Predicting chronic diseases using health records and wearable data
Approved Research ID: 94364
Approval date: January 11th 2023
The goal of this research is to associate information from wearable devices, like smartwatches and fitness trackers, to the health of their wearer and to the risk of getting a chronic disease. The importance of the physical activity to overall health has been observed in other studies. Our goal is to use AI models to process wearable device information about a person's physical activity (how many steps are taken throughout the day, for example) and link it to the appearance of chronic diseases and other health problems. We will also compare this procedure to the information from the clinical setting to assess its performance.
We will make the result of our work available in a mobile application, so that every member of the public can benefit from it by evaluating his or her own physical activity. We believe that such an evaluation will promote healthier living by providing better health awareness, by sending warnings when detecting early signs of diseases, and by providing health and wellness tips. Additionally, anyone can check the effects of new or ongoing daily habits on their health by comparing this evaluation over time. We estimate the required time to complete this study to be 36 months.