Objective: Using the Twente Medical Systems international B.V. (TMSi) electromyography (EMG) system, active signal shielding was applied to clean signals and create data without interference and cable movement artifacts. TMSi, used in high-density surface EMG pattern recognition, controls myoelectric rehabilitation robots, yet few have studied how active signal shielding influences pattern recognition. This study aimed to investigate how active signal shielding used within the TMSi influenced motion pattern recognition.
Methods: Surface EMG of dominant side forearm and hand muscles was studied in eight healthy participants. The common component’s influence was accessed by the classification performance of wrist and hand functional movements.
Results: The classification performance of EMG signals with the common component was obviously lower than signals without the common component using one to five electrodes. Conversely, a higher motion classification performance was achieved using signals with the common component using over 12 electrodes. Optimal channel distribution was examined based on the sequential feed-forward selection method, showing that the common component affected the optimal channel location.
Conclusions: Active signal shielding in the TMSi improved classification accuracy in motion pattern recognition when over 12 electrodes were used. The optimal channel distribution was related to the common component when using the TMSi.
Keywords: Electromyography; TMSi system; common component; myoelectrical pattern recognition; sequential feed-forward selection method; signal shielding technology.