摘要
提出了一种融合单、多关节及日常生活功能行动作训练的5自由度外骨骼式偏瘫上肢康复机器人系统.根据偏瘫患者上肢单侧受损的特点,提取偏瘫患者的健侧肢体运动的表面肌电信号用于驱动康复机器人辅助患者患侧肢体实现康复训练动作.采用肌电绝对值积分和自回归参数模型法对上肢运动中参与动作的4块肌肉产生的sEMG信号分别进行特征提取,并分别作为基于Levenberg-Marquardt算法的反向传播神经网络的输入,6个上肢运动作为输出建立表面肌电信号与上肢康复动作之间的关系.试验结果表明该方法利用sEMG准确地完成了对上肢康复动作的识别.该方法有利于提高中枢神经系统紧张度,促进血液循环,在康复的同时防止并发症的产生,更有利于提高患者运动积极性,保持患者正确运动的感觉.
plex motions and provide ADL training for hemiplegic patients, is presented. In general, hemiplegic patients are unilaterally impaired, so the surface electromyogram（sEMG） signal in the healthy limbs can be extracted to drive the rehabilitation robot lo assist patients＇ impaired limb to carry out rehabilitation exercises. Herein two methods were involved. IAV and AR were used to extract features of sEMG acquired from four upper limb muscles which contribute to focused activities of that upper limb. The extracted features were used as the input to a back propagation neural network （BPN） in the Levenberg-Marquardt （LM） algorithm, then a relationship was formulated between sMEG and the rehablilitation motion upper limb rehabilitation exercise motions as outputs. Experiments prove the effectiveness of this which is useful for patient to train the nervous system, improve blood circulation and keep a sense er motion and improve range of motion. with six method,
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2007年第9期1008-1013,共6页
Journal of Harbin Engineering University
基金
国家自然科学基金资助项目(60505016)
黑龙江省科技攻关资助项目(GB04A502-2)
哈尔滨市青年科学基金资助项目(2004AFQXJ017)
