Neural evidence for functional roles of tactile and visual feedback in the application of myoelectric prosthesis

Abstract

Abstract. Objective. The primary purpose of this study was to investigate the electrophysiological mechanism underlying different modalities of sensory feedback and multi-sensory integration in typical prosthesis control tasks. Approach. We recruited 15 subjects and developed a closed-loop setup for three prosthesis control tasks which covered typical activities in the practical prosthesis application, i.e., prosthesis finger position control (PFPC), grasping force control (GFC) and box and block control (BABC). All the three tasks were conducted under tactile feedback (TF), visual feedback (VF) and tactile-visual feedback (TVF), respectively, with a simultaneous electroencephalography (EEG) recording to assess the electroencephalogram (EEG) response underlying different types of feedback. Behavioral and psychophysical assessments were also administered in each feedback condition. Results. EEG results showed that VF played a predominant role in GFC and BABC tasks. It was reflected by a significantly lower somatosensory alpha event-related desynchronization (ERD) in TVF than in TF and no significant difference in visual alpha ERD between TVF and VF. In PFPC task, there was no significant difference in somatosensory alpha ERD between TF and TVF, while a significantly lower visual alpha ERD was found in TVF than in VF, indicating that TF was essential in situations related to proprioceptive position perception. Tactile-visual integration was found when TF and VF were congruently implemented, showing an obvious activation over the premotor cortex in the three tasks. Behavioral and psychophysical results were consistent with EEG evaluations. Signi cance. Our findings could provide neural evidence for multi-sensory integration and functional roles of tactile and visual feedback in a practical setting of prosthesis control, shedding a multi-dimensional insight into the functional mechanisms of sensory feedback.

An early force prediction control scheme using multimodal sensing of electromyography and digit force signals

“…However, multiple decision making complexities are involved within the human body to perform these tasks. The complexities include decision making for the type of gesture required to grasp the object, the selection of the grip force and feedback information from the sensory system of the hand and the visual sensory system of the eyes [ [1] , [2] , [3] , [4] ]. The decoding of the different muscle and brain signals has resulted in the designing of bionic devices.…”

“…Any error in the force prediction may result in the slippage of the object or breakage of the object. The neurophysiological studies have shown the complexities and changes in the somatosensory system, related to the skin [ 4 , 7 , 20 , 21 ]. These studies have shown that a human hand possesses a strong feedback system to manipulate the force while grasping an object [ 20 ].…”