AHFE Open AccessHealth Informatics and Biomedical Engineering Applications
Editors: Adrian Morales, José Laparra, Jay Kalra
Topics: Healthcare and Medical Devices
Publication Date: 2024
ISBN: 978-1-964867-18-2
DOI: 10.54941/ahfe1005064
Articles
From Concept to Context: Evaluating Medical Device Usability Where It Matters Most
The usability validation process of medical devices outside controlled environments such as test facilities, laboratories, or by expert groups is vital to scrutinising the viability of the developed solution. This work outlines a case study in which the Spanish emergency service 061-Andalucia took part in the validation process of a non-contact vital sign measuring device through image processing, describing the methodology, participant sample, data analysis and conclusions. The measured vital signs were heart rate, respiratory rate, oxygen saturation, temperature, and blood pressure contactless at 2 meters (6.5 ft). In the study, three emergency service teams from three different operation bases in Malaga (Spain) underwent the validation process under semi-real conditions. Each team was provided with one measurement device used during the work shift on patients who were not in a critical stage, conscious and willing to participate in the study after being informed and signing a consent form. The primary goals of the validation were to analyse the ease of the process, reliability, and robustness of the measurements against the standard measurement equipment of the emergency service in different scenarios, as well as detect errors and limitations under semi-real conditions of use. Besides providing evidence of a potential improvement in the service through this new camera system, the satisfaction of the users/ patient and reducing equipment weight. Under these harsh conditions, the measurement device with a technical readiness level 7 reached reliability and robustness between 70% and 100%, depending on the measured vital signs and a high acceptance among the professionals of 66,66%.
Adrian Morales Casas, Amparo López Vicente, Lorenzo Solano-garcía, Jose Laparra
Open Access
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Conference Proceedings
Connected Care Home platforms: Promoting self-management by empowering patients
Remote patient monitoring systems are increasingly gaining attention among researchers and healthcare providers who have also started adopting innovative solutions. It is easy to understand why remote monitoring platforms would enhance treatment efficiency and access to healthcare solutions for patients who face difficulties travelling to hospitals, especially older persons and chronic patients who require frequent monitoring of their vital signs and other health indicators, rehabilitation or other social and healthcare support. Therefore, these platforms are, in turn, sources of information for patients about their disease. The fact that they have access to information gives them more knowledge and makes them more in touch with and responsible for it. It empowers them. Besides, from a clinician's point of view, these platforms are a storage system for providing valuable and varied patient information, thus allowing them to have a holistic view of their patients and empowering them. In short, access to and availability of information empowers the patient-clinical staff team.Once these data have been collected, a thorough analysis and interpretation is necessary. This interpretation requires the interdisciplinary collaboration of the technical-clinical and scientific community to develop relevant and exciting functionalities for the improvement of health.This study presents a collection of case studies that collect some insight into the design based on human factors and user experience applied to three monitoring technologies and artificial intelligence algorithms to improve the prevention and management of different conditions.The usability and acceptance measures are generally well received and successful and are particularly effective when conducted during the preparation of the experiment. In other words, if the experiment includes the end-user (patient and clinical staff) as part of the design.
Beatriz Muñoz García, Adrian Morales Casas, Jose Laparra, David Garrido, Arturo Gomez Pellin
Open Access
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Conference Proceedings
Citizen Science Applied Health Care: Active involvement of clinicians and patients in co-creating health products, services and environments
Citizen science, involving the public in scientific processes alongside researchers, offers promise for health research and collaborative health management. This participatory approach engages laypersons in knowledge production, yielding insights unattainable through traditional methods. This article highlights citizen science's practical contributions to healthcare, advocating for its role in reshaping the healthcare model. Drawing from four recent projects, it emphasises the importance of professional and patient involvement in solution development. These experiences underscore the need for rigorous criteria identification and early-stage involvement to ensure project success.Recommendations to advance citizen science in health management include extending value-based health principles to product development, diversifying participant profiles, integrating citizen scientists into early research phases, leveraging technology for data collection, and ensuring methodological rigour. These suggestions aim to enhance the effectiveness of citizen science in addressing health challenges and fostering collaborative innovation in healthcare.The future of social and healthcare services must actively include citizens and professionals throughout the process to humanise these services, enhancing health products, services and environments.
Amparo López-vicente, Adrian Morales Casas, Carlos Atienza, Raquel Marzo Roselló, Jose Laparra
Open Access
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Conference Proceedings
Augmented Reality Eyewear with ophthalmic correction for mainstream applications, overcoming acceptance barriers through Human Factors Plan
Although more than 80% of human interactions with the world transit through our eyes and most daily activities require hands-on interaction, none of the current AR technologies and designs, mainly from the USA and Asia, has unlocked the essential combination of human-centred needs, technical requirements and market and society acceptance. Massive adoption, especially for extensive population usage, faces significant bottlenecks: insufficient optical quality, low visual, vestibular, cognitive and social comfort, and missing integrated ophthalmic correction or device aesthetics; the only way to enhance AR visual experience.EU POPULAR project is developing the first generic Augmented Reality Eyewear (ARE) platform covering the broadest range of users and use cases in a professional context, leisure or daily life, including personal ophthalmic correction. The ordinary-looking glasses will be comfortable, accessible and aesthetically appealing, making them suitable for all-day use. Moreover, privacy and security issues will be covered to ensure user, stakeholders, and society acceptance. The differential factors will be its compactness and invisible technology, optical quality, ultra-low power consumption and long operation times, integrating cost-efficiency aspects.To achieve this challenging aim, IBV has defined a Human Factors (HF) Plan covering visual comfort, vestibular comfort, mental fatigue, ease of use, freedom of movement, emotional reaction, risk of exclusion and societal acceptance. The HF Plan was defined in 3 sprints: 1) gather needs, risks analysis and conceptual design, 2) design, develop and iterative tests `process, from scratch and dummy prototypes to 4 functional prototypes (combining white/back or colour AR and without/with ophthalmic correction, 3) Final Validation in actual conditions along representative use cases. The HF Plan will be supported by a Social Science and Humanities Advisory Board and aligned with MDR protocols and processes.ARE acceptance and global scalability will be demonstrated in 3 realistic use case scenarios, outdoor sports, healthcare and logistics, as the first step to massive market deployment. The validation in real situations will include innovative methodologies to real-time asses of mental status to balance the loss of attention/distraction and cognitive overload, using eye tracking patterns and physiological response analysis.
Jose Laparra Hernández, Adrian Morales Casas, Mathieu Feuilliade, Xavier Bonjour, Armel Jimenez, Vanessa Jimenez, Luis Sánchez Palop, José Francisco Serrano Ortiz, José Manuel Rojas, Andrés Soler
Open Access
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Conference Proceedings
Humanizing X-Ray Services for Children with Cerebral Palsy: A Holistic Approach to Functionality, Usability and Aesthetics
The adequate acquisition of X-ray images is crucial for effectively monitoring and treating patients with significant spinal deformities, particularly those with mobility limitations, mainly children. Patients with these considerations include individuals with cerebral palsy, who face additional challenges in doctor-patient interactions due to speech and cognitive restrictions. Moreover, patients with spasticity resulting from paralysis may exhibit uncontrollable limb movements.In the absence of suitable devices forcing patients to maintain a stable seated position during imaging, they often adopt inadequate postures, risking misdiagnosis and unnecessary radiation exposure if exam repetition is needed. To address this issue, an X-ray Sitting Support device has been designed to accommodate patients with these pathologies and ensure high-quality radiographic images while prioritizing patient safety and comfort.The development of the X-Ray Sitting Support device was based on a Human Factors plan and User Experience methodologies, with an iterative process focusing on physical ergonomics, usability, and patient acceptance. Feedback from patients, medical personnel, and caregivers was integrated throughout the design process, from defining requirements to real-world prototype validation. This comprehensive approach ensured that the imaging sitting support met the needs of both patients and medical professionals, enhancing the effectiveness and safety of radiological examinations for individuals unable to stand.
José Antonio Diez - De Pablos, Luis Martí Bonmati, Nicolás Palomares, Ignacio Espíritu García-molina, Fernando Mollá-doménech, Carlos Atienza, Orlando Carles Diaz, Adrian Morales Casas, Jose Laparra
Open Access
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Conference Proceedings
A Longitudinal Study on Hearing Loss in South Korean Air Force Pilots: Evidence from Electronic Medical Records
Hearing loss is known to be one of the most common diseases that can occur among Air Force pilots. Since treatment for hearing loss varies greatly depending on the cause, an accurate diagnosis of the cause is important. However, few studies have comprehensively analysed the causes of hearing loss in Air Force pilots. Therefore, the purpose of this study is to contribute to the prevention of hearing loss by identifying the vulnerability of hearing loss in Air Force pilots in the long term through the analysis of Electronic Medical Records (EMRs). This study analysed the EMRs of Air Force pilots from 2012 to 2023 in South Korea. The EMRs included pilot demographic information as well as the results for each indicator of the general check, blood test, urine test, and Pure Ton Audiometry (PTA) test. Results of data analysis show that pilots who were older, had propeller aircraft types, and had a total flight time of 2,001 to 3,000 hours had a high rate of hearing loss. In addition, pilots with hearing loss were found to have both systolic and diastolic blood pressures outside the normal range. In particular, diastolic blood pressure and glucose levels showed a significant positive correlation with both left and right hearing test results in the high frequency range. In terms of PTA tests, pilots with hearing loss mainly exceeded the criteria in the left ear and high frequency range, and the C5-dip and asymmetry phenomenon were partially identified. The results of this study show the possibility of predicting hearing loss disease for Air Force pilots or suggesting medical treatment guidelines through the analysis of EMRs.
Sungho Kim, Kyehyun Kim, Kgyungwon Kim, Juhyeong Yang, Hong-kyung Lee, Jungwoon Kim, Geonhui Kim, Seunghoon Yoo, Younggun Lee, Dongsoo Kim
Open Access
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Conference Proceedings
Enhancing Canine Musculoskeletal Diagnoses: Leveraging Synthetic Image Data for Pre-Training AI-Models on Visual Documentations
The examination of the musculoskeletal system in dogs is a challenging task in veterinary practice. The careful diagnosis as well as the evaluation of very complex findings is getting increasingly important. Therefore, a novel method has been developed that enables efficient documentation of a dog's condition through a visual representation. However, since the visual documentation is new, there is no existing training data. The objective of this work is therefore to mitigate the impact of data scarcity in order to develop an AI-based diagnostic support system that can provide veterinarians with accurate predictions. To this end, the potential of synthetic data that mimics realistic visual documentations of diseases for pre-training AI models is investigated. Specifically, this work explores whether pre-training an AI model with synthetic data can improve the overall accuracy of canine musculoskeletal diagnoses.We propose a method for generating synthetic image data that mimics realistic visual documentations. Initially, a basic dataset containing three distinct classes is generated, followed by the creation of a more sophisticated dataset containing 36 different classes. Both datasets are used for the pre-training of an AI model, adapting it to the domain of visual documentations. Subsequently, an evaluation dataset is created, consisting of 250 manually created visual documentations for five different diseases. This dataset, along with a subset containing 25 examples, serves as the basis for evaluating the efficacy of pre-training an AI model on synthetic data.The obtained results on the evaluation dataset containing 25 examples demonstrate a significant enhancement of approximately 10% in diagnosis accuracy when utilizing generated synthetic images that mimic real-world visual documentations. However, these results do not hold true for the larger evaluation dataset containing 250 examples, indicating that the advantages of using synthetic data for pre-training an AI model emerge primarily when dealing with few examples of visual documentations for a given disease. This implies that the use of synthetic data may not be necessary for diseases with many visual documentation examples.Overall, this work provides valuable insights into mitigating the limitations imposed by limited training data through the strategic use of generated synthetic data, presenting an approach applicable beyond the canine musculoskeletal assessment domain.
Martin Thissen, Thi Ngoc Diep Tran, Ben Joel Schönbein, Ute Trapp, Barbara Esteve Ratsch, Beate Egner, Romana Piat, Elke Hergenröther
Open Access
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Conference Proceedings
Optimizing high accuracy 8K LCD 3D-printed Hollow Microneedles: Methodology and ISO-7864:2016 Guided Evaluation for Enhanced Skin Penetration
Microneedle research has surged due to its potential for user-friendly and painless drug delivery. Their ability to pierce the skin and adaptability to skin surfaces underscore their relevance to ergonomic drug delivery systems. Therefore rapid, precise and affordable prototyping is crucial for the advancement of this research field. Among fabrication techniques, 3D printing remains the most agile, particularly with the recent technological progress in high precision 8K LCD printers, providing superior geometric quality. This study focuses on optimizing hollow microneedle designs and conducting ISO 7864:2016 (Sterile hypodermic needles for single-use requirements and test methods)-guided testing to enable objective comparisons among structures. Specifically, relevant features, including hollow needle geometries, tip angles, wall thicknesses and print settings of microneedles, are investigated using a high-resolution liquid crystal display (LCD) printing platform. In the absence of specific ISO standards for transdermal microneedles, this research aims to establish guidelines modelled after ISO-7864:2016 for hypodermic needles. A detailed exploration of a low-cost, accessible test setup design is presented. This contributes to the establishment of benchmarks for microneedle design and evaluation practices through ISO-guided testing methodologies. Beyond scientific contributions, these efforts aim to ensure safer and more effective microneedle applications in healthcare.
Andres Vanhooydonck, Jochen Vleugels, Marc Parrilla, Phil Clerx, Regan Watts
Open Access
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Conference Proceedings
Enhancing Ultrasound Imaging through Convolutional Neural Networks: A Health Informatics Approach
Ultrasound imaging, a linchpin in diagnostic medicine, delivers invaluable non-invasive insights into anatomical structures and physiological processes. Despite its widespread application, challenges persist in interpreting ultrasound images due to inherent noise, artifacts, and variations in acquisition conditions. Traditional ultrasound imaging, while invaluable, faces limitations such as lower spatial resolution, susceptibility to noise interference, and challenges in distinguishing subtle abnormalities. The research introduces an innovative approach in health informatics, harnessing the transformative potential of Convolutional Neural Networks (CNNs) to profoundly elevate the clarity and diagnostic utility of ultrasound imaging. The principal objective of this study is to systematically address existing challenges in traditional ultrasound imaging by leveraging deep learning, specifically CNNs. Our approach deploys advanced image processing techniques to significantly enhance the accuracy, resolution, and overall interpretability of ultrasound scans. To achieve this, we propose the implementation of a robust CNN architecture meticulously trained on a diverse dataset of ultrasound images. This architectural design not only enables the CNN to learn intricate patterns and features inherent in ultrasound images but also facilitates intelligent denoising, artifact reduction, and enhancement of anatomical structure visualization. Transfer learning techniques are strategically explored to optimize model performance across different imaging modalities and patient demographics, ensuring versatility and widespread applicability. Moreover, this adaptability has the potential to alleviate the computational burden associated with training large AI models. The initial focus is on denoising, where the CNN is trained to intelligently filter out noise, resulting in clearer and diagnostically valuable ultrasound images. Simultaneously, the model is trained to identify and mitigate common artifacts, such as shadowing and reverberation, significantly enhancing image fidelity. The CNN's capacity for learning hierarchical representations is harnessed to improve the spatial resolution of ultrasound scans. This enhancement proves crucial in aiding the detection of subtle abnormalities, thereby elevating diagnostic accuracy to new heights. Furthermore, the proposed CNN architecture is meticulously designed for adaptability across various ultrasound machines, ensuring seamless integration into diverse clinical settings. This adaptability reinforces its potential to become a standard tool in routine clinical practices. This research envisions the development of an advanced ultrasound imaging tool that seamlessly integrates into existing clinical workflows. The CNN-enhanced ultrasound images are poised to empower healthcare professionals with clearer, more informative visuals, ultimately leading to improved diagnostic accuracy and enhanced patient outcomes. The integration of CNNs into ultrasound imaging represents a significant leap forward in health informatics and biomedical engineering. This approach has the transformative potential to revolutionize routine clinical practices, making ultrasound diagnostics more accessible, reliable, and conducive to enhanced patient care. The intersection of deep learning and ultrasound imaging presents a paradigm shift, laying the groundwork for a new era in medical diagnostics. In the pursuit of advancing healthcare technology, this study heralds a future where the synergy of artificial intelligence and ultrasound imaging sets unprecedented standards in diagnostic precision and patient care.
Fan Yang, Qian Mao, Menghan Shi, Fangling Xie, Ka Wei Eric Cheng
Open Access
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Conference Proceedings
Colors in Mind: A Comprehensive Study on the Neurological Impact of Saturation
The perception of color is a crucial cognitive aspect that profoundly impacts cognition, emotions, and behaviour. Cool colors evoke comfort and relaxation, while warm colors stimulate and energize. This study explores how color saturation impacts brainwave patterns, using EEG signals and the MUSE BCI. Twenty-five participants, including 5 colorblind individuals, aged 18-60, viewed 10 colors on a computer screen at varying saturations. Analysis reveals distinct color effects on attention and diverse responses. Notably, saturated blue captures attention, while yellow and violet elicit a less pronounced response. Energy frequency band analysis shows varied stimulation levels across brain waves. The ERD/ERS complex indicates positive aspects, suggesting desynchronization during color observation and heightened neuronal excitement. The study underscores color's substantial role, offering insights into psychology. Frontal EEG measurements elucidate the influence of color saturation on physiological and perceptual responses.
Ana Teixeira, Sonia Brito-costa, Anabela Gomes
Open Access
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NurseAid Monitor: A Non-Invasive Monitor to Assess Respiratory Rate and Pattern of Bedridden Patients
The clinical management of bedridden patients necessitates meticulous attention to their respiratory health, as their constrained mobility significantly increases the risk of respiratory complications. Considering the critical link between respiratory function and recovery outcomes, this research underscores the importance of monitoring respiratory frequency and patterns as an essential aspect of care for these individuals. Diligent observation of respiratory parameters enables healthcare providers to identify early signs of deterioration in respiratory health, allowing for timely intervention and, consequently, a reduction in the incidence of serious complications. We propose a platform based on non-invasive contactless Infrared thermography that analyzes respiratory frequency and patterns. With the help of volunteers, we conducted an experiment to collect data for statistical treatment and modeling. Our results, discussed in this work, substantiate the data collection approach and the selected methodology.
Rafael De Pinho Andre, Almir Fonseca, Lucas Westfal
Open Access
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Conference Proceedings
Comparing Perceptions of Human Factors - Priorities of Cardiologists and Biomedical Engineers in the Design of Cardiovascular Devices
This study aimed to understand perceptions of Human Factors (HF) within the Product Development Process (PDP) of catheter-based cardiovascular therapies. Attitudes of biomedical engineers were compared to those of the clinicians who use these devices. The main objectives were to:1.Determine how Engineers and Cardiologists perceive HF impact on user experience.2.Gain an understanding of how various design factors affect the user experience. 3.Identify Engineers’ familiarity with HF resources and understand what HF data they seek during the PDP.By identifying and later filling data gaps and barriers to optimise design, these findings can improve how HF is implemented during the PDP, leading to improved user experience and better patient outcomes.MethodsData were gathered from 57 Biomedical R&D Engineers and 20 Interventional Cardiologists via questionnaires and semi-structured interviews. An online form was distributed at an internal medical device company Global Catheter Summit during November 2023 targeting engineers with experience developing catheter-based devices. Data from Cardiologists were gathered across two in person events between February and April 2024. Parameters to gauge specialty and experience were gathered from both cohorts (Engineers & Interventional Cardiologists). Quantitative data were gathered in Excel and statistically analysed using SPSS. Qualitative data was thematically analysed using NVivo. DiscussionThe results highlighted that the Engineers’ priorities in the PDP differ from the prioritised needs of the Cardiologists, but both groups identified grasps/manipulations as important factors influencing user experience. Engineers focused on the factors specific to the device itself – they believe the device is what the user cares most about, however, the Cardiologists ranked the impact of having multiple operators and what surgical access site is being used highly, pointing to the importance of considering use scenario and environment. 75% of Engineers strongly agreed with the statement “I feel user centred design is important when developing a new product”, indicating that project teams place value on HF activities but there are several challenges in implementing these. Engineers often struggle to find the data and expertise they need to implement HF activities in a meaningful and impactful way, without compromising on timeline, budget, and other product development activities. Of those who identified themselves as R&D or Design Engineers 69% (N=33) struggled to find the data they wanted. User specific and context specific data, torque strength and dynamic force data were highlighted as key gaps in user data. Differences in priorities further underlines the need for user centred design, and implementation of an iterative design approach which engages the end user from design conception, to design implementation, and beyond.ConclusionOverall, both Engineers and Cardiologists respect the impact of HF on the optimisation of user interaction. They agreed on the need for further innovation to improve user experience for CBCD. Priorities of Biomedical Engineers during the design process differed from the prioritised needs of Cardiologists when using devices, however both cohorts felt manipulations required to operate devices is an important factor to consider during design. The Engineers reported a paucity of specific user related data regarding handle interaction in this field. There is a need for easily accessible literature reporting upon user force data for dynamic motion (i.e. torque, push and pull); force data for female users, and general human body measurements that are applicable to device design. This data can serve as an indicator of where academia and industry should focus their research efforts to improve the implementation of HF, and ultimately optimise the user experience.
Grainne Tyrrell, Donna Curley, Leonard O' Sullivan, Eoin White
Open Access
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