jasmineyliang / ml-imu-termproj

Prediction of the individual with over-weighted based on the center of mass acceleration data during the gait cycle.

ml-imu-termproj

Obesity is a prevalent issue in the U.S. The prevalence of obesity is increasing over the decade. Many underlying risks can lead to a critical health problem. Moreover, obesity is also a potential risk factor for cardiovascular disease (CVD) and diabetes. Recent advances in wearable motion sensor technologies offer an opportunity to translate laboratory ndings to the clinical environment with similar gait balance measures. Inertial measurement units (IMU) combine accelerometers, gyroscopes, and magnetometers into a single sensor and could be used to estimate COM acceleration. The use of wearable sensors to detect mobility impairments has grown rapidly and provides a time-efficient and user-friendly measurement of gait and balance performance. The IMU is placed at COM's proxy location. This project aims to investigate whether the gait pattern would change in an individual with obesity. We hypothesized that obesity could be detected by using the COM acceleration data from self-selected speed walking.