Ubiquitous vital sign monitoring with loss of balance detection

This project will develop a loss of balance detection system to enhance the iMD Research Vital Zenzer, which monitors vital user biometrics. Accelerometer signals from both waist and wrist-worn body locations will be analyzed to obtain key inputs for Machine Learning and AI algorithms. Such algorithms will be developed to adapt to changing user conditions such as progress in rehabilitation. Classification and feature extraction will use key vital sign parameters to identify stable versus unstable conditions. A loss of balance prediction and risk measure will be developed. Importantly, the security and privacy of user data will be integrated into the system. All development will be performed in collaboration with the iMD Research team.

Faculty Supervisor:

Sridhar Krishnan;Kristiina Valter-Mai;Reza Samavi;Kristiina Valter Mai

Student:

Partner:

iMD Research

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Toronto Metropolitan University

Program: