Dr. Chester’s current research aims to develop novel and intelligent healthcare tools to detect, diagnose and treat autism spectrum disorder gait impairments using personalized data. High quality data and machine learning algorithms can be a continuous source of data-driven learning to optimize patient quality of life, biomedical research and public health.
Dr. Chester received a Ph.D. in Mechanical Engineering from the University of New Brunswick in 2004, and also holds an undergraduate degree in Human Kinetics from the University of Guelph and a Master’s degree in Biomechanics from Laurentian University.
Current research projects include:
- Typical and clinical lower and upper extremity mechanics across the lifespan;
- Improved mechanical models of the foot and ankle;
- Assessment/development of treatment, rehabilitative and preventative strategies for improving mobility & QoL;
- Development of wearable sensors for assessing mobility;
- Classification of gait using machine learning tools.
