日本大阪大學研究人員日前在美國《神經(jīng)學年鑒》（Annals of Neurology）期刊網(wǎng)絡版上發(fā)表論文說,，他們利用安裝在運動麻痹患者腦部表面的電極，成功讀取患者的腦電波,，推測出其意圖,，從而使作為假肢的機器人動了起來。這一成果有望促進開發(fā)出幫助相關疾病患者運動和表達意圖的裝置,。
研究人員為12名年齡在13歲至66歲的運動麻痹患者腦部表面安裝電極,，這些患者的運動麻痹癥狀各不相同。研究人員利用電腦分析患者希望動手和動胳膊時腦電波的特征,，然后讓電腦“記住”這些特征,，推測患者運動意圖，結果準確率可達60%至90%,。
例如,，對于半身不遂患者，電腦能夠高效解讀患者的腦電波,，準確推測出患者希望做出的動作,，將分析結果輸入作為假肢的機器人，機器人能實時實現(xiàn)彎曲肘部,、抓東西等符合患者意圖的動作,。
研究人員下一步將擴大研究對象范圍，爭取將這項技術早日實用化,，以幫助患者提高生活質量,。（生物谷 Bioon.com）
doi:10.1002/ana.22613
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Electrocorticographic control of a prosthetic arm in paralyzed patients
Yanagisawa, Takufumi; Hirata, Masayuki; Saitoh, Youichi; Kishima, Haruhiko; Matsushita, Kojiro; Goto, Tetsu; Fukuma, Ryohei; Yokoi, Hiroshi; Kamitani, Yukiyasu; Yoshimine, Toshiki
Objective: Paralyzed patients may benefit from restoration of movement afforded by prosthetics controlled by electrocorticography (ECoG). Although ECoG shows promising results in human volunteers, it is unclear whether ECoG signals recorded from chronically paralyzed patients provide sufficient motor information, and if they do, whether they can be applied to control a prosthetic. Methods: We recorded ECoG signals from sensorimotor cortices of 12 patients while they executed or attempted to execute 3 to 5 simple hand and elbow movements. Sensorimotor function was severely impaired in 3 patients due to peripheral nervous system lesion or amputation, moderately impaired due to central nervous system lesions sparing the cortex in 4 patients, and normal in 5 patients. Time frequency and decoding analyses were performed with the patients' ECoG signals. Results: In all patients, the high gamma power (80–150Hz) of the ECoG signals during movements was clearly responsive to movement types and provided the best information for classifying different movement types. The classification performance was significantly better than chance in all patients, although differences between ECoG power modulations during different movement types were significantly less in patients with severely impaired motor function. In the impaired patients, cortical representations tended to overlap each other. Finally, using the classification method in real time, a moderately impaired patient and 3 nonparalyzed patients successfully controlled a prosthetic arm
