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Differentiated Time-Frequency Characteristics Based Real-Time Motion Decoding for Lower Extremity Rehabilitation Exoskeleton Robot

机译:基于差异化的时频特性基于基于下肢康复外骨骼机器人的实时运动解码

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Decode the human motion intension precisely in real time is the key problem in coordinated control of the lower extremity exoskeleton. In this research, the relationship between frequency characteristics of sEMG (surface electromyographic) and muscle contraction is established in real time according to the biomechanism of skeletal muscle; DPSE (Differentiated Power Spectrum Estimation) method is applied to extract frequency characteristics from sEMG precisely and quickly; offset compensation is added to prevent noise disturbance during feature extracting of the sEMG with lower SNR (signal-to-noise ratio). Corresponding experiments on knee joint are conducted by prototype exoskeleton robot. EMGBFT (EMG Biofeedback therapy) based on force and haptic is applied as information feedback. Results show the human-machine interface can decode human motion intension and assist or resist movement of the wearer in real-time.
机译:实时地解码人体运动内容是对下肢外骨骼的协调控制中的关键问题。在本研究中,根据骨骼肌的生物机制,在SEMG(表面电谱)和肌肉收缩之间的频率特性与肌肉收缩的关系; DPSE(差异化功率谱估计)方法应用于精确快速地从SEMG提取频率特性;添加偏移补偿以防止具有较低SNR(信噪比)的SEMG的特征提取期间的噪声干扰。膝关节的相应实验由原型外骨骼机器人进行。基于力和触觉的EMGBFT(EMG生物反馈疗法)作为信息反馈应用。结果显示人机界面可以在人体运动内涵解码人体运动内涵并实时辅助或抵抗佩戴者的运动。

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