). The 2024 US FDA draft and China’s National Medical Products Administration (Final, Oct. 2024) guidance are closely aligned in requiring manufacturers to use user-focused design principles in the design and development of new drug delivery devices and recommend specifications based on rigorous usability research rather than technical properties of device components (6, 7). New pharmaceutical products are generally developed for most of the population and largely exclude the special segments of the population which include pediatrics, geriatrics, and people with debilitating diseases or specific physical impairments. (1) Geriatric Population: Impaired vision, cognitive decline, motor sensory challenges.(2) Pediatric Population: Pediatric drug delivery systems repurposed from adult formulations and devices are difficult to administer, leading to compliance issues. Off-label use, physician- directed and Adult devices are difficult to use in pediatrics, i.e. Nasal, meter-dose, and dry powder inhalers. (3) Patient disabilities such as hand dexterity, and color blindness.(4) Patients with specific illness or disability: Rheumatoid Arthritis - Did you test your device or container closure with an arthritic glove; Schizophrenia - Very sensitive to any change in drug product appearance or design. There is a case for including Human Factor Engineering-led user-centric design principles and usability research in designing and developing device combination products targeting these special patient populations (8, 9, 10, 11).References1. Lauritsen, K. J., & Nguyen, T. (2009). Combination products regulation at the FDA. Clinical Pharmacology & Therapeutics, 85(5), 468-470.2. Tian, J., Song, X., Wang, Y., Cheng, M., Lu, S., Xu, W. & Zhang, X. (2022). Regulatory perspectives of combination products. Bioactive Materials, 10, 492-503.3. Schillinger., D. C. (2004). The office of combination products: its roots, its creation, and its role. 4. Jackson, J. (2022, July 11). FDA “hit list” of highest priority medical device for human factor guidance, Blogarithmic Thinking, Starfish Medical.5. World Health Organization. (2022, July). WHO global model regulatory framework for medical devices including in vitro diagnostic medical devices6. Food and Drug Administration. 2024. , Guidance for Industry and FDA Staff. Purpose and Content of Use: Related Risk Analyses for Drugs, Biological Products, and Combination Products. Rockville: Food and Drug Administration.7. ClariMed. (2024, Aug). New NMPA Human Factors Guidelines for Medical Devices in China: What Manufacturers Need to Know.8. Espinoza, J., Shah, P., Nagendra, G., Bar-Cohen, Y., & Richmond, F. (2022). Pediatric medical device development and regulation: current state, barriers, and opportunities. Pediatrics, 149(5).9. Djukic et al., 2020). Training improves the handling of inhaler devices and reduces the severity of symptoms in geriatric patients suffering from chronic obstructive pulmonary disease.10. Schneider, A., Richard, P., Mueller, P., Jordi, C., Yovanoff, M., & Lange, J. (2021). User-Centric Approach to Specifying Technical Attributes of Drug Delivery Devices: Empirical Study of Autoinjector- Cap Removal Forces. Patient preference and adherence, 159-168.11. Randal McCarthy, R & Li, Z (2024, Feb.). The Role of Human Factors in the Design of Drug Delivery Systems to Optimize Patient and Heath Care Provider Use and Compliance, US Annual Medical Device Human Factors and Usability Engineering Conference, Boston.

Randal Mccarthy
Open Access
Article
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Patients over Process: Stratifying Risk in the Design, Development, and Deployment of Artificial Intelligence in Healthcare

The global focus on artificial intelligence (AI) in healthcare and medicine is on the rise. Despite remarkable progress in integrating AI into clinical workflows, gaps in regulation remain a prevalent issue within healthcare systems. Effective regulation of artificial intelligence in clinical practice is essential for managing medico-legal risk and ensuring patient safety. Numerous studies highlight the significant potential for medico-legal risk and the need for clear guidelines on the ethical and safe use of AI in clinical practice. Although there are various concerns that these guidelines must address, our work focused on researching best practices regarding patient-centered factors like patient autonomy, trust and transparency, privacy and security, equity and fairness, and ensuring human oversight. While challenges in AI workflow integration arise from many factors, including human interactions and system inadequacies, the focus on individuals rather than the system has fostered an unsuitable culture for enhancing patient-centered care. Key focus areas include risk stratification strategies and increasing transparency within this inherently complex system, as they play a crucial role in guiding clinical decisions in patient management. Proper integration of AI regulatory frameworks into clinical practice is essential for addressing gaps in the design, development, deployment, and long-term monitoring of AI solutions. Globally, the regulation of AI in clinical practice is continually evolving as governments and legal systems adapt to the rapid advances in AI as a medical device (AIaMD). In Canada, a strategic path forward prioritizes federal and provincial regulations; however, at this stage, they remain fragmented. We advocate for the establishment of uniform guidelines that address the risks, benefits, opportunities, and best practices as AI technologies are integrated into the clinical workflow. Achieving a national standard with clear guidance on the ethical and safe use of AI in clinical practice is recommended to move forward.

Bryan Johnston, Jay Kalra
Open Access
Article
Conference Proceedings

Using Design Thinking to Improve Student Feedback in Healthcare Simulation

Patient safety remains a critical global challenge, with medical errors contributing to an estimated 400,000 deaths annually worldwide. Simulation-based training, particularly using Standardized Patients (SPs), has emerged as a promising approach to reducing such errors by providing medical students with realistic, hands-on learning experiences in a safe environment. SPs play a multifaceted role in simulation training, including designing case scenarios, delivering feedback, and ensuring the consistency of simulation outcomes. However, despite their importance, SPs face significant challenges in providing effective feedback, often due to limited resources, support, and the complexity of balancing multiple responsibilities. This paper explores the challenges SPs encounter in the feedback process and investigates strategies to better support them in their roles. It also examines the potential of design thinking—a user-centered, innovative problem-solving approach—to enhance SP training and improve the quality of feedback delivery. By engaging stakeholders such as medical educators, SP trainers, and students, this study aims to contribute to the development of more effective and supportive simulation training practices, ultimately enhancing patient safety and the quality of healthcare education

Swetha Anand
Open Access
Article
Conference Proceedings

Elicitation of risk perception strategies in emergency rooms based on KYT technique and eye tracking stimulated retrospections

In the present paper, we aim at eliciting risk perception strategies from medical doctors and nurses in emergency rooms (ERs). In the research processes, a series of cognitive task analyses including an effective debriefing procedure aided by eye movement recordings as well as eye movement data interpretation scheme are developed to identify individual risk perception strategy and its characteristics. To uncover the cognitive processes performed to find risks/hazards in an ER, we adopt KYT (KIKEN YOCHI Training, hazard prediction training in English) technique. In this technique, examples of various photos found in an ER (e.g., photos in which doctors are caring a patient moved by an ambulance) are shown to a medical staff. By seeing the photos, he/she is asked to explain what are risks, hazards, and potential issues. We record his/her eye movements to analyze his/her risk perception processes. In addition, we use the data as cues to verbalize his/her cognitive processes to obtain elaborated information regarding hidden cognitive processes.A series of KYT-styled experiments in which 15 medical doctors majoring in emergency and critical care medicine and 14 nurses participated were carried out. Six photos were shown to each participant. The photos were taken at ER/ICU in Tokyo Medical and Dental University Hospital. The participant was asked to see the photo based on the assumption that he/she see it in his/her daily working conditions, and what he/she would do in the given situations. Additionally, we asked him/her whether he/she found something relating to hazards/risk. During seeing photos, the participant’s eye movements were recorded. Immediately afterwards, an interview where eye tracking recordings were used as cues to verbalize the participant’s implicit cognitive/perceptional processes during seeing was conducted.Based on the verbal protocols obtained in the interview session, each participant’s cognitive/perceptual processes were carefully traced. In addition, the areas/objects to which most of attention (i.e., more than 80% of time spent) were paid in photos were clearly identified for each participant. From these results, we could find that the exist clear difference between doctors and nurses in risk perception strategies. Medical doctors tended to focus their attention mainly on information sources related to a patient’s vital signs. Nurses, on the other hand, seemed to pay their attention not only to vital signs, but also to information sources related to patient’s mental situation (e.g., a patient’s face to know his/her hidden needs) and other medical staffs to know the status of workloads. Based on all results as well as implications obtained, we discuss insights relating to effective medical care teams composed by doctors, nurses, and other co-medical staffs.

Hirotaka Aoki, Koji Morishita, Takanori Urano, Tomohiro Adachi, Mai Kinoshita, Atsushi Kudo
Open Access
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Advancing Scoliosis Treatment: Development and Evaluation of Anisotropic Textile Brace (ATB) for Enhanced Patient Compliance

Adolescent Idiopathic Scoliosis (AIS) presents significant challenges in treatment adherence, particularly with traditional full-time hard braces, which are often uncomfortable and psychologically burdensome for patients. This study focuses on the development and evaluation of a new generation of Anisotropic Textile Brace (ATB) designed to enhance patient compliance by improving comfort and flexibility while maintaining the efficacy of traditional braces in reducing spinal curvature.Our research addresses the limitations of existing rigid braces. The ATB incorporates intelligent padding and an exoskeleton with hinged vertebrae. These innovations aim to provide corrective forces and optimize treatment outcomes.The study involves a systematic clinical wear trial with 30 subjects aged 10 to 16, diagnosed with AIS. Throughout the trial, we assessed the effectiveness of the ATB using full-spine coronal and sagittal X-ray imaging with an EOS system, measuring parameters such as Cobb angle, pelvic tilt, sacral slope, and lumbar lordosis.Preliminary results suggest that the ATB maintains or reduces spinal curvature without increasing patient discomfort. Continuous feedback from participants regarding wear comfort and flexibility informed iterative design improvements. This study demonstrates the potential of the ATB to revolutionize scoliosis treatment by balancing functionality with enhanced patient compliance, ultimately improving long-term outcomes for AIS patients.

Jingyi Ma, Ka Po Lee, Kenneth Man Chee Cheung, Kai-yu Tong, Joanne Yip
Open Access
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Biological evaluation of antimicrobial treated textiles

Textiles provide a suitable environment for the growth of microorganisms, including fungi and bacteria. Their presence can have detrimental effects on both the fabric and the user. These effects may include unpleasant odors, fabric discoloration, a higher risk of contamination, and a decline in the material's mechanical strength. The transmission of infections through textiles can be mitigated by using antimicrobial fabrics, which either eliminate pathogens on contact or inhibit their reproduction before they spread to another surface or individual. Antimicrobial textiles are created by applying antimicrobial agents to textile substrates or by utilizing fibers that naturally possess antimicrobial properties. This paper is mainly focused on the biological evaluation of antimicrobial treated textiles with doxycycline and collagen hydrolysate. The textile structures were obtained from different fibers such as polyester (PES), cotton/elastane (CO/EL) and cotton/polyester (CO/PES). The antibacterial treatment was carried out by applying the obtained solution on the textile structures using the padding method. The characterization of the treated textiles includes the release profile of active compound, the evaluation of antibacterial activity on two bacterial strains Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), as well as the assessment of cell viability by MTS and LDH assays. The release kinetics of doxycycline from the textile structures showed a burst release in the first 30 minutes followed by a slow and sustained release until the end of the experiment. The samples presented good results in terms of antimicrobial activity on both bacterial strains, the effect being classified as satisfactory. The viability of HUVEC cells is places between 90.89-95.99%, while the necrosis has low values between 4.01-9.11% suggesting that the antibacterial treated textiles can be considered non-cytotoxic. The obtained results confirm that the textile structures treated with doxycyline and collagen hydrolysate can be used as functional antibacterial textiles in direct contact with human skin.

Alina Vladu, Emilia Visileanu, Alexandra Gabriela Ene, Madalina Georgiana Albu Kaya, Viviana Roman, Carmen Gaidau
Open Access
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Ergonomic investigation on Interventional Radiology in the era of robotic surgery

Interventional Radiology(IVR) is a minimally invasive treatment by using the small-caliber catheter and X-ray fluoroscopy. As the IVR technique can perform the dilation, occlusion and selective cannulation of the vessel and digestive canal without open-surgery, so demand and clinical cases have increased rapidly. However ergonomic problems of IVR had not been considered. Ergonomic problems during the IVR procedures of arterial catheterization are analyzed and investigated in this study. There are ergonomic problems such as neuro-muscular fatigue and asthenopia due to remote operation under X-ray fluoroscopy, small caliber catheters and inadequate working postures. Development of robotic catheter manipulator for IVR partially solved these problems. However, developments of robotic catheter manipulator are still limited such as coronary and carotid artery diseases, and manual operation by the physician still remains. Ergonomic and technological problems of IVR treatments should be further resolved through further workflow analysis of medical devices and medical staffs.

Kazuhiko Shinohara
Open Access
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Self-monitoring of blood glucose: The perception of physicians who care for older adults in a health service in Mexico

This paper presents the perception of the process of glucose self-monitoring by older adults diagnosed with type 2 diabetes mellitus. The study was conducted in a health service in Mexico using semi-structured interviews to physicians and it was based on the behavioural model. Diabetes mellitus type 2 (DM2) is one of the 3 main causes of death in Mexico. The self-monitoring of blood glucose (SMBG) behaviour is one of the most valuable tools in controlling of diabetes. In health care, it is common for interventions to be developed, implemented or evaluated to promote healthier lifestyle behaviours for patients; however, these interventions are often designed without an analysis or diagnosis to determine what needs to be changed to change the behaviour. This work focuses on the perception of people working in Mexican health services that provide medical care to the older adult population diagnosed with T2DM. The objectives of this research were: (1) Identify the organizational aspects that influence or affect the use of the blood glucose meter (BGM) in elderly patients with T2DM; (2) define the barriers and enablers for older adults to use the BGM detected by clinician in patients with T2DM and whether these characteristics differ with the rest of the population diagnosed with T2DM and; (3) understand the importance of the BGM for the treatment of T2DM in an elderly patient. Six semi-structured interviews with clinicians with specialization in Family Medicine (FM) of the first level of the Mexican Social Security Institute (IMSS) were undertaken. The interviews were divided into five aspects: (a) Clinicians’ background, (b) context and support by IMSS, (c) glucose meter in home and use, (d) information that patients receive, and (e) barriers and enablers to use the BGM. A thematic analysis of the qualitative data collected in the interviews with the clinicians was carried out to identify, analyze and report the patterns. The coding of the themes was based on the theory of the COM-B model. As a result of the interviews, it was identified that SMBG is composed of three different behaviours and that each behaviour requires different capabilities, motivations and opportunities. In order to perform the SMBG behaviour, clinicians considered 12 physical capacities necessary, 22 psychological capabilities, seven physical opportunities, three social opportunities, five reflective motivations and two automatic motivations. Physicians consider that older people have barriers to achieving the behaviour. The study further demonstrated that the target behaviour of SMBG use is not only the interaction with a single medical device; rather the older adult is required to interact with four medical devices to achieve SMBG.

Stephanie Daphne Prado-jimenez, Rosa Rosales-cinco, Carlos Aceves-gonzalez, Alexandra Lang
Open Access
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Socio-Technical Risk Analysis for the Digitalized Transfusion Process: the e-TRAST Tool

The digital transformation of the healthcare sector, while innovative for diagnoses and treatments, presents new challenges related to patient safety and the need to maintain a patient-centered approach. Among complex healthcare contexts, the transfusion sector, inherently both safety-critical and mission-critical, is increasingly characterized by the integration of digital solutions. These technologies, which play a crucial role in managing clinical data and supporting medical decision-making, are essential for ensuring the safety and efficiency of the transfusion process. However, the adoption of such tools has highlighted the need to consider Human and Organizational Factors (HOFs) to ensure the effective and safe integration of technology in high-risk healthcare settings. Although studies and hemovigilance reports have pointed out significant errors—including interoperability issues and inadequate management of IT alerts—that increase process complexity and risks, the literature has shown a lack of models to address these challenges. This master's thesis aims to fill this gap by exploring the impact of digitalization on the transfusion process through a qualitative and quantitative analysis of the risks associated with the interaction among technology, operators, and organizational structure.Methodology: The research process was developed in three main phases. First, a literature review was conducted to identify and classify relevant HOFs in the context of digital healthcare. Then, these findings were integrated into a risk analysis applied to e-health solutions in the transfusion process, resulting in the development of a theoretical model and the creation of a practical tool implemented in an Excel file. This tool was subsequently validated in collaboration with two hospitals and the developer of the software under analysis. Finally, the methodology was tested in a transfusion department of a hospital in Lombardy to calibrate the tool's parameters and verify its effectiveness.Results: The e-TRAST (digitalized Transfusion Risk Analysis from a Socio-Technical perspective) framework was developed by integrating Failure Modes, Effects, and Criticality Analysis (FMECA) with the Cognitive Reliability and Error Analysis Method (CREAM). This combination enables an in-depth analysis of failure modes within the digitalized transfusion process and their root causes. The tool’s underlying logic supports both safety and risk assessments that incorporate human, organizational, and technological factors, providing a holistic perspective on risk and facilitating the contextualization of e-health solutions within their operational environments.The Excel tool revealed that over 25% of failure modes present a higher likelihood of occurrence than previously estimated when human and organizational factors are considered. This tool proved to be effective in pinpointing areas for improvement—both for healthcare institutions, through enhanced training programs and stress management strategies, and for technology developers, by addressing system usability and reliability. In conclusion, the e-TRAST framework facilitates the safer and more efficient adoption of digital technologies within high-risk healthcare environments, ensuring patient safety and operational effectiveness.

Chiara Fasanotto, Annalisa Corradi, Rossella Onofrio, Paolo Trucco
Open Access
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Wearable sit-to-stand-up (STS) Guiding Device Using Asymmetric Vibration Speaker

The lack of physical therapist (PT) resources has become a global problem [1]. The sit-to-stand-up (STS) training is one of the most important PT programs to improve the elderly’s mobility and prevent falling. In this research, a wearable (STS) motion navigation system utilizing asymmetric vibration techniques has been developed. Aiming to help the elderly do PT programs at their own house instead of paying the high cost and difficulty of making an appointment for PT.The asymmetric vibration method in this research uses a vibration speaker to play the asymmetric amplitude signal that drives the speaker to generate a vibration that could have a practical feeling, like pushing or pulling [2]. This kind of poke feeling is similar to the guiding training that the PT doctor is poking the shoulder to direct the motion. Based on this method, our lab has developed an upper-limb rehabilitation training system [3] and a walking training system [4][5]. For this research, the STS motion has been picked up from the PT program. The guiding system mainly has two functions. (a) the first is according to the user’s current STS motion by using an IMU sensor. The system could generate an asymmetric vibration from the vibration model which is attached to the front side of the chest or the back side of the neck to guide the user to lean the body. This will match the key index of the PT training of the recommended STS motion. This will decrease the required torque on the body joint due to this kind of motion [6]. User under the guidance could stand up easily. (b)The Second function is for the sitting down motion, the system will calculate the COG position according to the age, height, and gender information that is input to the system. It will calculate the balanced COG moving tunnel and according to the detected angular data and acceleration for judge the current situation needs what kind of revise. Guide the user through the asymmetric vibration to sit down in a balanced way, preventing falling down.To achieve these two functions, the following points have been researched. 1) The definition of the recommended STS motion was calculated from the simplified 3-D human model by the condition of COG position and the muscle simulation 2) The suitable asymmetric vibration setting was researched in the wave shape frequency and the power. We invite volunteers to vote for the poke feeling and choose the sensitive position around the upper body, 3) The guiding quality was evaluated by the volunteer experiment in the repeated test and the STS motion timing judgment. 4) the guided learning angular data from the volunteer was recorded by motion capture system and compared to the recommended database for evaluating the quality of this system. From the motion comparison results, our proposed device's effectiveness could be evaluated.Reference:[1] N. Hori S., et al., “Trends in outpatient rehabilitation practices in Japan: analysis using the National Database of Health Insurance Claims Open Data,” J. Rural, pp. 125–130, 2022. [2] T. Tanabe, H. Yano, and H. Iwata, “Properties of proprioceptive sensation with a vibration speaker type non-grounded haptic interface,” IEEE Haptics Symposium, pp. 21–26, 2016. [3] H.Y. Duan, T. Q. Wang, H. Lee, E. Tanaka, A Wearable Haptic System for Rehabilitation Based on the Asymmetric Vibration, SII2021, pp. 815-816, (2021).[4] E. Tanaka, H. Y. Duan, K. Osawa, K. Nakagawa, H. Lee, L. Yuge, Development of a Walking Promoter Using Vibration Speaker, LIFE2022, pp. 20-23.(in Japanese)[5] E. Tanaka, K. Osawa, J.-R. Zhuang, X. Wu, Y. Hua, K. Nakagawa, H.-H. Lee, and L. Yuge, “Development of walking assistance devices considering the users’ psychological and physical status,” The 16th IFToMM World Congress (WC2023), pp. 152–162, 2023. [6] E. Tanaka, K. Osawa, J.-R. Zhuang, X. Wu, Y. Hua, K. Nakagawa, H.-H. Lee, and L. Yuge, “Mechanical design of a standing-up assistance apparatus of leaning forward the upper body which can be transformed into a flat-lying posture,” JSME, pp. 712–727, 2011.

Shenghao Yin, Jun Zhou, Keisuke Osawa, Kei Nakagawa, Eiichiro Tanaka
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Enhancing Motor Performance in Pediatric Cerebral Palsy: A Preliminary Study on Soft Knee Robotic

Crouch gait is a common pathology in individuals with cerebral palsy (CP), significantly affecting their daily activities. The soleus and gastrocnemius muscles in their shank are often too weak to generate sufficient force against body weight. Soft wearable robotics are compliant, lightweight, and portable. In this study, we aimed to address the gap in soft knee robotic systems for children with CP. This paper introduces the design of a textile-based knee actuator and a control system. It investigates the feasibility of this soft knee robotic system through a preliminary study involving two children with CP. The study includes 20 walking sessions to assess the system's performance.Methods: The actuator of the soft knee robot uses a PVC Nylon composite textile material. The actuator is worn on the back of the subject’s knee joint with a skin-friendly textile brace. The unilateral weight of the soft knee brace is only 0.2 kg. Two ground reaction sensors are placed on the forefoot and heel of the subject to detect gait events during the walking cycle. When the heel strikes the ground, the actuator inflates to assist knee joint extension until toe-off. The subjects participated in training twice a week, totaling 20 sessions over 10 weeks. Each session included 30 minutes of walking training with the soft knee robot.Results: Preliminary training results demonstrated the feasibility of the soft knee robot in improving crouch gait. The knee flexion angles of both subjects were reduced (Subject 1 from 20.56° to 1.9 ° and Subject 2 from 24.21°to 12.1°) during the mid-stance phase after 20 training sessions. The Modified Ashworth Scale (MAS) score of the paretic side knee joint reduced from 1+ to 0 and from 1+ to 1 respectively, indicating an improvement in muscle tone of the spastic knee joint. The subjects' gross motor function scale showed improvement.Conclusion: This work demonstrates the validation of the soft knee robot protocol for extension support in crouch gait with pneumatic and comfortable assistive torque. The pilot testing results indicate that the soft knee robotic system improves knee control and locomotor function during walking.

Dezhi Liang, Shuk Fan Tong, Alistair Mcewan, Darryl Chiu, Joanne Yip, Kai-yu Tong
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Conference Proceedings

Evaluating Clinical Efficacy of Optical Motion Tracking with Real-Time Animation for Rehabilitation Monitoring

Rehabilitation is a cornerstone for recovering motor function following conditions such as stroke, Parkinson’s disease, aging, or surgery. These conditions often result in musculoskeletal, neurological, or sensory dysfunctions that impair Activities of Daily Living (ADL), delaying recovery. Clinical studies have shown that repeated rehabilitation programs significantly enhance recovery outcomes. Motion capture systems (mocap) provide a robust method to monitor rehabilitation progress, diagnose biomechanical disorders, and adjust treatment plans. This study evaluates the clinical effectiveness of optical motion tracking systems by conducting quantitative kinematic analyses and integrating real-time animation streaming. The study utilized the OptiTrack motion capture system equipped with seven Flex 13 optical cameras and Motive Tracker software to record movement data. Five healthy participants (aged 19–29 years, M=23, SD=3.67; height 170–195 cm, M=181.6, SD=9.63) were recruited to perform three biomechanical tasks: gait, single-leg squat jump, and straight-leg sidewalk. Movements were analysed under normal and braced conditions to investigate key kinematic variables: knee flexion, dorsiflexion/plantar flexion, and hip abduction. Motion capture data was processed in MATLAB for 3D transformation matrix calculations, and the results were streamed into Unity3D to create real-time animations for visualization.Statistical parametric mapping (SPM) paired t-tests (α=0.05) revealed significant differences between normal and braced conditions. During gait, knee flexion range of motion (ROM) was reduced by 32.06° under braced conditions, indicating a limping motion with limited vertical swing-phase movement. In the single-leg jump test, braced conditions resulted in a 7.2° increase in plantar flexion and reduced jump height, while normal conditions demonstrated greater dorsiflexion and knee flexion, indicating compensation. For the sidewalk test, braced conditions showed reduced hip abduction and increased lumbar engagement, with lumbar flexion increasing from 16.82° to 30.89°, suggesting alternate muscle activation patterns. Real-time animation in Unity3D successfully visualized participant biomechanics, offering potential as a recreational and engaging tool for rehabilitation. While the system provided statistically significant data and detailed motion analyses, there are some limitations in the current approach. The rigid-body tracking method required extensive filtering to mitigate inaccuracies caused by marker occlusion and auto-solve algorithms. This approach differs from dynamic skeletal models, which typically integrate lower-body kinetic plugins, and therefore required additional post-processing to accurately calculate joint angles. In real-world applications, factors such as environmental conditions (e.g., lighting and reflective materials), patient behaviour, and movement variability must be considered. Expanding the study to include a diverse range of injury types and larger, more varied sample sizes will be important for understanding how motion capture can be seamlessly integrated into rehabilitation programs. Machine learning could automate the processing of motion data, enabling faster diagnosis and real-time tracking of movement disorders, such as gait abnormalities or Parkinson's symptoms. Furthermore, the integration of virtual reality (VR) with real-time animation could create more immersive rehabilitation experiences, enhancing patient engagement and motivation during therapy. Real-time applications could also enable home-based monitoring, allowing patients to continue their rehabilitation remotely, while clinicians track progress and provide personalized feedback from a distance. Augmented reality (AR) apps could further enrich this experience, guiding patients through exercises with interactive visuals and real-time feedback.This study highlights the growing potential of motion capture systems, combined with advanced computational tools, to transform rehabilitation. By optimizing motion tracking, enabling more personalized treatment, and improving patient engagement, these technologies have the capacity to enhance recovery outcomes and improve the accessibility of rehabilitation programs.

Kartikeya Walia, Kaivalya Raval
Open Access
Article
Conference Proceedings

Usability Testing of Healthcare Portals for Individuals with Mental and Physical Disabilities: Assessing Accessibility and User Experience (UX)

As healthcare continues to become more digital, patient portals have become essential tools for patients in their healthcare experience, including but not limited to accessing electronic healthcare records (EHR), scheduling appointments, and messaging healthcare providers. Despite widespread use of these tools, challenges with accessibility continue to exist, disproportionately impacting individuals with cognitive and physical disabilities. This study investigates the usability of healthcare portals for this population with usability mixed-methods tests with individuals experiencing cognitive or physical disabilities to assess how well their needs are met with online patient portals. Ten participants completed nine tasks representative of routine healthcare interactions. Quantitative results indicated that participants with physical impairments took three times longer to complete tasks such as scheduling appointments and locating lab results. Qualitative data revealed shared frustrations across all participants, with many expressing confusion over inconsistent terminology. Emotional hesitation was common, driven by fear of making an irreversible mistake. The findings suggest that task-specific improvements such as simplified navigation and real-time feedback cues are beneficial to ensuring equitable digital health access for users.

Janelle Wilson, Duha Ali
Open Access
Article
Conference Proceedings

Directional Kinetic Characteristics of Drop Landing for Patients with Functional Ankle Instability

This study aimed to investigate the kinetic characteristics, potential injury risk factors, and energy dissipation strategies of bilateral lower limbs during multidirectional drop landings in patients with unilateral functional ankle instability (FAI). Methods: Fifteen male patients with unilateral FAI participated in this study. Kinetic data were synchronously collected using a Vicon infrared motion capture system and a Kistler 3D force platform during single-leg drop landings performed in three directions (forward/oblique/side, FL/OL/SL) for both the unstable and stable limbs. A repeated-measures analysis of variance was conducted to compare the kinetic performance across directions and between sides. Results: Peak vertical ground reaction force (PvGRF), the time to PGRF in the vertical and lateral directions, the loading rate, and hip joint torques were affected by direction (p < 0.05). Hip torques at initial contact were significantly influenced by limb side (p < 0.05), and an interaction effect between direction and side was observed for ankle plantarflexion torques (p < 0.05). Specifically, the unstable limb ankle plantarflexion torques in FL and OL were lower than those in SL, while on the stable limb, plantarflexion torques in FL were lower than in OL and SL. Furthermore, plantarflexion torques were greater in the stable limb than in the unstable limb during FL and OL (p < 0.05). Conclusions: OL exerted higher medial ankle impact forces, while SL, which combines forward and lateral loading components, placed higher adaptive demands on the unstable ankle. FAI patients relied on compensatory strategies, with increased dependence on the stable limb for energy dissipation during drop landing movements.

Marilyn Meng, Yubo Wang, Qiuxia Zhang
Open Access
Article
Conference Proceedings

Integrating Explainable Machine Learning Techniques for Predicting Diabetes: A Transparent Approach to AI-Driven Healthcare

Diabetes mellitus is a global health concern affecting millions worldwide, with profound medical and socioeconomic implications. The increasing adoption of machine learning (ML) in healthcare has revolutionized clinical decision-making by enabling predictive diagnostics, personalized treatment plans, and efficient resource allocation. Despite their potential, many ML models are often regarded as "black boxes" due to their lack of transparency, which raises significant challenges in critical fields like healthcare, where explainability is crucial for ethical and accountable decision-making (Hassija et al., 2024).Explainable Artificial Intelligence (XAI) has emerged as a solution to address these challenges by making ML models more interpretable and fostering trust among healthcare practitioners and patients. This paper explores the integration of XAI techniques with ML models for diabetes prediction, emphasizing their potential to enhance transparency, trust, and clinical utility. We present a comparative analysis of popular XAI methods, such as SHAP (Shapley Additive Explanations), LIME (Local Interpretable Model-agnostic Explanations), and attention mechanisms, within the context of healthcare decision support. These techniques are evaluated based on interpretability, computational efficiency, and clinical applicability, highlighting the trade-offs between accuracy and transparency.The study underscores the critical role of interpretability in advancing trust and adoption of AI-driven solutions in healthcare, while addressing challenges such as balancing model performance with explainability. Finally, future directions for deploying explainable ML in healthcare are outlined, aiming to ensure ethical, transparent, and effective AI implementation.

Casam Nyaga, Ruth Wario, Lucy Gitonga, Amos Njeru, Rosa Njagi
Open Access
Article
Conference Proceedings

Analyzing Diabetes-Related Hospitalizations: Trends and Insights from NIS 2016–2019 for Health Informatics Applications

Potentially preventable hospitalizations are a major area of concern as they represent a huge financial burden across the healthcare ecosystem. To alleviate this issue, this research investigates characteristics, risk factors, and outcomes related to hospital inpatient stays in the context of diabetic patients. Diabetes is a major public health issue that is approaching epidemic proportions globally. Compared to the early 2000s, the prevalence of diabetes in individuals within the age group of 20 - 79 years has increased by 53.3% in the US. In addition to clinical factors, prior studies emphasized the role of socio-economic factors, health conditions, demographics, and quality of care in influencing hospitalization rates. In this retrospective cohort study, Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) dataset (2016-2019) was analyzed. This study identified trends in length of stay (LOS) by highlighting disparities related to demographics, income and payer type with an overall goal to guide administrators and policy makers involved in the design and development of systems and health policy services to implement new action plans and quality initiatives.From 2016 to 2019, it was observed that diabetes-related hospitalizations increased by 6.8%. Females accounted for 51–52% of cases, and most patients were between 18–68 years. White patients comprised the largest proportion (52–53%), while individuals in the lowest income quartile accounted for 38.9–40.8% of diabetes-related hospitalizations. The mean LOS for diabetes-related stays increased slightly from 3.17 to 3.25 days over the four years, with older adults and males experiencing longer stays. Most patients were treated in private, non-profit hospitals, with urban teaching hospitals accounting for most admissions. A multivariate linear regression model was used to analyze the impact of variables such as age, gender, payer type, income, hospital characteristics, and severity of illness on LOS. The results indicate that among diabetic patients, risk factors such as age, demographics, income, and insurance policies associated with in-patient stays are critical and warrant further investigation. Findings of this study suggest that awareness, timely screening, and lifestyle changes from a young age can reduce diabetes-related complications and eventually lower preventable hospitalizations, thus improving the effectiveness of healthcare delivery.

Ruchi Kukde, Jaymeen Shah, Aindrila Chakraborty
Open Access
Article
Conference Proceedings

Smart Glasses and Augmented Reality to Support Healthcare

Augmented Reality (AR) holds considerable promise in transforming clinical practice by enabling hands-free, real-time access to critical information. This paper examines the current state, challenges, and prospects of integrating AR smart glasses in healthcare environments through a human-centred design framework. Despite technological advances and promising pilot studies, the widespread clinical adoption of AR remains limited due to issues in comfort, spatial accuracy, usability, and insufficient clinical validation. Smart glasses and head-mounted displays (HMDs) such as Microsoft HoloLens have demonstrated their utility in surgical settings, medical training, and remote collaboration. These systems enhance situational awareness and procedural efficiency by overlaying digital information within the clinician’s field of view. However, significant barriers such as ergonomic discomfort, inadequate integration with electronic health records (EHR), cognitive overload, and limited interoperability with hospital systems hinder broader acceptance. The EU-funded POPULAR project addresses these limitations by proposing a human-centred AR Eyewear (ARE) platform tailored for clinical settings. This platform emphasises ergonomic design, ophthalmic customisation, and context-sensitive data presentation, aligning with healthcare workflows and professional needs. A user-centric methodology underpins the development process, involving qualitative and quantitative research with healthcare professionals and educators. Through interviews, focus groups, and usability benchmarking, “training in medical procedures” emerged as the primary application area. Additional functionalities such as vital sign projection, procedural alerts, and medical history access were also prioritised. Early-stage prototypes with side-mounted and top-mounted projection systems underwent testing at the Medical University of Lodz (MUL). Field trials under simulated emergency scenarios revealed user preferences for side-mounted configurations due to superior comfort and visibility. Continuous participant feedback informed iterative design refinements, improving usability and acceptance. The study found that visual clarity, optimal fit, and seamless information integration into clinical tasks are critical to long-term adoption. Despite these advances, challenges remain. Data security and patient privacy concerns are paramount, especially when AR systems incorporate real-time audio-visual capture and EHR access. Additional barriers include device weight, thermal discomfort, and steep learning curves. The successful deployment of smart glasses in healthcare requires addressing these multifaceted issues through robust encryption, ergonomic engineering, intuitive interfaces, and structured user training. Looking ahead, further clinical validation and large-scale deployment are necessary to confirm the effectiveness and safety of AR smart glasses in real-world healthcare scenarios. By embedding user feedback throughout the development cycle, smart glasses can evolve into reliable tools that enhance care quality, clinical efficiency, and professional satisfaction across diverse medical contexts.

Adrian Morales Casas, Clara Solves Camallonga, José Manuel Rojas, Vanessa Jimenez, Fabien Divo, Aneta Andrzejczyk
Open Access
Article
Conference Proceedings