Graduation Semester and Year




Document Type


Degree Name

Master of Science in Computer Science


Computer Science and Engineering

First Advisor

David Levine


With the advent of new commercially available consumer grade fitness and health devices, it is now possible and very common for users to obtain, store, share and learn about some of their important physiological metrics such as steps taken, heart rate, quality of sleep and skin temperature. For devices with this wearable technology, it is common to find these sensors embedded in a smart watch, or dedicated wearable wrist bands such that among other functionalities of a wearable device, it is capable of smartly assisting users about their activity levels by leveraging the fact that these devices can be, and are typically, worn by people for prolonged periods of time. This new connected wearable technology has a great potential for physicians to be able to monitor and regulate their patients’ activity levels. There exist many software applications and complex Wireless Body Area Network (WBAN) based solutions for remote patient monitoring but what has been lacking is a solution for physicians, especially exercise physiologists, to automate and convey appropriate training levels and feedback in a usable manner. This work proposes a software framework that enables users to know their prescribed level of exercise intensity level and then record their exercise session and securely transmit it wirelessly to a centralized data-store where physiologists will have access to it.


Remote, Patient, Monitoring, Health, Band, Fitbit, Microsoft, Assist, Cloud, Microservice, Prescription, Exercise, Activity level, Intensity level


Computer Sciences | Physical Sciences and Mathematics


Degree granted by The University of Texas at Arlington