AI Based Video Assessment of Walking Speed (Gait)
2021 – 2022
Project goal: Aging adults want to age in place in their homes to remain in their community of friends, family and activities. This independence for many depends on the support of family care givers such as spouses or adult children that may live separately or work outside the home. The use of ambient sensors in the home can provide an extra level of knowledge about well-being. Specifically, video cameras have the potential to provide a great wealth of information but do so at the expense of privacy. Project partner AltumView, makes a unique video camera with built in Artificial Intelligence (AI) that detects and automatically removes people replacing them with a stick figure. This camera has the potential for use in well-being assessment without intruding on privacy. This project will specifically explore the potential for the assessment of walking speed (gait speed) as one measure of physical well-being.
PI: Bruce Wallace
Students: Ashi Agarwal
Other Funding: MITACS Accelerate
Ron Beleno (SAM3 CAC member), Bruce Wallace (SAM3 Exec Dir) and Bob Zhang (Altumview CFO) at the AGE-WELL AGM in Regina Oct 2022.
Wednesday, August 3, 2022
Agarwal, A., Wallace, B., Goubran, R., Knoefel, F., Thomas, N., “Method to Improve Gait Speed Assessment for Low Frame Rate AI Enabled Visual Sensor” 2022 IEEE Sensors Applications Symposium (SAS), 2022