Home-Based Monitor for Gait and Activity Analysis

TLDR

Clinical trials for neuromuscular disorders rely on motor function scales, timed tests, and strength measures administered by trained evaluators, but these point assessments are subjective and susceptible to daily patient variability such as fatigue and motivation. The study develops a wearable magneto‑inertial sensor to enable home‑based monitoring of gait and activity. The WMIS consists of two lightweight watch‑like sensors equipped with tri‑axial accelerometers, gyroscopes, magnetometers, and barometers, worn on the wrist, ankle, or wheelchair, and a docking station for overnight charging and data upload, and proprietary algorithms analyze the recorded signals to compute movement parameters. The WMIS records digital biomarkers, including total distance walked and the proportion of fastest or longest strides, providing objective gait metrics over a defined period.

Abstract

Current outcomes in neuromuscular disorder clinical trials include motor function scales, timed tests, and strength measures performed by trained clinical evaluators. These measures are slightly subjective and are performed during a visit to a clinic or hospital and constitute therefore a point assessment. Point assessments can be influenced by daily patient condition or factors such as fatigue, motivation, and intercurrent illness. To enable home-based monitoring of gait and activity, a wearable magneto-inertial sensor (WMIS) has been developed. This device is a movement monitor composed of two very light watch-like sensors and a docking station. Each sensor contains a tri-axial accelerometer, gyroscope, magnetometer, and a barometer that record linear acceleration, angular velocity, the magnetic field of the movement in all directions, and barometric altitude, respectively. The sensors can be worn on the wrist, ankle, or wheelchair to record the subject's movements during the day. The docking station enables data uploading and recharging of sensor batteries during the night. Data are analyzed using proprietary algorithms to compute parameters representative of the type and intensity of the performed movement. This WMIS can record a set of digital biomarkers, including cumulative variables, such as total number of meters walked, and descriptive gait variables, such as the percentage of the most rapid or longest stride that represents the top performance of patient over a predefined period of time.