A strain gauge based locomotion mode recognition method using convolutional neural network

Published in Advanced Robotics, 2019

Recommended citation: Y. Feng, W. Chen, and Q. Wang, "A strain gauge based locomotion mode recognition method using convolutional neural network," Advanced Robotics, vol. 33, no. 5, pp. 254-263, Jan. 2019, doi:10.1080/01691864.2018.1563500.

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In this paper, we propose a novel locomotion mode recognition method based on convolutional neural network and strain gauge signals. The strain gauge only provides one-dimensional signals and the convolutional neural network takes the raw noisy signals as inputs. The results show that the strain gauge contains information of locomotion modes, and the convolutional neural network has the capacity of extracting features from raw signals.

My responsibilities included collaborating with lab partner to collect data, training different neural network models in Tensorflow and analyzing the performance of the algorithms.