Development of a Bioimpedance and sEMG Fusion Sensor for Gait Phase Detection: Validation with a Transtibial Amputee.

Abstract

Accurate gait phase detection is crucial for safe and efficient robotic prosthesis control in lower limb amputees. Several sensing modalities, including mechanical and biological signals, have been proposed to improve the accuracy of gait phase detection. In this paper, we propose a bioimpedance and sEMG fusion sensor for high-accuracy gait phase detection. We fabricated a wearable band-type sensor for multichannel bioimpedance and sEMG measurement, and we conducted gait experiments with a transtibial amputee to obtain biosignal data. Finally, we trained a deep-learning-based gait phase detection algorithm and evaluated its detection performance. Our results showed that using both bioimpedance and sEMG yielded the highest accuracy of 95.1%. Using only sEMG yielded a higher accuracy (90.9%) than that using only bioimpedance (85.1%). Therefore, we conclude that using both signals simultaneously is beneficial for improving the accuracy of gait phase detection. In addition, the proposed sensor can be applied to several applications by improving the accuracy of motion intention detection.