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This study was undertaken to determine if an Artificial Neural Network based model could be used to approximate an individual’s center of mass (COM) during dynamic movements in upright stance given only pressure data originating from pressure sensing insoles. This type of modelling may provide insight into how the human postural control system uses this sensory information to control balance.
The activity was voluntary leaning in four directions (forward, right, left and backwards) all held for just over a second. The model demonstrated good prediction of the COM in the anterior/posterior direction such that the predicted COM approximation was within 10 mm of the measured COM. Extension of this model to 2-D space, incorporating medial/lateral information, has also given a good prediction of the COM location.
Pilot work has also begun on modelling the COM and its relationship to the base of support during gait using pressure insoles; some data is presented here and has shown encouraging results as we continue to the next logical stage of development.
Funded by SHARCNet Undergraduate Fellowships.
Stephen Perry, Director