Enhancing Prosthetic Safety and Environmental Adaptability: A Visual-Inertial Prosthesis Motion Estimation Approach on Uneven Terrains
Chuheng Chen, Xinxing Chen, Shucong Yin, Yuxuan Wang, Binxin Huang,, Yuquan Leng, Chenglong Fu

TL;DR
This paper introduces a visual-inertial motion estimation method for prostheses to improve safety and adaptability on uneven terrains by accurately perceiving movement and environment changes.
Contribution
It presents a novel approach combining depth camera data and inertial sensors with Kalman filtering to robustly estimate prosthetic motion on uneven terrains.
Findings
Accurately tracks prosthetic and leg motion with less than 5 cm RMS error.
Enhances environmental perception for safer prosthesis control.
Demonstrates effectiveness on stair walking trials.
Abstract
Environment awareness is crucial for enhancing walking safety and stability of amputee wearing powered prosthesis when crossing uneven terrains such as stairs and obstacles. However, existing environmental perception systems for prosthesis only provide terrain types and corresponding parameters, which fails to prevent potential collisions when crossing uneven terrains and may lead to falls and other severe consequences. In this paper, a visual-inertial motion estimation approach is proposed for prosthesis to perceive its movement and the changes of spatial relationship between the prosthesis and uneven terrain when traversing them. To achieve this, we estimate the knee motion by utilizing a depth camera to perceive the environment and align feature points extracted from stairs and obstacles. Subsequently, an error-state Kalman filter is incorporated to fuse the inertial data into visual…
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Taxonomy
TopicsHand Gesture Recognition Systems · Tactile and Sensory Interactions · Gaze Tracking and Assistive Technology
