Insole-based sensor fusion for ambulatory gait analysis for occupational health & safety

MEGA InTech aims to maintain healthy workers and prevent injuries. This research will advance a smart insole to deliver analyses of ambulatory gait and posture. Specifically, signal processing and sensor fusion algorithms to deliver detailed metrics of gait and occupational ergonomics will be developed. The proposed methodology will leverage the partner’s prototype insole sensor hardware to generate sensor fusion algorithms to estimating the target metrics related to occupational health & safety (e.g., falls, fatigue, soft tissue injury). To develop and test new algorithms, research-grade biomechanics equipment available at the University of Waterloo will be used as criterion-standard measurements to compare algorithm outputs derived from prototype insole sensor signals. The deliverables of this project are: 1) algorithms delivering gait and posture analytics, 2) reports detailing methods and test results, and 3) acquired datasets. The proposed research will advance products and tools towards maintaining occupational health and safety.

Faculty Supervisor:

James Tung;Arash Arami

Student:

Partner:

MEGA InTech

Discipline:

Engineering

Sector:

Wholesale trade

University:

University of Waterloo

Program: