Single EMG Sensor-Driven Robotic Glove Control for Reliable Augmentation of Power Grasping

The practical operation of wearable robots requires intuitive, compact, yet reliable control interfaces. However, current myoelectric interfaces based on surface electromyography (EMG) often fail to achieve these requirements by demanding multiple sensors and exhibiting unreliable performance under limb posture changes. In this study, we show that a interface the musculotendinous junctions (MTJs) flexor digitorum superficialis (FDS) enables robotic glove with single EMG sensor identifying power grasp intentions. We found signals from MTJs FDS significantly increased amplitudes exclusively when is performed, regardless arm posture. systematically verified that, in intentions, proposed single-sensor even outperforms five-sensor around proximal forearm. By exploiting unique biological feature MTJs, devised two methods for glove-Dual-threshold Morse-code control-and further showed their performances operations. Dual-threshold direct co-operation between user glove, provides various command options user.