Abstract
Brain-computer interfaces (BCIs) have been proven to be useful for stroke rehabilitation, but there are a number of factors that impede the use of this technology in rehabilitation clinics and in home-use, the major factors including the usability and costs of the BCI system. The aims of this study were to develop a cheap 3D-printed wrist exoskeleton that can be controlled by a cheap open source BCI (OpenViBE), and to determine if training with such a setup could induce neural plasticity. Eleven healthy volunteers imagined wrist extensions, which were detected from single-trial electroencephalography (EEG), and in response to this, the wrist exoskeleton replicated the intended movement. Motor-evoked potentials (MEPs) elicited using transcranial magnetic stimulation were measured before, immediately after, and 30 min after BCI training with the exoskeleton. The BCI system had a true positive rate of 86 ± 12% with 1.20 ± 0.57 false detections per minute. Compared to the measurement before the BCI training, the MEPs increased by 35 ± 60% immediately after and 67 ± 60% 30 min after the BCI training. There was no association between the BCI performance and the induction of plasticity. In conclusion, it is possible to detect imaginary movements using an open-source BCI setup and control a cheap 3D-printed exoskeleton that when combined with the BCI can induce neural plasticity. These findings may promote the availability of BCI technology for rehabilitation clinics and home-use. However, the usability must be improved, and further tests are needed with stroke patients.
Highlights
Brain-computer interfaces (BCIs) have over the past years been proposed as a tool for motor rehabilitation after neural injuries, such as spinal cord injury or stroke [1,2,3,4,5,6].It is well-established that brain-computer interface (BCI) can be used for inducing neural plasticity [7,8,9,10,11], which is believed to be the underlying mechanism of motor learning/recovery [12]
It has been shown previously that neural plasticity, when quantified with transcranial magnetic stimulation (TMS), can be induced using BCI-triggered electrical stimulation and passive movements from rehabilitation robots/exoskeletons for the cortical projections of the lower limb muscles [7,8,9,10,11], but this has not been shown for the cortical projections of the upper limb muscles, functional improvements in stroke patients have been reported for the upper limbs
86 ± 12% of the imaginary wrist extensions were correctly detected by the asynchronous BCI, while there were 1.20 ± 0.57 false positive detections per minute and 0.63±0.58 false negatives per minute
Summary
Brain-computer interfaces (BCIs) have over the past years been proposed as a tool for motor rehabilitation after neural injuries, such as spinal cord injury or stroke [1,2,3,4,5,6].It is well-established that BCIs can be used for inducing neural plasticity [7,8,9,10,11], which is believed to be the underlying mechanism of motor learning/recovery [12]. Several low-cost commercial EEG systems have become available [18] Some of these systems may not be useful for applications where neural plasticity is induced in the motor system, since they do not record electrical activity from the relevant brain areas [19]. It is possible to create a simple exoskeleton that can perform wrist extensions or the dorsiflexion of the ankle joint with a single actuator [11] Both of these movement types are important to train during stroke rehabilitation. The aim of this study is to investigate if a BCI-triggered exoskeleton can induce neural plasticity in the cortical projections of the forearm muscles that control wrist extension It will be tested if this is possible using a low-cost EEG amplifier and open source BCI software
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