Performance Assessment of a Brain–Computer Interface Driven Hand Orthosis

Abstract

Stroke survivors are typically affected by hand motor impairment. Despite intensive rehabilitation and spontaneous recovery, improvements typically plateau a year after a stroke. Therefore, novel approaches capable of restoring or augmenting lost motor behaviors are needed. Brain-computer interfaces (BCIs) may offer one such approach by using neurophysiological activity underlying hand movements to control an upper extremity orthosis. To test the performance of such a system, we developed an electroencephalogram-based BCI controlled electrically actuated hand orthosis. Six able-bodied participants voluntarily grasped/relaxed one hand to elicit BCI-mediated closing/opening of the orthosis mounted on the opposite hand. Following a short training/calibration procedure, participants demonstrated real-time, online control of the orthosis by following computer cues. Their performances resulted in an average of 1.15 (standard deviation: 0.85) false alarms and 0.22 (0.36) omissions per minute. Analysis of signals from electrogoniometers mounted on both hands revealed an average correlation between voluntary and BCI-mediated movements of 0.58 (0.13), with all but one online performance being statistically significant. This suggests that a BCI driven hand orthosis is feasible, and therefore should be tested in stroke individuals with hand weakness. If proven viable, this technology may provide a novel approach to the neuro-rehabilitation of hand function after stroke.

Use of Electroencephalography Brain‐Computer Interface Systems as a Rehabilitative Approach for Upper Limb Function After a Stroke: A Systematic Review

“…A total of 248 articles were retrieved, but only 45 were selected for further review and critical reading, according to the previously established selection procedure. Finally, 13 of the 45 articles met the inclusion criteria [8,51‐62], and 32 were excluded [29,63‐93] (Table 4) (Figure 1). The methodological quality of the included articles, measured with the Critical Review Form, ranged between 6 and 15 (Table 5).…”

The feasibility of a brain-computer interface functional electrical stimulation system for the restoration of overground walking after paraplegia

“…These spatio-spectral data were then subjected to dimensionality reduction using classwise principal component analysis (CPCA) [ 18 , 19 ], and discriminating features were extracted using approximate information discriminant analysis (AIDA) [ 20 ]. Note that this feature extraction method is rooted in information theory [ 21 ] and has been extensively tested in our prior BCI studies [ 10 , 15 , 16 , 22 , 23 ]. More formally, one-dimensional (1D) features were extracted by: …”

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

“…In addition, robotic devices have produced stroke rehabilitation outcomes at least as effective as those achieved with traditional therapies [ 4 ]. Brain-computer interfaces (BCI) are another type of assistive technology; these systems provide an artificial communication channel between the brain and an external device such as a robotic orthosis [ 5 , 6 ]. BCIs based on motor imagery (MI) of affected limbs have shown great potential as a tool for brain plasticity enhancement [ 7 , 8 ].…”

“…Some of the advantages of these combined systems are that they are noninvasive, are fully automated, and could increase brain plasticity. Some studies have evaluated the performances of these BCI systems with healthy subjects [ 6 ], as well as some proofs of concept [ 26 , 27 ] and a randomised controlled trial [ 28 ] that have demonstrated positive rehabilitation outcomes for stroke patients. Even though BCI systems coupled to robotic assistive devices have shown promising outcomes for stroke rehabilitation, to date, none of such systems are used in clinical practice.…”