关键词] 脑电；脑机接口；义肢手；电机驱动 [gap=710]Key words: EEG; brain-computer interface; prosthesis hand; motor driving
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It was applied in the control system of prosthesis hand, the detected signal was recognized by neural network, 6 action patterns can be classified, the success rate is above 95%.
将其应用于假肢手的控制系统中，通过神经网络进行动作模式识别，共识别了6个手部动作模式，识别成功率在95%以上。
On the other hand, the intelligence of the lower limb prosthesis is mainly demonstrated on the controlling of moment of knee Jo int and the in time responsibility to the outside impacts.
下肢假肢的智能主要体现在膝关节力矩控制和对外界冲击及时反应等能力。
Conclusion This system implemented anterior prosthesis CAD automatically and provided characteristic color design by hand.
结论实现了修复体颜色的计算机自动匹配和手动个性化设计。
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