User Experience with AI-Enabled Wearable Medical Technology for Self-Care
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Abstract
Wearable medical devices equipped with artificial intelligence (AI) have emerged as transformative tools in managing chronic conditions, offering real-time health monitoring and enhancing patient autonomy. While technological advancements have improved device functionality, the subjective experiences of users, particularly their adaptation, trust, and emotional engagement with these technologies, remain underexplored. This study addresses this gap by investigating the lived experiences of individuals using AI-enabled wearable medical devices, focusing on how these technologies are perceived, adopted, and integrated into daily life. Using a phenomenological approach, we identified three key themes: initial adaptation challenges, concerns about trust and data accuracy, and psychological reassurance from self-monitoring. Data were collected through semi-structured interviews with 15 participants, analyzed thematically to uncover the deeper meanings behind their experiences. Findings highlight the importance of user-centered design and the need for clearer communication from manufacturers to build trust and support long-term device engagement. These insights contribute to a more nuanced understanding of the interplay between technology and user experience, with implications for improving the design and implementation of wearable medical devices. Future research should explore diverse populations and longitudinal impacts to further enhance the adoption and effectiveness of health technologies.
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Aldhaibani, J. A., Mohammed, M. Q., Mahmood, A. A., & Hamza, M. S. (2024). Development of wearable textile patch antenna 2.43 GHz for biomedical applications. International Journal of Advanced Technology and Engineering Exploration, 11(111), 177–189. Scopus. https://doi.org/10.19101/IJATEE.2023.10102312
Cai, H., & Cai, M. (2024). Cardiac function monitoring during marathon training based on smart medical wearable sensor device. MCB Molecular and Cellular Biomechanics, 21(4). Scopus. https://doi.org/10.62617/mcb627
Chen, L., Chen, Y., Liang, W., Li, X., Li, K.-C., Wang, J., & Xiong, N. (2024). MASS: A Multi-Attribute Sketch Secure Data Sharing Scheme for IoT Wearable Medical Devices Based on Blockchain. IEEE Internet of Things Journal. Scopus. https://doi.org/10.1109/JIOT.2024.3468733
Hirczy, S., Zabetian, C., & Lin, Y.-H. (2024). The current state of wearable device use in Parkinson’s disease: A survey of individuals with Parkinson’s. Frontiers in Digital Health, 6. Scopus. https://doi.org/10.3389/fdgth.2024.1472691
John, B., & Rai, N. R. (2024). Customer Awareness of Medical Wearable Health Care Technology and Policy Management in India. South Eastern European Journal of Public Health, 23(3), 268–274. Scopus. https://doi.org/10.70135/seejph.vi.847
Karim, M. Z. A., Thamrin, N. M., Shauri, R. L. A., Jailani, R., Manaf, M. H. A., & Mustapa, N. A. (2024). Tele-DM: development of a mobile health technology for non-invasive type-2 diabetes mellitus patients with assistive physical activities and vital signs monitoring. International Journal of Advanced Technology and Engineering Exploration, 11(112), 288–315. Scopus. https://doi.org/10.19101/IJATEE.2023.10102368
Karunya, N. W. S., Jose, P. S. H., & Karunya, J. R. (2021a). Review on reliable and quality wearable healthcare device (WHD). International Journal of Grid and High Performance Computing, 13(4), 1–23. Scopus. https://doi.org/10.4018/IJRQEH.2021100101
Karunya, N. W. S., Jose, P. S. H., & Karunya, J. R. (2021b). Review on reliable and quality wearable healthcare device (WHD). International Journal of Information Systems and Supply Chain Management, 14(4), 1–19. Scopus. https://doi.org/10.4018/IJRQEH.2021100101
Nanda, S., & Gautam, T. (2020). Internet of things-based wearable health solutions: Empirical study for health startups. World Review of Entrepreneurship, Management and Sustainable Development, 16(6), 605–610. Scopus. https://doi.org/10.1504/WREMSD.2020.111389
Patan, R., Pradeep Ghantasala, G. S., Sekaran, R., Gupta, D., & Ramachandran, M. (2020). Smart healthcare and quality of service in IoT using grey filter convolutional based cyber physical system. Sustainable Cities and Society, 59. Scopus. https://doi.org/10.1016/j.scs.2020.102141
Sneha, S., Panjwani, A., Lade, B., Randolph, J., & Vickery, M. (2021). Alleviating Challenges Related to FDA-Approved Medical Wearables Using Blockchain Technology. IT Professional, 23(4), 21–27. Scopus. https://doi.org/10.1109/MITP.2021.3072535
Stevens, G., Larmuseau, M., Damme, A. V., Vanoverschelde, H., Heerman, J., & Verdonck, P. (2024). Feasibility study of the use of a wearable vital sign patch in an intensive care unit setting. Journal of Clinical Monitoring and Computing. Scopus. https://doi.org/10.1007/s10877-024-01207-5
Tannirkulam Chandrasekaran, S., Prashant Bhanushali, S., Banerjee, I., & Sanyal, A. (2021). Toward Real-Time, At-Home Patient Health Monitoring Using Reservoir Computing CMOS IC. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 11(4), 829–839. Scopus. https://doi.org/10.1109/JETCAS.2021.3128587
Xinyan, Z., Mamun, A. A., Ali, M. H., Siyu, L., Yang, Q., & Hayat, N. (2022). Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach. Frontiers in Public Health, 10. Scopus. https://doi.org/10.3389/fpubh.2022.1016065
Zhao, M., Wang, D., & Li, J. (2021). Data management and visualization of wearable medical devices assisted by artificial intelligence. Network Modeling Analysis in Health Informatics and Bioinformatics, 10(1). Scopus. https://doi.org/10.1007/s13721-021-00328-0