Date of Award
2022
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Electrical Engineering
First Advisor
Ryan S. McGinnis
Abstract
Wearable sensors are growing in popularity in the medical field to help measurephysiological signals from patients. The M-Sense Research Group at the University of Vermont uses wearable sensors to measure accelerometer and gyroscope data of patients with multiple sclerosis amongst other clinical applications. The sensors are attached directly to a patient’s skin on the chest and thigh and are worn for anywhere from an hour or two when being monitored in the lab or for five weeks when wearing the sensors at home. Current wearable sensors are closed source and do not allow recorded data to be seen in real time. The purpose of this thesis was to create a new, open-source, and configurable wearable sensor system with the ability monitor data collected in real time. An iterative design process was used to develop a new wearable sensor system leveraging Arduino hardware, software, and cloud infrastructure. The final sensor design was able to measure and record wearable sensor data as well as current commercial sensor technologies while also providing the desired new features. Specifically, the sensor system was able to display data in real time via a computer or phone while also allowing easy hardware and software upgrades to meet the needs of future research studies.
Language
en
Number of Pages
70 p.
Recommended Citation
Joyce, Conor, "Open-Source Wearable Sensors For Detecting Fall Risk In Patients With Multiple Sclerosis" (2022). Graduate College Dissertations and Theses. 1558.
https://scholarworks.uvm.edu/graddis/1558