CN111300413B - 一种多自由度肌电假手控制系统及其使用方法 - Google Patents

一种多自由度肌电假手控制系统及其使用方法 Download PDF

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CN111300413B
CN111300413B CN202010139635.5A CN202010139635A CN111300413B CN 111300413 B CN111300413 B CN 111300413B CN 202010139635 A CN202010139635 A CN 202010139635A CN 111300413 B CN111300413 B CN 111300413B
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myoelectric
freedom
circuit board
wrist
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CN111300413A (zh
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宋爱国
胡旭晖
卫智恺
李会军
徐宝国
曾洪
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Southeast University
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Abstract

本发明公开了一种多自由度肌电假手控制系统及其使用方法，该系统包括机械手、机械手腕、残肢接受腔和数据处理器，机械手和残肢接受腔分别安装在机械手腕两端，残肢接受腔内连接有多通道肌电阵列电极袖套、控制单元电路板和电池，控制单元电路板另一端连接机械手和机械手腕，该系统的使用方法包括以下步骤：(S1)令使用者戴上多通道肌电阵列电极袖套，连接好电池和控制单元电路板；(S2)令使用者完成手势，采集表面肌电信号后上传至数据处理器；(S3)数据处理器接收表面肌电信号并输入神经网络算法生成手势预测模型；(S4)使用者控制机械手腕、机械手的多个自由度运动。该系统能够对连续手势及手势力度进行识别，做出多自由度的手势。

Description

一种多自由度肌电假手控制系统及其使用方法
技术领域
本发明涉及一种假手控制系统及其使用方法，更具体地，涉及一种多自由度肌电假手控制系统及其使用方法。
背景技术
人工假肢的研究可以应用到高端医疗装备、生机电一体化智能机器人、危险环境勘查、灾难救援装备、国防装备以及辅助残疾人进行康复工程训练等多个领域，其科学技术成果可辐射，因此具有重要的战略意义，到目前为止，基于单自由度的仿人型机器人手部结构已经十分成热但单自由度并不能不满足仿真假手的灵活度需求，且不存在能够同步识别假手手势和手势力度的算法，使得假手的应用受到了限制。
发明内容
发明目的：本发明的目的是提供一种能够同步识别手势及其力度，并进行多自由度控制的多自由度肌电假手控制系统，本发明的另一目的是提供该系统的使用方法。
技术方案：本发明所述的多自由度肌电假手控制系统包括机械手、机械手腕、残肢接受腔和数据处理器，机械手和残肢接受腔分别安装在机械手腕两端，残肢接受腔内连接有多通道肌电阵列电极袖套，多通道肌电阵列电极袖套连接有控制单元电路板和电池，控制单元电路板另一端连接机械手和机械手腕。数据处理器向控制单元电路板发出采集表面肌电信号的指令，使多通道肌电阵列电极袖套采集表面肌电信号，并通过接收的数据进行神经网络处理，生成手势预测模型。
其中，机械手腕包括锥齿轮组机构、皮带轮传动机构、伺服电机和手腕支撑框，锥齿轮组机构采用四个锥齿轮相互啮合，构成十字型排布，左、右两个锥齿轮安装在手腕支撑框架上，并分别连接有传动轮，皮带轮传动机构连接在传动轮上，并连接有伺服电机；锥齿轮组机构中水平方向的两个齿轮为太阳轮，太阳轮通过主动轴与传动轮相连，太阳轮通过太阳轮顶丝固定在主动轴上，传动轮通过传动轴顶丝固定在主动轴上，垂直方向上部为连接机械手的第一行星齿轮，下部为第二行星齿轮，第一行星齿轮和第二行星齿轮之间穿过一空心被动轴，空心被动轴与第一行星齿轮和第二行星齿轮之间安装有深沟轴承，手腕支撑框架由左面板、右面板、梁和底板构成，左面板、右面板上端通过梁连接，下端与底板固定连接，伺服电机安装在左、右面板上，伺服电机皮带轮与传动轮通过皮带套接，皮带外侧固定一压轮。
本发明所述的多自由度肌电假手控制系统的使用方法包括以下步骤：
(S1)令使用者戴上多通道肌电阵列电极袖套，然后连接好控制单元电路板、电池；
(S2)令使用者根据实验动作序列完成手势，数据处理器向控制单元电路板发出采集表面肌电信号的指令，控制单元电路板控制多通道肌电阵列电极袖套采集表面肌电信号后储存至控制单元电路板并上传至数据处理器；
(S3)数据处理器接收表面肌电信号并输入神经网络算法生成手势预测模型；
(S4)使用者穿戴上残肢接受腔，并连接好机械手和机械手腕，利用生成的手势预测模型进行实时手势识别，控制单元电路板控制手腕、机械手的多个自由度运动。
其中，步骤S3中神经网络算法对数据处理包括以下步骤：
(S31)对原始表面肌电信号进行预处理以提取肌肉激活信号，然后用固定长度的时间窗口分割并作为无监督神经网络的输入层，网络的第一个隐藏层利用主成分分析方法压缩时间-空间特征；
(S32)第二个隐藏层采用自编码器学习2N个前臂肌肉完成不同手势时相互协同的肌肉信号特征，根据肌肉协同特征和实验动作序列生成连续手势标签，其中2N表示要识别的2N个手势自由度，N为参与手势运动的前臂肌肉中互为拮抗肌肉的个数；
(S33)第三个隐藏层将肌肉协同特征与连续手势标签进行拟合，生成回归网络，回归网络的输出层包含N个神经元，分别输出N对拮抗肌表现出的连续运动学与动力学数据，其中不同神经元表示不同的手势，神经元输出的连续数据表示该手势的力度。
有益效果：本发明与现有技术相比，其显著优点是：1、能够对连续手势进行识别，并对手势力度进行识别；2、能够做出多自由度的手势，假手更加灵巧。
附图说明
图1是本发明假手安装示意图；
图2是手腕结构示意图；
图3是锥齿轮组机构结构示意图；
图4是手腕支撑框架结构示意图；
图5是手腕结构侧视图；
图6是分层神经网络框图；
图7是手势识别算法第二隐层自编码器框图；
图8是标签自生成方法示意图；
图9是手势识别算法流程图；
图10是神经网络流程图。
具体实施方式
如图1～图5所示，多自由度肌电假手控制系统，其特征在于，包括机械手、机械手腕2、残肢接受腔1和数据处理器3，机械手和残肢接受腔分别安装在机械手腕两端，残肢接受腔内连接有多通道肌电阵列电极袖套，多通道肌电阵列电极袖套连接有控制单元电路板和电池，控制单元电路板另一端连接机械手和机械手腕。数据处理器3向控制单元电路板发出采集表面肌电信号的指令，使多通道肌电阵列电极袖套采集表面肌电信号，并通过接收的数据进行神经网络处理，生成手势预测模型。
机械手腕2包括锥齿轮组机构4、皮带轮传动机构5、伺服电机7和手腕支撑框架6，锥齿轮组机构4采用四个锥齿轮相互啮合，构成十字型排布，水平方向的两个齿轮为太阳轮15，安装在手腕支撑框架6上，太阳轮15通过主动轴9与传动轮10相连，太阳轮15通过太阳轮顶丝12固定在主动轴9上，传动轮10通过传动轴顶丝11固定在主动轴9上，垂直方向上部为连接机械手的第一行星齿轮14，下部为第二行星齿轮13，第一行星齿轮14和第二行星齿轮13之间穿过一空心被动轴8。空心被动轴8与第一行星齿轮14和第二行星齿轮13之间安装有深沟轴承。手腕支撑框架6由左面板、右面板、梁16和底板17构成，左面板、右面板上端通过梁16连接，下端与底板固定连接，所述伺服电机7安装在左、右面板上，伺服电机皮带轮19与传动轮10通过皮带18套接。皮带18外侧固定一压轮20。
手势识别算法流程如图9所示，使用时，先将控制单元电路板、电池与多通道肌电阵列电极袖套相连，令使用者穿戴上多通道肌电阵列电极袖套，令使用者依次完成手腕外翻，手腕外旋、手张开、手腕内翻、手腕内旋、手握拳共计六个动作，由腕翻、腕旋、手开合三个自由度的动作组成，每个动作从开始到结束持续3秒，之后手处于放松状态并持续3秒，每种手势需连续完成3次再做下一个手势，当所有手势都做完后视为一轮采集结束，同一对象需要采集三轮数据，多通道肌电阵列电极袖套采集肌电信号后储存至控制单元电路板并上传至数据处理器3，输入神经网络算法进行处理，处理流程如图10所示。肌电数据收集完成后，训练集被分层神经网络的三层网络加工，如图6所示，首先对8个通道的原始肌电信号进行预处理，采用均方根RMS均值来获得激活信号，然后，这8个激活信号被固定长度的时间窗口分割并作为神经网络的输入层，每个输入样本将包含阵列肌电信号的空间和时间信息，网络的第一个隐藏层利用主成分分析方法来降低输入信号的维度，第二个隐藏层采用自编码器学习六个肌肉协同特征以进一步降低特征维度，第三个隐藏层将肌肉协同特征与自动生成的运动意图标签进行拟合，最终网络的输出层包含三个神经元，分别输出三个自由度的连续运动数据，各个神经网络隐藏层的权值矩阵是独立训练再堆叠在一起，在实际拟合深度神经网络过程中进行逐层精调，其中预测出的手腕运动信息用于控制机械手腕2，手开合运动信息用于控制安装于机械手腕2上的机械手。
设图6中的时间窗内包含T个样本点，阵列肌电传感器的个数为c，则网络输入层神经元的个数为c×T。为了从冗余信息中获取有代表性的时间和空间信息，本发明对每个通道的肌电激活信号进行时间尺度上的主成分分析，将时间窗内的T个肌电激活信号采样点为代入主成分分析的特征，以滑动窗口的形式生成样本，设滑动步长为1，单个通道表面肌电信号的采样点数为m，则生成样本数为m-T+1，图中描述了每个肌电信号通道选取两个主成分来表征该时间窗内的数据。
图7表示图6中第二隐层从8个通道的主成分特征中提取2N种肌肉协同特征的过程，2N表示要识别的2N个手势自由度，N为参与手势运动的前臂肌肉中，互为拮抗肌肉的个数，经过第一层网络的加工后，继续输入神经网络的神经元个数由c×T降为c×2，进一步的，第二层神经元用于提取肌肉协同相关的特征，本实施例中从肌电激活特征中提取6种肌肉协同特征，分别对应手腕外翻、手腕内翻、顺时针腕旋、逆时针腕旋、手打开和手握拳，且肌肉协同特征值均为非负值，第二层神经元的权值矩阵通过训练一个自编码器得到。自编码器的主要特征在于输入神经元与输出神经元完全一致，且隐藏层神经元个数小于输入输出神经元个数，该神经网络结构可以获得输入数据中某些潜在的特征。从网络的输入层到隐藏层称为编码过程，从隐藏层到输出层称为解码过程，文本使用自编码器完成训练后的编码部分作为第二层网络的权值矩阵。为了使隐层神经元均为非负值，编码过程的激活函数使用Relu函数，由于输入层包含数值为负的特征，为了使输出层也能复原出负值特征，解码过程的激活函数使用Tanh函数。自编码器的损失函数使用交叉熵cross entropy函数；编码器的权值矩阵使用Xavier法进行初始化，该方法能够使初始权值呈均值为0的正态分布；迭代训练过程中使用剪枝算法减小过拟合情况，网络学习率随迭代次数指数衰减、并采用ADAM梯度下降法和Mini-Batch法加快训练速度，与非负矩阵因式分解方法相比，该方法拟合出的模型由于经过了非线性激活函数的运算，因此具有更好的逼近效果。
图8表示从图7中得到的肌肉协同特征中提取运动学和动力学标签的过程，自编码器学习到的肌肉协同特征虽然不能直接得到期望的运动意图，但当6个协同特征经过矢量叠加运算后，将得到图8中所示的震荡波形图，其中每一个波峰表示完成某一动作时肌肉协同程度达到的最大值，两侧的波谷表示肌肉协同处于静息状态，因此一个完整的波谷-波峰-波谷段表示某手势完成至最强肌肉激活程度再到静息恢复的过程，通过搜索波峰和波谷位置可以重构出手部、腕部共三个自由度的运动学参数标签。在得到标签数据后，最后将上一层网络计算得到的肌肉协同特征和标签数据代入一个前馈神经网络进行回归拟合。得到的网络层再与是前两节计算得到的网络层进行堆叠，即形成了最终的深层回归模型，所有网络层训练完成并堆叠起来形成最终的手势识别网络并反馈给控制单元电路板。实际使用是，令使用者穿戴上残肢接受腔1，并连接好机械手和机械手腕2，使用者通过想象手势动作来控制假肢手的腕部和手部动作，控制单元电路板同时控制假肢的机械手腕2、机械手的多个自由度运动，机械手运动的速度由分层网络预测的肌肉力调控。

Claims (6)

1.一种多自由度肌电假手控制系统的使用方法，该假手控制系统包括机械手、机械手腕(2)、残肢接受腔(1)和数据处理器(3)，所述机械手和残肢接受腔分别安装在机械手腕两端，所述残肢接受腔内连接有多通道肌电阵列电极袖套，所述多通道肌电阵列电极袖套连接有控制单元电路板和电池，所述控制单元电路板另一端连接机械手和机械手腕，所述数据处理器向控制单元电路板发出采集表面肌电信号的指令使多通道肌电阵列电极袖套采集表面肌电信号并接受数据进行处理生成手势预测模型，其特征在于，该使用方法包括以下步骤：
(S1)令使用者戴上多通道肌电阵列电极袖套，然后连接好控制单元电路板、电池；
(S2)令使用者根据实验动作序列完成手势，数据处理器(3)向控制单元电路板发出采集表面肌电信号的指令，控制单元电路板控制多通道肌电阵列电极袖套采集表面肌电信号后储存至控制单元电路板并上传至数据处理器(3)；
(S3)数据处理器(3)接收表而肌电信号并输入神经网络算法生成手势预测模型；其中神经网络算法对数据处理包括以下步骤：
(S31)对原始表面肌电信号进行预处理以提取肌肉激活信号，然后用固定长度的时间窗口分割并作为无监督神经网络的输入层，网络的第一个隐藏层利用主成分分析方法压缩时间-空间特征；
(S32)第二个隐藏层采用自编码器学习2N个前臂肌肉完成不同手势时相互协同的肌肉信号特征，根据肌肉协同特征和实验动作序列生成连续手势标签，其中2N表示要识别的2N个手势自由度，N为参与手势运动的前臂肌肉中互为拮抗肌肉的个数；
(S33)第三个隐藏层将肌肉协同特征与连续手势标签进行拟合，生成回归网络，回归网络的输出层包含N个神经元，分别输出N对拮抗肌表现出的连续运动学与动力学数据，其中不同神经元表示不同的手势，神经元输出的连续数据表示该手势的力度；
(S4)使用者穿戴上残肢接受腔，并连接好机械手和机械手腕，利用生成的手势预测模型进行实时手势识别，控制单元电路板控制手腕、机械手的多个自由度运动。
2.根据权利要求1所述的多自由度肌电假手控制系统的使用方法，其特征在于，所述机械手腕(2)包括锥齿轮组机构(4)、皮带轮传动机构(5)、伺服电机(7)和手腕支撑框架(6)，所述锥齿轮组机构(4)采用四个锥齿轮相互啮合，构成十字型排布，左、右两个锥齿轮安装在手腕支撑框架(6)上，并分别连接有传动轮(10)，所述皮带轮传动机构(5)连接在传动轮(10)上，并连接有伺服电机(7)。
3.根据权利要求2所述的多自由度肌电假手控制系统的使用方法，其特征在于，所述锥齿轮组机构(4)中水平方向的两个齿轮为太阳轮(15)，太阳轮(15)通过主动轴(9)与传动轮(10)相连，太阳轮(15)通过太阳轮顶丝(12)固定在主动轴(9)上，传动轮(10)通过传动轴顶丝(11)固定在主动轴(9)上，垂直方向上部为连接机械手的第一行星齿轮(14)，下部为第二行星齿轮(13)，所述第一行星齿轮(14)和第二行星齿轮(13)之间穿过一空心被动轴(8)。
4.根据权利要求3所述的多自由度肌电假手控制系统的使用方法，其特征在于，所述空心被动轴(8)与第一行星齿轮(14)和第二行星齿轮(13)之间安装有深沟轴承。
5.根据权利要求2所述的多自由度肌电假手控制系统的使用方法，其特征在于，所述手腕支撑框架(6)由左面板、右而板、梁(16)和底板(17)构成，所述左面板、右面板上端通过梁(16)连接，下端与底板固定连接，所述伺服电机(7)安装在左、右面板上，伺服电机皮带轮(19)与传动轮(10)通过皮带(18)套接。
6.根据权利要求5所述的多自由度肌电假手控制系统的使用方法，其特征在于，所述皮带(18)外侧固定一压轮(20)。
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