Fig. 1.
a Typical profiles of velocities of the elbow and hand aperture in abled-bodied subject [21, 45, 46] compared to that generated with a traditional prosthetic device, as presented in [25, 26]. During reaching, the aperture of the human hand (solid green line) changes in coordination with the extension of the arm (dashed blue line). In contrast, the prosthetic hand (dash-dotted red line) begins its motion later in the reach-to-grasp cycle, once the elbow is fully extended. In our approach, we separate the reach-to-grasp motion into three phases (denoted by dashed vertical lines) according to the angular acceleration of the elbow joint ael. We distinguish between acceleration, deceleration and rest phases. We present that a pattern recognition system, trained including the reaching motion, could gain efficient prediction confidence early in the reaching motion and, thus, activate faster a prosthetic device. b The selected five grasp types used in our classification, following the names and using figures from the taxonomy of [47]. c Experimental set-up for training the system with amputee subjects in data recordings. EMG-information from the amputated arm are recorded while the subject performs the reach and grasp motion with his/her intact arm