Motor Imagery-Based Brain-Computer Interface Coupled to a Robotic Hand Orthosis Aimed for Neurorehabilitation of Stroke Patients

Abstract

Motor imagery-based brain-computer interfaces (BCI) have shown potential for the rehabilitation of stroke patients; however, low performance has restricted their application in clinical environments. Therefore, this work presents the implementation of a BCI system, coupled to a robotic hand orthosis and driven by hand motor imagery of healthy subjects and the paralysed hand of stroke patients. A novel processing stage was designed using a bank of temporal filters, the common spatial pattern algorithm for feature extraction and particle swarm optimisation for feature selection. Offline tests were performed for testing the proposed processing stage, and results were compared with those computed with common spatial patterns. Afterwards, online tests with healthy subjects were performed in which the orthosis was activated by the system. Stroke patients' average performance was 74.1 ± 11%. For 4 out of 6 patients, the proposed method showed a statistically significant higher performance than the common spatial pattern method. Healthy subjects' average offline and online performances were of 76.2 ± 7.6% and 70 ± 6.7, respectively. For 3 out of 8 healthy subjects, the proposed method showed a statistically significant higher performance than the common spatial pattern method. System's performance showed that it has a potential to be used for hand rehabilitation of stroke patients.

Longitudinal Analysis of Stroke Patients’ Brain Rhythms during an Intervention with a Brain-Computer Interface

“…Cortical activation differences were observed in several regions across sessions of the BCI intervention. In both alpha and beta, activation changes were observed over the somatosensory cortex, which could be expected since MI-BCI systems coupled to robotic assistive devices have shown to elicit activity above this area in stroke patients [15, 27]. However, these central area significant changes across sessions were not associated in all patients with time since stroke onset.…”

“…When activated by the BCI system, the robotic orthosis provided passive flexion followed by extension of the fingers of the hand. A more detailed description of the BCI system can be found in the work by Cantillo-Negrete et al [27]. A depiction of the BCI system is shown in Figure 1.…”

The Effects of Combined Low Frequency Repetitive Transcranial Magnetic Stimulation and Motor Imagery on Upper Extremity Motor Recovery Following Stroke

“…Another non-invasive neuromodulation technique-motor imagery (MI), has been validated to increase the efficacy of rehabilitation and improve the performance of tasks associated with MI in patients after stroke (15–17). The functional recovery of most stroke patients occurred mainly in the first 3 months, and the functional gain obtained in the chronic phase was limited (18).…”

Brain–Computer Interfaces in Neurorecovery and Neurorehabilitation

“…15 Restoration of lost function typically entails bypassing a lesion incurred by disease or trauma, with the aim of directly supplanting the function lost. Examples of this include BCIenabled prosthetic arm control to supplant lost limb function 10,[16][17][18][19][20][21] or BCI-enabled typing or speech to supplant impaired verbal communication capability. [22][23][24][25][26][27][28][29][30] In so doing, such technologies facilitate novel means to perform an activity in a manner that bypasses the lesioned area that is ordinarily engaged in performing that function.…”