Depth Sensing for Improved Control of Lower Limb Prostheses

We developed an algorithm to segment stairs from depth sensing of the environment and extract significant measures to detect the user intention, such as the distance and angle from the stairs, the number of steps, stair height, and stair depth. We conducted several experiments to test the our system and achieved 98.8% accuracy.

Link to TBME paper

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