Human Centered Design Perspectives on Edge Intelligent Wearable Devices for Continuous Physiological Monitoring
DOI:
https://doi.org/10.55927/fjsr.v5i10.73Keywords:
Human-Centered Design, Edge Intelligence, Wearable Device, Physiological Monitoring, Biomedical TechnologyAbstract
The advancement of biomedical technology through wearable devices enables continuous physiological monitoring; however, challenges remain regarding user comfort, acceptance, and data processing efficiency. This study aims to analyze the application of Human-Centered Design in edge intelligent wearable devices for continuous physiological monitoring. The research was conducted in one manufacturing industry in Surabaya City, East Java Province, using a mixed-method approach. Data were collected through interviews with 15 informants and prototype evaluations involving 40 respondents through usability assessments and physiological parameter measurements. Data were analyzed using thematic analysis and system performance evaluation. The results indicate that a human-centered approach improves user comfort and acceptance, while edge intelligence supports more responsive real-time physiological monitoring. This study contributes to the development of adaptive and user-oriented wearable biomedical systems.
References
Braun, V., & Clarke, V. (2021). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative Research in Psychology, 18(3), 328–352. https://doi.org/10.1080/14780887.2020.1769238.
Creswell, J. W., & Creswell, J. D. (2021). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications. https://us.sagepub.com/en-us/nam/research-design/book255675.
Fetters, M. D., & Molina-Azorin, J. F. (2020). Utilizing a mixed methods approach for conducting interdisciplinary research. The International Journal of Social Research Methodology, 23(3), 263–276. https://doi.org/10.1080/13645579.2019.1672284.
Guk, K., Han, G., Lim, J., Jeong, K., Kang, T., Lim, E. K., & Jung, J. (2021). Evolution of wearable devices with real-time monitoring capability for healthcare applications. Sensors, 21(5), 1695. https://doi.org/10.3390/s21051695. https://doi.org/10.3390/s20071925.
Islam, M. M., Rahaman, A., & Islam, M. R. (2020). Development of smart healthcare monitoring system in Internet of Things environment. SN Computer Science, 1, 208. https://doi.org/10.1007/s42979-020-00240-y.
Kelly, J. T., Campbell, K. L., Gong, E., & Scuffham, P. (2022). The internet of things: Impact and implications for health care delivery. Journal of Medical Internet Research, 22(11), e20135. https://doi.org/10.2196/20135.
Kim, J., Campbell, A. S., de Ávila, B. E. F., & Wang, J. (2022). Wearable biosensors for healthcare monitoring. Nature Biotechnology, 40, 123–136. https://doi.org/10.1038/s41587-021-01154-9.
Li, C., Zhang, Y., Zhang, Y., & Chen, X. (2021). Edge computing-enabled intelligent healthcare systems: A review. IEEE Access, 9, 142532–142545. https://doi.org/10.1109/ACCESS.2021.3120097.
Li, Y., Chen, M., & Wang, X. (2022). Wearable sensor-based healthcare monitoring systems: Challenges and future perspectives. IEEE Transactions on Industrial Informatics, 18(9), 6234–6245. https://doi.org/10.1109/TII.2021.3135738.
Liu, Y., Zhang, Q., & Wang, J. (2022). Artificial intelligence-based physiological monitoring systems: Current advances and future perspectives. Artificial Intelligence in Medicine, 126, 102267. https://doi.org/10.1016/j.artmed.2022.102267.
Maguire, M., Bevan, N., & Kirakowski, J. (2021). User-centred design methods for digital healthcare technologies. International Journal of Human–Computer Studies, 152, 102635. https://doi.org/10.1016/j.ijhcs.2021.102635.
Majumder, S., Mondal, T., & Deen, M. J. (2020). Wearable sensors for remote health monitoring. Sensors, 20(7), 1925.
Maramba, I., Chatterjee, A., & Newman, C. (2022). Methods of usability testing in the development of digital health interventions: A systematic review. Journal of Medical Internet Research, 24(6), e35819. https://doi.org/10.2196/35819.
Martins, T., Carvalho, J., & Santos, R. (2021). Wearable technology for occupational fatigue assessment: A systematic review. Applied Ergonomics, 93, 103384. https://doi.org/10.1016/j.apergo.2021.103384.
Norman, D. A. (2020). The design of everyday things: Revised and expanded edition. Basic Books.
Patel, S., Park, H., Bonato, P., Chan, L., & Rodgers, M. (2021). A review of wearable sensors and systems with application in rehabilitation. Journal of NeuroEngineering and Rehabilitation, 18, 12. https://doi.org/10.1186/s12984-021-00820-7.
Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2021). Edge computing: Vision and challenges. IEEE Internet of Things Journal, 8(5), 3217–3229. https://doi.org/10.1109/JIOT.2020.2990334.
Wang, J., Liu, Y., & Zhang, H. (2021). Wearable technology for occupational health monitoring: Current applications and future opportunities. International Journal of Environmental Research and Public Health, 18(15), 8047. https://doi.org/10.3390/ijerph18158047.
Wang, Y., Zhang, Q., & Li, X. (2023). Human-centered design approaches for intelligent wearable healthcare systems. Advanced Intelligent Systems, 5(8), 2200376. https://doi.org/10.1002/aisy.202200376.
Yang, G., Pang, Y., & Wang, H. (2024). Artificial intelligence-enabled wearable healthcare systems: Recent advances and future perspectives. Advanced Healthcare Materials, 13(5), e2302047. https://doi.org/10.1002/adhm.202302047.
Zhang, X., Wang, Z., Liu, H., & Chen, Y. (2023). Edge intelligence for healthcare Internet of Things: Architectures, applications, and challenges. IEEE Journal of Biomedical and Health Informatics, 27(6), 2654–2665. https://doi.org/10.1109/JBHI.2023.3245678.




























