Abstract
Interactive games have the potential to mitigate or prevent gait impairments and cognitive decline in older adults. This study aimed at developing a novel real-time step detection and direction classification approach to be used in the evaluation of multidirectional steps and interaction while playing motor-cognitive games. Two shoe-mounted inertial sensors were used to capture foot motions, which were treated interchangeably after the application of a novel foot sagittal reflection method. A single multi-class classifier was able to distinguish step direction with an accuracy of 98.1%. Experimental results support the applicability of the solution in the context of interactive motor-cognitive training.
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