AI-Powered Wearables Revolutionizing Health Tracking and Personalized Wellness Management
Keywords:
AI-powered wearables, Empirical validation, Health tracking, Personalized monitoring, Management.
Abstract
Integrating artificial intelligence (AI) into wearable technology has revolutionized health tracking, offering users personalized insights into their well-being. However, gaps exist in empirical validation, personalized monitoring, and ethical considerations. Purpose: This study aims to explore the transformative role of AI-powered wearables in health tracking, addressing existing gaps in the literature and offering novel insights into their potential. Methodology: A literature study was employed to analyze peer-reviewed articles published from 2018 onwards. Empirical validation studies and user-centric research were scrutinized to extract insights into AI algorithms' accuracy, reliability, and personalized capabilities in wearables. Result/Conclusion: The analysis reveals that while AI-powered wearables hold promise, empirical validation is crucial to ensuring their effectiveness. Personalized monitoring strategies are essential for empowering users to make informed decisions about their health. Addressing ethical concerns surrounding data privacy is paramount for fostering user trust. Overall, AI-powered wearables significantly advance health-tracking technology, offering users a holistic and personalized approach to managing their well-being
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References
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Bent, Brinnae, et al. “Investigating Sources of Inaccuracy in Wearable Optical Heart Rate Sensors.” Npj Digital Medicine, vol. 3, no. 1, 10 Feb. 2020, https://doi. org/10.1038/s41746-020-0226-6.
Chinoy, Evan D, et al. “Performance of Seven Consumer Sleep-Tracking Devices Compared with Polysomnography.” Sleep, vol. 44, no. 5, 30 Dec. 2020, https://doi.org/10.1093/sleep/zsaa291.
Clark, Marianne I., and Matthew W. Driller. “University Student’s Perceptions of Self-Tracking Devices, Data Privacy, and Sharing Digital Data for Research Purposes.” Journal for the Measurement of Physical Behaviour, 2020, pp. 1–7, https://doi.or g/10.1123/jmpb.2019-0034. Accessed 4 May 2020.
Dimitratos, Sarah M, et al. “Wearable Technology to Quantify the Nutritional Intake of Adults: Validation Study.” JMIR MHealth and UHealth, vol. 8, no. 7, 22 July 2020, p. e16405, https://doi. org/10.2196/16405 Accessed 14 Apr. 2022.
Dwivedi, Yogesh K., et al. “Artificial Intelligence (AI): Multidisciplinary Perspectives on Emerging Challenges, Opportunities, and Agenda for Research, Practice and Policy.” International Journal of Information Management, vol. 57, no. 101994, Aug. 2021.
Fine, Jesse, et al. “Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring.” Biosensors, vol. 11, no. 4, 16 Apr. 2021, p. 126, https://doi.org/10.3390 /bios11040126.
Hutchinson, Shinelle, et al. “Investigating Wearable Fitness Applications: Data Privacy and Digital Forensics Analysis on Android.” Applied Sciences, vol. 12, no. 19, 1 Jan. 2022, p. 9747, www.mdpi.com/2076-3417/12/19/9747/htm,https://doi.org/10.3390/app12199747.
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Kim, Kwang Bok, and Hyun Jae Baek. “Photoplethysmography in Wearable Devices: A Comprehensive Review of Technological Advances, Current Challenges, and Future Directions.” Electronics, vol. 12, no. 13, 1 Jan. 2023, p. 2923, www.mdpi.com/2079-9292/12/13 /2923 , https://doi.org/10.3390/electronics1213292 3.
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Lin, Qiang, et al. “Advanced Artificial Intelligence in Heart Rate and Blood Pressure Monitoring for Stress Management.” Journal of Ambient Intelligence and Humanized Computing, vol. 12, no. 3, 6 Nov. 2020, pp. 3329–3340, https://doi.org/10.1007/s12652-02 0-02650-3.
Mejía-Mejía, Elisa, et al. “Heart Rate Variability (HRV) and Pulse Rate Variability (PRV) for the Assessment of Autonomic Responses.” Frontiers in Physiology, vol. 11, 23 July 2020, https://doi.org/10.3389/fphys .2020.00779.
Nahavandi, Darius, et al. “Application of Artificial Intelligence in Wearable Devices: Opportunities and Challenges.” Computer Methods and Programs in Biomedicine, vol. 213, no. 1, Jan. 2022, p.
106541,https://doi.org/10.1016/j.cmpb.2021.106541.
Neuwirth, Rostam J. “The Global Regulation of “Fake News” in the Time of Oxymora: Facts and Fictions about the Covid-19 Pandemic as Coincidences or Predictive Programming?” International Journal for the Semiotics of Law - Revue Internationale de Sémiotique Juridique, 13 Apr. 2021, https://doi.org /10.1007/s11196-021-09840-y. Accessed 9 May 2021.
Nguyen, Quyen N. T., et al. “Validation Framework for Sleep Stage Scoring in Wearable Sleep Trackers and Monitors with Polysomnography Ground Truth.” Clocks & Sleep, vol. 3, no. 2, 1 June 2021, pp. 274–288, www.mdpi.com/2624-5175/3/2/17# cite,https://doi.org/10.3390/clockssleep3020017. Accessed 16 May 2021.
Oakley, Amanda. “HIPAA, HIPPA, or HIPPO: What Is the Health Insurance Portability and Accountability Act?” Biotechnology Law Report, vol. 42, no. 6, 23 Nov. 2023, https://doi.org/10.1089/blr.2023.29329. aso.
Tadeusz Hawrot. “Psychedelic Therapies: The Case for a New Focus in the EU’s Mental Health Care Approach.” Open Access Government, vol. 39, no. 1, 10 July 2023, pp. 188–189, https://doi.org/10.56367/oag-039-110-edit. Accessed 1 Oct. 2023.
Thompson, Stuart A., and Charlie Warzel. “Twelve Million Phones, One Dataset, Zero Privacy.” Auerbach Publications EBooks, 16 Mar. 2022, pp. 161–169, https://doi.org/10.1201/9781003278290-25. Accessed 12 June 2024.
Wu, Yichen, et al. “Achieve Personalized Exercise Intensity through an Intelligent System and Cycling Equipment: A Machine Learning Approach.” Applied Sciences, vol. 10, no. 21, 30 Oct. 2020, p. 7688,
https://doi.org/10.3390/app10217688. Acces sed 11 Apr. 2021.
Xiangfang, Ren, et al. “Research and Sustainable Design of Wearable Sensor for Clothing Based on Body Area Network.” Cognitive Computation and Systems, vol. 3, no. 3, 16 Apr. 2021, pp. 206–220, https://doi. org/10.1049/ccs2.12014.
Published
2024-07-23
How to Cite
Komalasari, R. (2024) “AI-Powered Wearables Revolutionizing Health Tracking and Personalized Wellness Management”, Timor Leste Journal of Business and Management, 6, pp. 42-50. doi: 10.51703/bm.v6i0.163.
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Articles
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