Two-stage classification of electromyogram signals from hand grasps in the transverse plane

This paper presents a two-stage classification to resolve the effect of arm position changes on electromyogram (EMG) classification for hand grasps in the transverse plane. The proposed method combines the EMG signals with the signals from an inertial measurement unit in both the position and motion classification stages. To improve accuracy, we incorporate EMG data from the upper arm and shoulder with the forearm EMG signals. When evaluated on the five alternative object grasps placed on the nine positions, the proposed technique yields an average total classification error of 0.9%, which is a substantial improvement over the single-stage classification (4.3%).