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ML & FSM help amputees walk more naturally

Blog: Decision Management Community

Researchers from the University of Utah designed a robotic leg that learns from the user’s motion how to help amputees walk more naturally.  It uses machine learning to generate a human-like stride. It also helps wearers step over obstacles in a natural way. Link  Rather than trying to recognize obstacles in the user’s path, the prosthesis relies on cues from the user’s body to tell it when something is in the way. Sensors in the user’s hip feed data a thousand times per second into a processing unit located in the unit’s calf. For instance, the way a user rotates their hip might tell the leg to tuck its knee to avoid tripping over an obstacle.

(courtesy of Andrew Ng)

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