Date of Award
Master of Science in Engineering (MSE)
Electrical and Computer Engineering
Body area networks (Electronics), Equilibrium (Physiology)--Testing., Internet of things.
In an aging society with increased lifespans, falls represent a serious risk for older adults. Balance is a key indicator of mobility, stability, and risk of falls. Wireless body area networks (WBAN) provide opportunity for unobtrusive monitoring and assessment of balance impairments and mobility. This thesis presents an implementation of WBAN system for monitoring of balance in older adults in smart homes. The system features two wireless inertial sensor nodes, a smart watch, an always-on home server, and an Android smartphone application. The sensors are placed on the user’s lower back and forehead. We designed and implemented custom smart inertial sensors that synchronize with the connected home server running on a Raspberry Pi 3B Linux controller. We implemented a smartphone application to automate 4 stage balance test, recommended by the CDC. The application initiates the balance test, while server synchronizes sensors, acquires and processes data from the sensors, and collects all records. The user subsequently receives a test summary, while raw data is stored on the home server for additional post-processing by the smartphone application using Python scripts.
Ganegoda, Harsha, "An implementation of the wireless body area network of synchronized inertial sensors for balance testing" (2020). Theses. 326.