基于交互力模糊识别的上肢康复机器人模式调整控制策略研究

在上肢康复机器人辅助训练过程中,对于软瘫期脑卒中患者通常采用被动训练策略。为了激发患者的主动康复意愿,对于逐渐具备主动发力能力的患者,康复治疗师会采用机器人助动训练策略。本文针对末端牵引式上肢康复机器人,提出一种基于交互力模糊判别的人体上肢运动功能评估方法以及按需辅助的人机交互控制策略。首先设计了基于计算力矩控制器的被动训练和结合势能场的助动训练模式,然后将训练过程中三维力传感器采集的交互力信息引入至模糊推理系统中,提出了主动参与度σ,并设计相应的辅助策略算法实现两种训练模式的自适应调整。最后通过试验证明了主动参与度σ与表面肌电信号之间的相关性。并且,相较于仅通过交互力大小进行模式调整的控制策略,该方法具有更快的响应速度,使机器人在训练过程中更具安全性。     

脑卒中患者上肢康复机器人及评价方法综述

利用机器人技术进行上肢康复训练是脑卒中患者进行康复治疗的重要手段之一。本文根据中枢神经系统具有高度的可塑性,分析了机器人辅助康复训练的理论依据。并且依据康复机器人的社会需求和研究意义,归纳总结了5种上肢康复机器人的研究进展和研究成果,其中包括上肢康复机器人、功能性电刺激辅助上肢康复机器人、基于虚拟现实技术的上肢康复机器人、基于sEMG的上肢康复训练机器人、基于BCI上肢康复训练机器人。为完善康复机器人的功能,实现对脑卒中患者上肢运动功能的量化评估,本文还分析了目前临床上常用的几种评价方法,即Brunnstrom等级评价法、Fugl?Meyer量表评价法、上田敏评价法和Bobath评价法。最后分析了上肢康复机器人在机械设计、控制策略和评价方法等方面的发展趋势。     

基于PCI-1240运动控制卡的肢体康复训练控制系统的实现与软件设计EI北大核心CSCD

本研究开发了一种基于坐姿的下肢康复运动控制系统,该系统包括下肢外骨骼机构、电机驱动控制电路、运动控制程序等。通过6个电机为髋、膝、踝关节转动提供动力,采用PCI-1240运动控制卡作为控制核心,实现了下肢各关节重复性转动训练和步态康复训练的速度、角度和运动时间的精确控制和调节。本文试验结果表明,该运动控制系统能很好地满足下肢功能障碍患者重复性康复训练运动的需求。本文为康复训练机器人中运动控制系统提供了更多的方法数据,可促进工业自动化设备向医疗领域转变,有利于康复机器人的更进一步研究。     

基于PCI-1240运动控制卡的肢体康复训练控制系统的实现与软件设计

本研究开发了一种基于坐姿的下肢康复运动控制系统,该系统包括下肢外骨骼机构、电机驱动控制电路、运动控制程序等。通过6个电机为髋、膝、踝关节转动提供动力,采用PCI-1240运动控制卡作为控制核心,实现了下肢各关节重复性转动训练和步态康复训练的速度、角度和运动时间的精确控制和调节。本文试验结果表明,该运动控制系统能很好地满足下肢功能障碍患者重复性康复训练运动的需求。本文为康复训练机器人中运动控制系统提供了更多的方法数据,可促进工业自动化设备向医疗领域转变,有利于康复机器人的更进一步研究。     

融合功能性电刺激的助行康复外骨骼机器人混合控制策略研究进展

运动康复有助于促进脊柱损伤的恢复或脑卒中患者神经可塑,这对患者受损运动功能的恢复有着非常重要的作用。近年来,功能性电刺激(FES)技术与外骨骼机器人的结合,发挥了这两种康复技术的优势,同时互补了各自缺陷,从而促进实现了更有效的康复辅助模式,目前已逐渐成为本领域的研究热点。综述融合FES与下肢康复机器人混合控制策略的研究现状,并分别就FES结合被动矫形器的单向控制方法和融合主动外骨骼的协同控制方法,剖析其相关技术与难点;讨论构建人机信息交互环路的关键问题,以及如何设计出合理高效混合控制策略,从而实现动态控制分配和患者最大程度主动参与康复训练的目标。对未来的混合康复技术发展方向进行了总结与展望。     

一种组合式远程康复训练机器人的研制:适用性及其安全性

背景:国内对康复机器人的研究起步比较晚,辅助型康复机器人的研究相对较多,而康复训练机器人的研究相对较少,医工跨学科的结合有待加强,国内的康复器械远远不能满足市场对智能化、人机工程化的康复机器人的需求。目的:针对国内康复专家少而患者较多这一问题,将遥操作机器人技术与康复医疗器械相结合,以期研制一种基于力反馈的组合式远程康复训练机器人系统。方法:充分考虑到患者的安全性,采用磁流变阻尼器加上直流电机的模式,设计了一种组合式机械臂,将遥操作机器人技术应用于肢体残障者的康复训练,使患者可以根据康复治疗师的远程设定进行康复锻炼,并将虚拟现实技术与康复训练相结合,把枯燥的康复训练变成轻松有趣的游戏。结果及结论:该系统的服务对象是上肢有运动障碍的患者,通过对机械臂的拆卸和组合,可给患者提供康复需要的不同训练模式和治疗方案;运用计算机网络技术可使患者根据康复医师的远程设定进行康复训练;身临其境的虚拟现实技术显著提高了康复训练的积极性与效果。实验结果表明,所研制的远程康复训练机器人系统具有良好的适用性和安全性。     

基于Kinect和NAO机器人的人体上肢康复训练跟随控制EI北大核心CSCD

动作模仿是康复训练中常见的训练策略。传统的康复训练中患者需要在康复医师的指导下完成训练动作,然而由于医院资源有限,无法满足所有患者的训练指导需求。本文针对康复训练中的动作模仿任务,提出了一种基于Kinect和NAO机器人的跟随控制方法。该方法通过逆运动学解析实现了Kinect坐标系到NAO机器人坐标系关节角度映射。针对肘关节偏转角的估计问题,通过构建虚拟空间平面实现了偏转角的精确估计。最后,基于肘关节的运动偏转角进行了对比实验,结果显示该方法右肘横轴偏转和纵轴偏转的角度估计值均方根误差分别为2.734°和2.159°,证实了该方法可以实现NAO机器人实时、稳定地跟随人体动作,从而向患者展示康复训练方案。     

基于Simulink的上肢康复训练人机整体建模与分析

机器人康复训练是解决中风瘫痪患者康复训练需求的重要方法,康复机器人设定的训练参数对患者能力的适应程度是决定训练能否加快患者康复进程的重要因素。目前临床上的康复训练内容由康复医师对患者进行量表评估并结合自己的经验制定,这种经验式的训练方法在康复机器人训练过程中无法实现。为了探讨上肢康复机器人运动训练参数与患者运动能力之间的关系,本文建立了牵引式上肢康复机器人训练的Simulink人机整体模型,并将模型计算的人体肩关节、肘关节运动与实际动作下的肩关节、肘关节运动进行了对照。分析显示仿真结果与实验数据存在明显的相关性,从而证明了模型的准确性。进一步地,本文根据模型仿真结果拟合了人机接触端平面画圆半径与人体肩关节、肘关节主动运动自由度的线性函数关系,为临床上康复机器人制定训练目标提供了量化参考。     

基于多传感器信息的新型穿戴式上肢外骨骼康复机器人

目的 设计基于多传感器信息的新型穿戴式上肢外骨骼康复机器人,以解决上肢外骨骼康复机器人便携性不佳、患者参与度较低、训练模式自适应不足等问题,并探究受试者穿戴外骨骼时肌肉激活程度、肌电信号预测关节角度的准确性以及实现上肢康复训练的可行性.方法 该设备机械结构包括肘关节和腕关节,采用模块化设计并结合3D打印技术;控制系统包括肌电采集、应力采集、姿态采集等单元,并设计主动、被动和助动三种训练模式.受试者穿戴外骨骼机器人后进行屈-伸肘实验,对比有、无辅助力时手臂肌肉激活程度;分析肘关节角度,并对比肌电信号预测的关节运动角度;验证机器人运行性能与应力检测效果.结果 受试者穿戴外骨骼康复机器人安全可靠地完成了屈-伸肘动作,受试者肱二头肌、肱三头肌肌肉激活程度在有、无辅助力时分别减弱约32％、11％,肌电信号预测关节角度准确度约95％,应力测量值误差均低于5％.结论 上肢外骨骼机器人可以给人体提供辅助力、预测关节角度,机器人通过肌电、应力以及位置信息辅助患者实现上肢康复训练具有可行性.     

下肢步态康复机器人:研究进展及临床应用

背景:为解决康复训练过程中出现的问题,需要安全、定量、有效及可进行重复训练的新技术,康复机器人的出现从某种程度上解决了这一问题。目的:对如何使用康复机器人加强和恢复肌肉骨骼的功能,并改善其协调能力进行相应的探讨。分析以上新发展对康复领域的影响,局限性以及现在科研人员所面临的挑战。方法: 以stroke,gait,biofeedback,rehabilitation,treadmilltraining,rehabilitationrobot为检索词,检索Pubmed数据库(1992-04/2009-12);以"脑卒中,步态,生物反馈,康复疗法,活动平板训练,康复机器人"为检索词,检索中国期刊全文数据库(1992-04/2009-12)。以与下肢步态康复机器人的相关文献为评价指标。纳入与下肢步态康复机器人相关的内容,排除重复研究。结果与结论:腿部驱动步态康复训练机器人通过牵引患者大腿和小腿协调摆动完成腿部步行动作,足底驱动步态康复训练机器人通过驱动患者足部模拟步行过程中踝关节的运动轨迹来进行步态训,从某种程度上解决很多临床问题。在探索脑卒中患者如何使用康复机器人的过程中发现:机器人的应用提供了各种康复机会来改善残疾人的生存质量。     

Control strategies for effective robot assisted gait rehabilitation: The state of art and future prospects

A large number of gait rehabilitation robots, together with a variety of control strategies, have been developed and evaluated during the last decade. Initially, control strategies applied to rehabilitation robots were adapted from those applied to traditional industrial robots. However, these strategies cannot optimise effectiveness of gait rehabilitation. As a result, researchers have been investigating control strategies tailored for the needs of rehabilitation. Among these control strategies, assisted-as-needed (AAN) control is one of the most popular research topics in this field. AAN training strategies have gained the theoretical and practical evidence based backup from motor learning principles and clinical studies. Various approaches to AAN training have been proposed and investigated by research groups all around the world. This article presents a review on control algorithms of gait rehabilitation robots to summarise related knowledge and investigate potential trends of development.There are existing review papers on control strategies of rehabilitation robots. The review by Marchal-Crespo and Reinkensmeyer (2009) had a broad cover of control strategies of all kinds of rehabilitation robots. Hussain et al. (2011) had specifically focused on treadmill gait training robots and covered a limited number of control implementations on them. This review article encompasses more detailed information on control strategies for robot assisted gait rehabilitation, but is not limited to treadmill based training. It also investigates the potential to further develop assist-as-needed gait training based on assessments of patients’ ability.In this paper, control strategies are generally divided into the trajectory tracking control and AAN control. The review covers these two basic categories, as well as other control algorithm and technologies derived from them, such as biofeedback control. Assessments on human gait ability are also included to investigate how to further develop implementations based on assist-as-needed concept. For the consideration of effectiveness, clinical studies on robotic gait rehabilitation are reviewed and analysed from the viewpoint of control algorithm.     

A robotic system to train activities of daily living in a virtual environment

In the past decade, several arm rehabilitation robots have been developed to assist neurological patients during therapy. Early devices were limited in their number of degrees of freedom and range of motion, whereas newer robots such as the ARMin robot can support the entire arm. Often, these devices are combined with virtual environments to integrate motivating game-like scenarios. Several studies have shown a positive effect of game-playing on therapy outcome by increasing motivation. In addition, we assume that practicing highly functional movements can further enhance therapy outcome by facilitating the transfer of motor abilities acquired in therapy to daily life. Therefore, we present a rehabilitation system that enables the training of activities of daily living (ADL) with the support of an assistive robot. Important ADL tasks have been identified and implemented in a virtual environment. A patient-cooperative control strategy with adaptable freedom in timing and space was developed to assist the patient during the task. The technical feasibility and usability of the system was evaluated with seven healthy subjects and three chronic stroke patients.     

Improving backdrivability in geared rehabilitation robots

Many rehabilitation robots use electric motors with gears. The backdrivability of geared drives is poor due to friction. While it is common practice to use velocity measurements to compensate for kinetic friction, breakaway friction usually cannot be compensated for without the use of an additional force sensor that directly measures the interaction force between the human and the robot. Therefore, in robots without force sensors, subjects must overcome a large breakaway torque to initiate user-driven movements, which are important for motor learning. In this technical note, a new methodology to compensate for both kinetic and breakaway friction is presented. The basic strategy is to take advantage of the fact that, for rehabilitation exercises, the direction of the desired motion is often known. By applying the new method to three implementation examples, including drives with gear reduction ratios 100–435, the peak breakaway torque could be reduced by 60–80%.     

Development of a quantitative evaluation system for motor control using wrist movements--an analysis of movement disorders in patients with cerebellar diseases

In this study, we developed a new system for quantitative evaluation of the wrist movement. We designed this system to analyze the causal relationship between movement disorders and abnormal muscle activities. In addition, this system was also designed to be non-invasive and used handily at the bedside. We tested this system for analysis of movement disorders in the cerebellar patients. As an experimental task, we asked subjects to perform step-tracking wrist movements with a manipulandum, and simultaneously recorded wrist joint movements and muscle activities of four wrist prime movers with surface electrodes. The participants included eight patients with cerebellar diseases and eight normal controls. First, we made quantitative analysis of movement kinematics in the cerebellar patients in terms of accuracy and directional deviation of wrist movements. Then we examined how well the wrist movement could be explained with the activities of the four prime movers. Specifically, we compared the wrist joint torque calculated from the movement of the wrist (kinematic torque) and the wrist joint torque estimated from the muscle activities (muscle torque). Then we evaluated match between the two. Our surprising observation was that there were very high correlations between the kinematic torque and the muscle torque for both normal controls and cerebellar patients. Correlation coefficients R for normal controls were 0.85 +/- 0.06 for X-axis component and 0.78 +/- 0.09 for Y-axis component. On the other hand, correlation coefficients R for cerebellar patients were 0.78 +/- 0.11 for X-axis component and 0.78 +/- 0.1 for Y-axis component. These results strongly suggested that there were enough information in the activities of the four muscles to explain the position, speed and acceleration of the wrist joint. In other words, with our system, it is possible to identify causal abnormality of muscle activities for movement disorders. Therefore, it is possible with our system to analyze movement disorders at a motor command level.     

Non-linear adaptive controllers for an over-actuated pneumatic MR-compatible stepper

Pneumatics is one of the few actuation principles that can be used in an MR environment, since it can produce high forces without affecting imaging quality. However, pneumatic control is challenging, due to the air high compliance and cylinders non-linearities. Furthermore, the system’s properties may change for each subject. Here, we present novel control strategies that adapt to the subject’s individual anatomy and needs while performing accurate periodic gait-like movements with an MRI compatible pneumatically driven robot. In subject-passive mode, an iterative learning controller (ILC) was implemented to reduce the system’s periodic disturbances. To allow the subjects to intend the task by themselves, a zero-force controller minimized the interaction forces between subject and robot. To assist patients who may be too weak, an assist-as-needed controller that adapts the assistance based on online measurement of the subject’s performance was designed. The controllers were experimentally tested. The ILC successfully learned to reduce the variability and tracking errors. The zero-force controller allowed subjects to step in a transparent environment. The assist-as-needed controller adapted the assistance based on individual needs, while still challenged the subjects to perform the task. The presented controllers can provide accurate pneumatic control in MR environments to allow assessments of brain activation.     

一种跟随人体重心高度的骨盆支撑减重康复系统EI北大核心CSCD

支撑减重康复训练系统现已成为下肢运动功能障碍康复的重要治疗方法。本文针对现有的恒定阻抗减重的骨盆支撑减重康复系统在康复训练过程中骨盆机构提供固定的运动轨迹、患者主动参与康复训练程度低等问题,提出了一种跟随人体重心高度(CoMH)的骨盆支撑减重康复系统。该系统通过惯性测量单元采集人体下肢运动信息,经过人工神经网络对CoMH进行预测,实现骨盆支架高度的跟踪控制。通过偏瘫患者康复训练进行试验,结果表明,相比于骨盆支架运动轨迹固定的传统减重康复训练,跟随CoMH骨盆支撑减重康复训练使患者患侧髋、膝关节活动范围分别提升25.0%和31.4%,患侧摆动相与支撑相占比更接近健侧步态相位。该减重康复训练模式的骨盆支架的运动轨迹取决于当前训练者的状态,可实现偏瘫患者健侧主动运动引导行走训练。动态调整减重支撑的策略更有助于提高行走康复训练效率。     

Turning strategies in patients with cerebellar ataxia

Turning while walking is a common but demanding task requiring modification of the motor program from linear walking to lateral turning and it is associated with a high risk of falls. Patients with cerebellar ataxia have unstable gait and report a high incidence of falls. In the present study, we investigated the motor strategies adopted by ataxic patients when performing turns of different degrees and directions of rotation. Ten ataxic patients and 10 controls were analyzed while performing 30°/90° turns to the right/left. We recorded the number of completed turn tasks, the number of steps needed, and the time taken to complete the task, time–distance parameters and the onset of head, trunk and pelvis reorientation. The ataxic patients were less able to complete 90° turns, displayed a greater stride width, shorter step length, and greater number of steps when turning, and were unable to flexibly adjust their stride width across the turning task. The duration of the turning task and of the segmental reorientation did not differ from control values. Our findings indicate that ataxic patients have more difficulties in performing large turns and adopt a series of compensatory strategy aimed at reducing the instability associated with turning, such as enlarge the base of support, shorten the step length, increase the number of steps, and use the “multi-step” rather than the “spin-turn” strategy. Given the high risk of falls related to this task, it would be useful to include turning training in the rehabilitation protocol of ataxic patients.     

Enabling variable-stiffness hand rehabilitation orthoses with dielectric elastomer transducers

Patients affected by motor disorders of the hand and having residual voluntary movements of fingers or wrist can benefit from self-rehabilitation exercises performed with so-called dynamic hand splints. These systems consist of orthoses equipped with elastic cords or springs, which either provide a sustained stretch or resist voluntary movements of fingers or wrist. These simple systems are limited by the impossibility of modulating the mechanical stiffness. This limitation does not allow for customizations and real-time control of the training exercise, which would improve the rehabilitation efficacy. To overcome this limitation, ‘active’ orthoses equipped with devices that allow for electrical control of the mechanical stiffness are needed. Here, we report on a solution that relies on compact and light-weight electroactive elastic transducers that replace the passive elastic components. We developed a variable-stiffness transducer made of dielectric elastomers, as the most performing types of electromechanically active polymers. The transducer was manufactured with a silicone film and tested with a purposely-developed stiffness control strategy that allowed for electrical modulations of the force–elongation response. Results showed that the proposed new technology is a promising and viable solution to develop electrically controllable dynamic hand orthoses for hand rehabilitation.     

Functional MRI using robotic MRI compatible devices for monitoring rehabilitation from chronic stroke in the molecular medicine era (Review)

The number of individuals suffering from stroke is increasing daily, and its consequences are a major contributor to invalidity in today's society. Stroke rehabilitation is relatively new, having been hampered from the longstanding view that lost functions were not recoverable. Nowadays, robotic devices, which aid by stimulating brain plasticity, can assist in restoring movement compromised by stroke-induced pathological changes in the brain which can be monitored by MRI. Multiparametric magnetic resonance imaging (MRI) of stroke patients participating in a training program with a novel Magnetic Resonance Compatible Hand-Induced Robotic Device (MR_CHIROD) could yield a promising biomarker that, ultimately, will enhance our ability to advance hand motor recovery following chronic stroke. Using state-of-the art MRI in conjunction with MR_CHIROD-assisted therapy can provide novel biomarkers for stroke patient rehabilitation extracted by a meta-analysis of data. Successful completion of such studies may provide a ground breaking method for the future evaluation of stroke rehabilitation therapies. Their results will attest to the effectiveness of using MR-compatible hand devices with MRI to provide accurate monitoring during rehabilitative therapy. Furthermore, such results may identify biomarkers of brain plasticity that can be monitored during stroke patient rehabilitation. The potential benefit for chronic stroke patients is that rehabilitation may become possible for a longer period of time after stroke than previously thought, unveiling motor skill improvements possible even after six months due to retained brain plasticity.     

ARMin: a robot for patient-cooperative arm therapy

Task-oriented, repetitive and intensive arm training can enhance arm rehabilitation in patients with paralyzed upper extremities due to lesions of the central nervous system. There is evidence that the training duration is a key factor for the therapy progress. Robot-supported therapy can improve the rehabilitation allowing more intensive training. This paper presents the kinematics, the control and the therapy modes of the arm therapy robot ARMin. It is a haptic display with semi-exoskeleton kinematics with four active and two passive degrees of freedom. Equipped with position, force and torque sensors the device can deliver patient-cooperative arm therapy taking into account the activity of the patient and supporting him/her only as much as needed. The haptic display is combined with an audiovisual display that is used to present the movement and the movement task to the patient. It is assumed that the patient-cooperative therapy approach combined with a multimodal display can increase the patient’s motivation and activity and, therefore, the therapeutic progress.