Hasegawa Ryohei P
Human Technology Research Institute, National Institute of Advanced Industrial Science and Technolo (AIST).
Rinsho Shinkeigaku. 2013;53(11):1402-4. doi: 10.5692/clinicalneurol.53.1402.
A cognitive brain-machine interface (BMI), "neurocommunicator" has been developed by the author's research group in AIST in order to support communication of patients with severer motor deficits. The system can identify candidate messages (pictograms) in real time from electroencephalography (EEG) data, combining three core technologies; 1) a portable/wireless EEG recorder; 2) a high-speed and high-accuracy decoding algorithm; and 3) a hierarchical message generation system. The accuracy of the model at single predictions of the target was generally over 95%, corresponding to about 32 bits per minute for normal subjects. Monitor experiments have been also started for patients at their home, in which further technical improvements are required.
作者所在的日本产业技术综合研究所（AIST）的研究团队开发了一种认知脑机接口（BMI）“神经通信器”，以支持运动功能严重受损患者的交流。该系统结合了三项核心技术，能够从脑电图（EEG）数据中实时识别候选消息（象形图）；1）便携式/无线EEG记录器；2）高速高精度解码算法；3）分层消息生成系统。该模型对目标的单次预测准确率通常超过95%，正常受试者每分钟约为32比特。针对患者在家中的监测实验也已启动，不过还需要进一步的技术改进。
