A SHARCNET Undergraduate Fellowship funded a study to determine if an Artificial Neural Network based model could be used to approximate an individualís center of mass (COM) during dynamic movements in upright stance given only pressure data originating from pressure sensing insoles. The objective was to gain insight into how the human postural control system uses this sensory information to control balance. The model demonstrated good prediction of the COM in the anterior/posterior direction and an extension of this model to 2-D space, incorporating medial/lateral information. Pilot work has also begun on modeling the COM and it relationship to the base of support during gait using pressure insoles.
Dr. Stephen Perry
Department of Kinesiology & Physical Education