TY - JOUR AU - Zhang, Xiaorong AU - Huang, He PY - 2015 DA - 2015/02/19 TI - A real-time, practical sensor fault-tolerant module for robust EMG pattern recognition JO - Journal of NeuroEngineering and Rehabilitation SP - 18 VL - 12 IS - 1 AB - Unreliability of surface EMG recordings over time is a challenge for applying the EMG pattern recognition (PR)-controlled prostheses in clinical practice. Our previous study proposed a sensor fault-tolerant module (SFTM) by utilizing redundant information in multiple EMG signals. The SFTM consists of multiple sensor fault detectors and a self-recovery mechanism that can identify anomaly in EMG signals and remove the recordings of the disturbed signals from the input of the pattern classifier to recover the PR performance. While the proposed SFTM has shown great promise, the previous design is impractical. A practical SFTM has to be fast enough, lightweight, automatic, and robust under different conditions with or without disturbances. SN - 1743-0003 UR - https://doi.org/10.1186/s12984-015-0011-y DO - 10.1186/s12984-015-0011-y ID - Zhang2015 ER -