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nduction of Neural Plasticity Using a Low-Cost Open Source Brain-Computer Interface and a 3D-Printed Wrist Exoskeleton
Sensors ( IF 3.4 ) Pub Date : 2021-01-15 , DOI: 10.3390/s21020572
Mads Jochumsen , Taha Al Muhammadee Janjua , Juan Carlos Arceo , Jimmy Lauber , Emilie Simoneau Buessinger , Rasmus Leck Kæseler

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.

中文翻译:

低成本开源脑机接口和3D打印腕部外骨骼的神经可塑性诱导

脑机接口(BCI)已被证明对中风康复有用,但有许多因素阻碍了该技术在康复诊所和家庭使用中的使用,主要因素包括脑卒中的可用性和成本。 BCI系统。这项研究的目的是开发一种可以通过廉价的开源BCI(OpenViBE)控制的廉价的3D打印腕外骨骼,并确定采用这种设置进行训练是否可以诱导神经可塑性。十一名健康志愿者想象着从单次试验脑电图(EEG)中检测到的腕部伸展,对此,腕部外骨骼复制了预期的动作。在经颅磁刺激之前,之后和之后,测量经颅磁刺激引起的运动诱发电位(MEP)BCI训练后30分钟。BCI系统的真实阳性率为86±12%,每分钟错误检测为1.20±0.57。与BCI训练之前的测量值相比,MEP在BCI训练后立即增加35±60%,在30分钟后增加67±60%。BCI性能与可塑性的诱导之间没有关联。总之,可以使用开源BCI设置检测假想运动并控制便宜的3D打印外骨骼,当与BCI结合使用时,可以诱导神经可塑性。这些发现可能会促进康复诊所和家庭使用BCI技术的可用性。但是,必须改善可用性,并且需要对中风患者进行进一步测试。每分钟57次错误检测。与BCI训练之前的测量值相比,MEP在BCI训练后立即增加35±60%,在30分钟后增加67±60%。BCI性能与可塑性的诱导之间没有关联。总之,可以使用开源BCI设置检测假想运动并控制便宜的3D打印外骨骼,当与BCI结合使用时,可以诱导神经可塑性。这些发现可能会促进康复诊所和家庭使用BCI技术的可用性。但是,必须改善可用性,并且需要对中风患者进行进一步测试。每分钟57次错误检测。与BCI训练之前的测量值相比,MEP在BCI训练后立即增加35±60%,在30分钟后增加67±60%。BCI性能与可塑性的诱导之间没有关联。总之,可以使用开源BCI设置检测假想运动并控制便宜的3D打印外骨骼,当与BCI结合使用时,可以诱导神经可塑性。这些发现可能会促进康复诊所和家庭使用BCI技术的可用性。但是,必须改善可用性,并且需要对中风患者进行进一步测试。BCI性能与可塑性的诱导之间没有关联。总之,可以使用开源BCI设置检测假想运动并控制便宜的3D打印外骨骼,当与BCI结合使用时,可以诱导神经可塑性。这些发现可能会促进康复诊所和家庭使用BCI技术的可用性。但是,必须改善可用性,并且需要对中风患者进行进一步测试。BCI性能与可塑性的诱导之间没有关联。总之,可以使用开源BCI设置检测假想运动并控制便宜的3D打印外骨骼,当与BCI结合使用时,可以诱导神经可塑性。这些发现可能会促进康复诊所和家庭使用BCI技术的可用性。但是,必须改善可用性,并且需要对中风患者进行进一步测试。
更新日期:2021-01-15
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