Environmental Context Prediction for Lower Limb Prostheses With Uncertainty Quantification
Zhong, B., Silva, R. L., Li, M., Huang, H., & Lobaton, E. (2020, May 22). IEEE Transactions on Automation Science and Engineering.
author keywords: Uncertainty; Neural networks; Bayes methods; Measurement uncertainty; Cameras; Microsoft Windows; Bayesian neural network (BNN); environmental context prediction; prosthesis; uncertainty quantification
topics (OpenAlex): Prosthetics and Rehabilitation Robotics; Muscle activation and electromyography studies; Context-Aware Activity Recognition Systems
TL;DR:
A novel vision-based context prediction framework for lower limb prostheses to simultaneously predict human’s environmental context for multiple forecast windows by leveraging the Bayesian neural networks (BNNs) and producing a calibrated predicted probability for online decision-making.
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