赵丽娜, 刘作军, 苟斌, 杨鹏. 基于隐马尔可夫模型的动力型下肢假肢步态预识别[J]. 机器人, 2014, 36(3): 337-341. DOI: 10.3724/SP.J.1218.2014.00337
引用本文: 赵丽娜, 刘作军, 苟斌, 杨鹏. 基于隐马尔可夫模型的动力型下肢假肢步态预识别[J]. 机器人, 2014, 36(3): 337-341. DOI: 10.3724/SP.J.1218.2014.00337
ZHAO Lina, LIU Zuojun, GOU Bin, YANG Peng. Gait Pre-recognition of Dynamic Lower Limb Prosthesis Based on Hidden Markov Model[J]. ROBOT, 2014, 36(3): 337-341. DOI: 10.3724/SP.J.1218.2014.00337
Citation: ZHAO Lina, LIU Zuojun, GOU Bin, YANG Peng. Gait Pre-recognition of Dynamic Lower Limb Prosthesis Based on Hidden Markov Model[J]. ROBOT, 2014, 36(3): 337-341. DOI: 10.3724/SP.J.1218.2014.00337

基于隐马尔可夫模型的动力型下肢假肢步态预识别

Gait Pre-recognition of Dynamic Lower Limb Prosthesis Based on Hidden Markov Model

  • 摘要: 为使动力型假肢膝关节协调配合人体的运动,关键是对人体行走步态进行有效预识别.本文利用安装在假肢接受腔上的加速度传感器和安装在足底的压力传感器采集人体的运动信息,根据人体运动的规律性和重复性特点,通过将隐马尔可夫模型引入到所获得的运动信息中来分析并预识别人体的运动步态.实验表明,基于隐马尔可夫模型的动力型下肢假肢的步态预识别方法是有效并且准确的.

     

    Abstract: Effective pre-recognition of human gait is one of the key points to make the dynamic prosthetic knee joint coordinate with the body movement. Acceleration sensor installed in the prosthetic socket and pressure sensor installed in the plantar are used to acquire body's motion information. According to regularity and repeatability characteristics, hidden Markov model is adopted to analyze the acquired motion information and performing gait pre-recognition. The experiments show that the gait pre-recognition of dynamic lower prosthesis based on hidden Markov model is effective and accurate.

     

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