Empowering human health with wearables : exploring the feasibility and efficacy of AI-powered health mentoring systems
Tun, Zaw Ye (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024112029023
https://urn.fi/URN:NBN:fi:amk-2024112029023
Tiivistelmä
This thesis deals with AI mentoring systems in the medical field especially in wearable technology and how it could be applied to individual health and wellness by studying the feasibility and efficacy of AI health wearable devices on end user perspective. The primary data was collected by employing a quantitative research method, distributing surveys to students of Oulu University of Applied Sciences.
The statistical analysis includes descriptive statistics, correlation analysis, and thematic coding for frequency of use of the wearable, user satisfaction, perceived accuracy, and health impact. The feedback from the respondents says that they are extremely pleased with the ease of use, physical activity tracking and sleep improvement but not quite as much with the ability to motivate behavior and improve health. Users expressed notable concerns over data accuracy, privacy, and device costs, with recommendations for improving AI integration in wearables to better meet health goals. This thesis would show what is coming from the user perspective, what the AI health systems lack, and what improvements need to be made on the AI health mentoring technology.
The statistical analysis includes descriptive statistics, correlation analysis, and thematic coding for frequency of use of the wearable, user satisfaction, perceived accuracy, and health impact. The feedback from the respondents says that they are extremely pleased with the ease of use, physical activity tracking and sleep improvement but not quite as much with the ability to motivate behavior and improve health. Users expressed notable concerns over data accuracy, privacy, and device costs, with recommendations for improving AI integration in wearables to better meet health goals. This thesis would show what is coming from the user perspective, what the AI health systems lack, and what improvements need to be made on the AI health mentoring technology.