The study of bipedal gait is important for two primary reasons: biomimetic robotics and human gait rehabilitation. Both fields have numerous models describing bipedal locomotion that require a no-slip interaction with the ground for accuracy. This paper presents a low cost wearable sensor system capable of identifying slip in real time, which could afford rehabilitative analysts important information on the nature of patient falls, and provide robot designers a feedback ability with which to implement an active traction control system. The system can functionally provide better than 90% detection rates when calibrated to an individual.
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