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摘要: 针对残臂较短或残臂上肌电信号测量点较少的残疾人使用多自由度假手的需求，提出一种基于脑电信号（Electroencephalogram，EEG）和表面肌电信号（Surface electromyogram signal，sEMG）协同处理的假手控制策略.该方法仅用1个肌电传感器和1个脑电传感器实现多自由度假手的控制.采用1个脑电传感器测量人体前额部位的EEG，从测量得到的EEG中提取出眨眼动作信息并将其用于假手动作的编码；采用1个肌电传感器测量手臂上的sEMG，并针对肌电信号存在个体差异和位置差异的问题，采用自适应方法实现手部动作强度的估计；采用振动触觉技术设计触觉编码用于将当前假手的控制指令反馈给佩戴者，从而实现EEG和sEMG对多自由度假手的协同控制.为验证该控制策略的有效性进行了实验研究，结果表明，提出的假手控制策略是有效的.Abstract: A control strategy based on electroencephalogram (EEG) and surface electromyogram signal (sEMG) is proposed to meet the demand of using multiple degrees of freedom (DOF) prosthetic hand for the upper limb amputee whose remnant arm is too short to place enough sEMG sensors. In this paper, one EEG sensor and one sEMG sensor are adopted to realize the control of the multiple DOF prosthetic hand. A portable EEG measurement instrument, MindWave, is employed to capture the EEG of the user's forehead. The blink information extracted from the EEG is used to code the actions of the prosthetic hand. An sEMG sensor is employed to capture the sEMG on the user's surface skin. The captured sEMG is used to estimate the severity of the action including grasp force, opening and closing speeds, rotational speed of the wrist. An adaptive method is also proposed to reduce the influence on the sEMG caused by the individual differences. A tactile feedback device is designed to realize the EEG and sEMG coordinating control of the prosthetic hand. Experiments are implemented to verify the validity of the proposed control strategy and the results show that the proposed control strategy is effective.
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Key words:
- Prosthetic hand /
- motion coding /
- coordinated control /
- tactile feedback
1) 本文责任编委 程龙 -
图 5 同一块肌肉不同位置测量得到的两路肌电信号
Fig. 5 Two channels of sEMG captured from different locations of the same muscle
图 10 EEG和sEMG协同控制流程图
Fig. 10 Flow chart of the coordinated control based on EEG and sEMG
图 15 对手爪闭合动作进行眨眼编码时测量得到的EEG
Fig. 15 EEG captured in the process of blink coding of the hand closing
表 1 单位时间内眨眼次数与假手动作类型的关系
Table 1 The relationship between the blink times and the motion type of the prosthetic hand
第一环节眨眼次数 第二环节眨眼次数 动作类型 2 2 手爪张开 3 手爪闭合 3 2 手腕顺时针转动 3 手腕逆时针转动 
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表 2 手部动作识别结果
Table 2 Results of the hand motion recognition experiments
受试者编号 性别 动作编码正确率（%) 手爪张开 手爪闭合 顺时针旋转 逆时针旋转 平均正确率 1 女 96 100 100 96 98 2 女 96 92 96 92 94 3 女 92 96 96 96 95 4 女 96 92 92 96 94 5 女 92 100 96 100 97 6 男 96 96 92 100 96 7 男 92 96 96 96 95 8 男 92 92 96 96 94 9 男 96 100 92 92 95 10 男 92 88 92 96 92
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表 3 触觉感知实验结果
Table 3 Results of the tactile perception experiments
受试者编号 性别 动作编码正确率（%) 手爪动作 手腕动作 手爪张开 手爪闭合 顺时针旋转 逆时针旋转 平均正确率 1 女 100 100 100 100 100 100 100 2 女 100 100 100 100 100 100 100 3 女 100 100 100 100 95 95 98.33 4 女 100 100 100 100 100 100 100 5 女 100 100 100 100 95 100 99.17 6 男 100 100 100 100 100 95 99.17 7 男 100 100 100 100 100 95 99.17 8 男 100 100 100 100 100 100 100 9 男 100 100 100 95 95 100 98.33 10 男 100 100 95 100 95 95 97.5
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表 4 砝码抓取实验结果
Table 4 Results of the grasping weights
受试者编号 性别 成功率（%) 1 女 95 2 女 95 3 女 90 4 女 100 5 女 95 6 男 90 7 男 100 8 男 95 9 男 95 10 男 100
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表 5 纸杯取实验结果
Table 5 Results of the grasping paper cups
受试者编号 性别 成功率（%) 1 女 95 2 女 95 3 女 90 4 女 100 5 女 95 6 男 90 7 男 100 8 男 95 9 男 95 10 男 100
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