EEG-Controlled Functional Electrical Stimulation Therapy With Automated Grasp Selection: A Proof-of-Concept Study

Abstract

Functional electrical stimulation therapy (FEST) is a promising intervention for the restoration of upper extremity function after cervical spinal cord injury (SCI). This study describes and evaluates a novel FEST system designed to incorporate voluntary movement attempts and massed practice of functional grasp through the use of brain-computer interface (BCI) and computer vision (CV) modules. An EEG-based BCI relying on a single electrode was used to detect movement initiation attempts. A CV system identified the target object and selected the appropriate grasp type. The required grasp type and trigger command were sent to an FES stimulator, which produced one of four multichannel muscle stimulation patterns (precision, lateral, palmar, or lumbrical grasp). The system was evaluated with five neurologically intact participants and one participant with complete cervical SCI. An integrated BCI-CV-FES system was demonstrated. The overall classification accuracy of the CV module was 90.8%, when selecting out of a set of eight objects. The average latency for the BCI module to trigger the movement across all participants was 5.9 ± 1.5 seconds. For the participant with SCI alone, the CV accuracy was 87.5% and the BCI latency was 5.3 ± 9.4 seconds. BCI and CV methods can be integrated into an FEST system without the need for costly resources or lengthy setup times. The result is a clinically relevant system designed to promote voluntary movement attempts and more repetitions of varied functional grasps during FEST.

Brain-Computer Interface Controlled Functional Electrical Stimulation: Evaluation With Healthy Subjects and Spinal Cord Injury Patients

“…In summary, the proposed BCI system's classifiers indicate that the BCI can discriminate successfully between the different MI conditions and a resting period. This is consistent with results of studies published within the field [25], [29], [30], [32], [70], [72], [76]. Therefore, we can expect that most healthy people and SCI patients with mild to moderate disability levels could be potential users of this technology.…”

“…However, BCI performance results were not reported in this study. In [29], this proof-of-concept study evaluated a FES system designed to incorporate voluntary movement attempts through the use of BCI. The BCI used power changes from a single EEG signal (compared against a predetermined threshold) as a feature to control FES activation.…”

Hemodynamic Signal Changes During Motor Imagery Task Performance Are Associated With the Degree of Motor Task Learning

“…An important aspect in mental practice is how vividly an individual can perform MI; if MI vividness can be evaluated neurophysiologically, MI can be used effectively in rehabilitation. MI is already used in neurofeedback systems such as Brain Computer Interface (BCI) and Functional electrical stimulation therapy ( Khan et al, 2015 ; Koo et al, 2016 ; Likitlersuang et al, 2018 ). Our results demonstrate that hemodynamic signal changes in the SMA are associated with MI vividness, which can be used not only for mental practice but also for other techniques such as BCI.…”

Neural Bypasses: Literature Review and Future Directions in Developing Artificial Neural Connections

“…Motor imagery with EEG paired with FES has also been used to activate shoulder movements through stimulation of the deltoid and supraspinatus muscles [23,24]. Furthermore, studies have utilized microelectrode arrays implanted in the motor cortex, or implanted ECoG grids paired with FES, to control the magnitude and time course of arm movements, including reaching and grasping [3,7,18,32,33,37,43,45,46]. Cortical microelectrode recordings from M1 have also been decoded to produce graded force in wrist movements, moving past binary flexion and extension movements [51].…”