具有感觉反馈的仿生假手人机交互研究

仿生假手是一个典型的生机电一体化系统.针对现有假手缺乏感觉反馈的问题,研究了具有双向信息传输能力的生机电一体化假手人机交互系统.采用压力传感器阵列检测肌肉压力分布信号,通过压力分布图的构建,基于主成分分析的特征提取和基于KNN分类器的特征识别方法实现了人手多运动模式的解码.基于假手力传感器,采用电刺激方式实现了假肢接触力向人体的感觉反馈.实验表明,基于肌肉压力分布信号的手部多运动模式识别方法具有较高的正确率,采用具有感觉反馈的交互控制系统可提高假手的抓取能力.     

基于MSP430的肌电假手系统设计

在对人体表面肌电信号研究的基础上,设计出一种肌电假手系统,其中包括肌电信号采集调理系统和假手控制系统。肌电信号经信号调理电路放大、滤波、陷波后,由低功耗的MSP430F149单片机进行A/D转换、特征计算。单片机结合肌电信号与触滑觉传感器反馈的信息来控制电机转向与转速,从而控制假手做出相应动作。通过实际采集的肌电信号在示波器上显示的波形与假手的动作进行对比,说明系统设计是合理有效的。     

基于表面肌电图像的灵巧假手控制系统

设计了一种通过佩戴阵列型表面肌电传感器,实时识别受试者的8种手势,并控制一个自主研发的六自由度灵巧操作假手进行同步动作的人–机协同控制系统.控制假手的手势识别策略基于神经网络算法,受试者仅需在首次训练阶段重复完成预先设定的8种手势动作(分别为放松、手腕外翻、手腕内翻、握拳、伸掌、手势2、手势3和竖大拇指),之后该系统即能够实时识别受试者随机完成8种手势中的任意一种手势.本文提出的网络参数随机搜索算法和梯度下降算法,与目前同规模的神经网络相比提高了网络的训练速度和手势预测精度;该手势识别算法使用Tensorflow机器学习框架学习权值并进行了可视化分析;采用经过优化的手势训练方式既缩短了受试者的手势训练时间,同时提高了手势训练的熟练度.本文对一名肌肉无损伤的受试者进行表面肌电信号采集、训练和预测,对8种手势的综合预测精度达到97%,且再次佩戴时不再需要进行训练.受试者实际控制假手时,使用投票算法对实时手势预测结果进行深度优化,最终假手的动作同步率到达99%.     

基于DSP的多自由度假手电气控制系统的研究

阐述了基于数字信号处理器(DSP)和步进电机的新型仿人型假手的电气控制系统。介绍了假手电气系统构成及其原理,该系统具有结构简单、集成度高的优点。给出了控制系统的硬件实现和软件程序的设计,并通过实验验证了假手的抓取性能。     

一种基于EEG和sEMG的假手控制策略

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.     

仿生假手触滑觉研究

实现人体假手的触滑觉传感器，包括其结构设计、传感信号的采集、处理和感觉信息输出。传感器采用PVDF作为敏感材料，柔顺的传感器表面和小巧的尺寸使之能完全应用于仿生假手的手指上。信号调理电路完成信号的放大、滤波。信号数字处理完成触觉、滑觉信号的分离，并根据特征值的大小判断是否输出相应的感觉信息。     

新型多自由度假手的研制

介绍了一种新型多自由度假手的机械结构、运动方式及其静力学分析．假手的主要结构部件由光敏树 脂制成,使用小型直流伺服电机作为驱动器．手指采用欠驱动及腱驱动方式．该假手具有拟人的外观、较低的整体 重量和对被抓物体外形的适应能力．文章研究了假手的运动特点及接触力规律,通过仿真对假手的接触受力规律进 行了校验．最后通过实验,对假手的运动规律与抓握能力进行了验证．     

智能电刺激仪中肌电反馈功能的设计

为了改善常规电刺激仪缺少主动训练模式导致的疗效不佳,在电刺激仪中引入一种新的肌电反馈方法,在肌电反馈设计中,针对病情不一导致的患者肌电幅值跨度大的特点,设计了自适应增益控制及滤波模块;采用了基于Delta-sigma计算技术的均方根值提取方法,检测患者自发肌电是否达到康复训练的闭值要求;并将均方根值作为反馈量控制刺激脉冲的输出;创新地实现了肌电信号的自适应增益调节、特征值提取及反馈控制.促使患者主动参与训练和治疗;经实验可知:系统已达到预定的功能,实现了康复治疗训练过程的智能化.     

仿生假手抓握力控制策略

为了使仿生假手完成各种精细作业,提出一种抓握力控制策略.在自由空间和约束空间中分别使用基于位置的阻抗控制和力跟踪阻抗控制.在过渡过程中使用模糊观测器切换控制模式.两种控制模式采用同一个基于位置的阻抗控制器,在约束空间向阻抗控制器中引入参考力,以满足约束空间的抓握力控制要求.这种方法可以使关节在自由空间和约束空间中分别实现良好的轨迹跟踪和力矩跟踪,在过渡过程中实现控制模式的可靠切换和系统的稳定过渡.提出一种自适应滑模摩擦力补偿方法,利用终端滑模思想设计了滑模函数,使得系统跟踪误差在有限时间内收敛,避免了传统线性滑模面状态跟踪误差无法在有限时间内收敛至0的问题.根据指数形式摩擦力的特点,利用终端滑模控制思想获得包含摩擦力参数估计的滑模控制律,并基于李亚普诺夫稳定性定理推导了估计参数的在线自适应律.对该抓握力控制策略在HIT假手上进行了抓取实验,实验结果证明了控制策略的有效性.     

再造“指”假手控制系统的研究

本课题基于将脚趾移植到残臂端的再造指技术，采用微处理器技术与模糊控制方法，进行假手控制系统的研究。     

基于FPGA的仿人假手控制系统设计

为了满足生机电一体化仿人假手的控制需求,提出了基于FPGA的仿人假手电气控制系统设计方案。采用模块化设计思想,由FPGA构成的主控芯片模块便于功能拓展与二次开发;由DSP构成的手指运动控制模块、肌电信号采集模块、电刺激模块、USG接口模块和电池管理模块均可独立工作,与主控芯片模块间通过通用接口连接。系统集成度高,可完全放置于假手内部。应用该控制系统在HIT V代手上进行多指抓取实验,实验结果证明其工作效果良好。     

Electromyographic prosthetic hand using grasping-force-magnification mechanism with five independently driven fingers

This paper proposes an electromyographic (EMG) prosthetic hand that has five independently driven fingers, a flexion drive, and a force-magnification drive. The flexion drive allows for rapid finger motion, and the force-magnification drive allows for a firm grasp. To realize the natural feeling of control similar to that of movements with nonamputated parts, the control system includes the impedance model of human forearms and utilizes the muscle contraction level extracted from a user’s EMG signals. We experimentally verified that the maximum fingertip force of the hand exceeds 20 N, and the time required to fully close the hand by the flexion drive is 0.53 s. We also experimentally verified that in response to EMG signals, the fingers can flex smoothly and the grasping force can be modulated. Furthermore, we show that taking EMG signals as inputs makes it possible to control six operations, including ones that use the five fingers in distinctive ways.     

An anthropomorphic controlled hand prosthesis system

Based on HIT/DLR(Harbin Institute of Technology/Deutsches Zentrum für Luft-und Raumfahrt) Prosthetic Hand II,an anthropomorphic controller is developed to help the amputees use and perceive the prosthetic hands more like people with normal physiological hands.The core of the anthropomorphic controller is a hierarchical control system.It is composed of a top controller and a low level controller.The top controller has been designed both to interpret the amputee’s intensions through electromyography(EMG) signals recognition and to provide the subject-prosthesis interface control with electro-cutaneous sensory feedback(ESF),while the low level controller is responsible for grasp stability.The control strategies include the EMG control strategy,EMG and ESF closed loop control strategy,and voice control strategy.Through EMG signal recognition,10 types of hand postures are recognized based on support vector machine(SVM).An anthropomorphic closed loop system is constructed to include the customer,sensory feedback system,EMG control system,and the prosthetic hand,so as to help the amputee perform a more successful EMG grasp.Experimental results suggest that the anthropomorphic controller can be used for multi-posture recognition,and that grasp with ESF is a cognitive dual process with visual and sensory feedback.This process while outperforming the visual feedback process provides the concept of grasp force magnitude during manipulation of objects.     

Effects of auditory,haptic and visual feedback on performing gestures by gaze or by hand

Modern interaction techniques like non-intrusive gestures provide means for interacting with distant displays and smart objects without touching them. We were interested in the effects of feedback modality (auditory, haptic or visual) and its combined effect with input modality on user performance and experience in such interactions. Therefore, we conducted two exploratory experiments where numbers were entered, either by gaze or hand, using gestures composed of four stroke elements (up, down, left and right). In Experiment 1, a simple feedback was given on each stroke during the motor action of gesturing: an audible click, a haptic tap or a visual flash. In Experiment 2, a semantic feedback was given on the final gesture: the executed number was spoken, coded by haptic taps or shown as text. With simultaneous simple feedback in Experiment 1, performance with hand input was slower but more accurate than with gaze input. With semantic feedback in Experiment 2, however, hand input was only slower. Effects of feedback modality were of minor importance; nevertheless, semantic haptic feedback in Experiment 2 showed to be useless at least without extensive training. Error patterns differed between both input modes, but again not dependent on feedback modality. Taken together, the results show that in designing gestural systems, choosing a feedback modality can be given a low priority; it can be chosen according to the task, context and user preferences.     

Development of adaptive locomotion of a caterpillar-like robot based on a sensory feedback CPG model

This paper presents a novel control mechanism for generating adaptive locomotion of a caterpillar-like robot in complex terrain. Inspired by biological findings in studies of the locomotion of the lamprey, we employ sensory feedback integration for online modulation of the control parameters of a new proposed central pattern generator (CPG). This closed-loop control scheme consists of the following stages: First, touch sensor information is processed and transformed into module states. Then, reactive strategies that determine the mapping between module states and sensory inputs are generated according to an analysis of the module states. Finally, by means of a genetic algorithm, adaptive locomotion is achieved by optimising the amount and speed of sensory input that is fed back to the CPG model. Incorporating the closed-loop controller in a caterpillar-like robot, both simulation and real on-site experiments are carried out. The results confirm the effectiveness of the control system, based on which the robot flexibly adapts to, and manages to crawl across the complex terrain.     

The relationships between hand coupling force and vibration biodynamic responses of the hand-arm system

This study conducted two series of experiments to investigate the relationships between hand coupling force and biodynamic responses of the hand–arm system. In the first experiment, the vibration transmissibility on the system was measured as a continuous function of grip force while the hand was subjected to discrete sinusoidal excitations. In the second experiment, the biodynamic responses of the system subjected to a broadband random vibration were measured under five levels of grip forces and a combination of grip and push forces. This study found that the transmissibility at each given frequency increased with the increase in the grip force before reaching a maximum level. The transmissibility then tended to plateau or decrease when the grip force was further increased. This threshold force increased with an increase in the vibration frequency. These relationships remained the same for both types of vibrations. The implications of the experimental results are discussed.

Practitioner Summary: Shocks and vibrations transmitted to the hand–arm system may cause injuries and disorders of the system. How to take hand coupling force into account in the risk assessment of vibration exposure remains an important issue for further studies. This study is designed and conducted to help resolve this issue.