AI-Powered Wireless Human Activity Recognition for Safety and Health Improvement

Human’s gait, and activity monitoring play important roles in many applications that can have a positive impact on improving the ability of individuals to be as independent, secure, and healthy as possible. Most existing technologies rely on cameras and wearables, while people are not always compliant and need to be wearing them with a battery charge for them to work. Camera-based sensors, on the other hand, systems are sensitive to high-contrast light and poor visibility conditions and suffer from obstructed line-of sight conditions and privacy concerns. The purpose of this research project is to develop zero e?ort and wireless sensors for independent and autonomous gait monitoring and activity recognition.

Faculty Supervisor:

Plinio Pelegrini Morita;George Shaker

Student:

Partner:

TandemLaunch Inc

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology; Advanced Manufacturing; Information and Communications Technology

University:

University of Waterloo

Program: