Wearable Tech and Chronic Disease Management: An Interdisciplinary Study of Bioengineering, Data Analytics, and Patient Psychology

Abstract

The transformation of chronic disease management owes much to how wearable technology lets users watch over their health all day, provide timely assistance and receive personalized attention. The combined approach investigates how bioengineering, data analytics and understanding the psychology of patients are essential to effectively using wearables to manage diabetes, cardiovascular disease and many other illnesses. Bioengineering research has made it possible to create sensors that track important state measures comfortably and accurately. Data analytics, using machine learning, helps make sense of a lot of health data to identify when someone’s symptoms or risks may change, so healthcare can take action ahead of time. At the same time, understanding patient psychology helps drive adherence, strong involvement and appropriate behavior changes which determines the success of adopting these devices. Analysis of data from 150 patients together with interviews of patients, clinicians and bioengineers found that using wearables led to better symptom management, more compliance with medications and fewer visits to the hospital. Even so, data privacy, how easy it is to use technology and mental barriers are areas that deserve attention. The authors suggest a model that links engineering, data science and psychological approaches to better control chronic diseases through wearable technology. The findings support working together to create healthcare technology that is useful for both people and the technical side.