A task oriented haptic gait rehabilitation robot

This paper presents the concept, design process, and the prototype of a novel haptics-based lower-extremity rehabilitation robot for bed-ridden stroke patients. This system, named Virtual Gait Rehabilitation Robot (ViGRR), is required to provide the average gait motion training as well as other targeted exercises such as leg press, stair stepping and motivational gaming, in order to facilitate motor learning and enable the training of daily activities such as walking and maintaining balance. The system requirements are laid out and linked to the design of a redundant planar 4DOF robot concept prototype. An iterative design optimization loop was setup to obtain the robot kinematic and dynamic parameters as well as the actuators. The robot’s mechanical design, model, safety features, admittance controllers, and the architecture of the haptic controller are presented. Preliminary experiments were planned and performed to evaluate the capability of the system in delivering task-based virtual-reality exercises and trajectory following scenarios.     

基于自适应按需辅助的上肢镜像控制策略

为了提高偏瘫患者在镜像康复训练过程中的主动性与系统抗干扰性,该文提出一种基于自适应按需辅助的上肢镜像控制策略。该策略主要包括镜像控制和自适应按需辅助控制两个模块,镜像模块采集健侧位置解算出患侧期望位置,与患侧实际位置比较得到位置偏差;按需辅助模块结合传统阻抗控制和一种患肢运动状态评估方法,自动实时调节对患肢的辅助力大小,以实现患肢主动力矩的最大化。该文设计了两项实验,分别验证本策略对患者主动性和系统抗干扰性的提升效果,实验结果表明,对于镜像康复训练系统使用所提方法有效减小了56.9%的平均辅助力,患肢跟随健肢的位置精度为5.6%,能有效补偿89%的干扰外力。因此所提方法有效提升了训练者的主动性,同时具有良好的抗干扰性,满足镜像康复训练的要求。     

基于贝叶斯优化的康复训练参与度自适应增强方法研究

针对现有的评估被试主动参与度指标建模复杂以及训练强度与被试运动能力及参与度不匹配等问题,该文提出一种基于贝叶斯优化的挑战型力控制器自适应增强康复训练参与度的方法。首先使用基于表面肌电信号(sEMG)表征的肌肉激活度来评估被试者的参与度,其次采用基于轨迹误差放大的抗阻训练模式进行上肢训练,并构建归一化急动度和肌肉激活度相结合的综合目标函数,然后采用贝叶斯优化方法在训练过程中更新挑战型力场的抗阻系数和死区宽度两个超参数,逐次优化该目标函数,以提高运动轨迹的顺滑度并保持被试者的训练参与度。最后,将16名健康被试者随机分为实验组和对照组并以其非利手进行训练,验证所提方法的有效性。实验结果表明,训练过程中实验组的肌肉激活度维持在高于对照组2.51%的水平;训练后实验组的运动能力改善明显优于对照组(59.8% vs 40.7%),验证了该文所提的自适应增强康复训练参与度策略比固定参数策略更有优势。     

MATHEMATICAL MODELING AND EXPERIMENTAL STUDY ON SIT-TO-STAND PROCESS BASED ON ASSISTIVE STANDING-UP ROBOT

设计了一种符合人体起立运动的辅助起立机器人,通过牛顿欧拉方程对人体起立过程动力学进行分析与建模,推导机器人辅助起立、上肢辅助起立和肌力不足下肢辅助起立3种情况下,人体力与力矩平衡方程,依据方程在Simulink中建立仿真模型,并使用传感器系统对起立机器人辅助人体起立过程中力与力矩进行测量分析.结果表明：不论采取何种辅助起立方法,辅助起立机器人都可有效辅助起立,特别是对起立初始阶段辅助效果尤为明显.上肢辅助起立时,既可保持身体平衡与稳定,又可补偿起立时所需力与力矩,在接近完全站立时这种效果尤为明显,仿真模型可预测站立过程的关节力与力矩.肌力不足下肢参与辅助起立时,所提供辅助力有限但也起到一定作用.     

Relationship between first mobilization following the onset of stroke and clinical outcomes in patients with ischemic stroke in the general ward of a hospital: A cohort study

Objective: The purpose of this study was to compare the effects of first mobilization following a stroke with independently performing the activities of daily living at discharge in acute phase ischemic stroke patients in a general ward of a hospital. Methods: A total of 158 patients with ischemic strokes were admitted to a general ward from June 1, 2014 to March 31, 2015. Of the 158 patients, 53 met the study''s eligibility criteria. First mobilization was defined as the transfer of a patient from the bed to a wheelchair by a rehabilitation therapist. A favorable primary outcome at discharge was defined as a modified Rankin Scale score of < 3. The outcome was analyzed using the proportional hazards analysis and receiver operating characteristic curves. Results: The age of the participants was 78.2 ± 11.7 years, stroke severity evaluated by the National Institutes of Health Stroke Scale scores on admission was 14.3 ± 10.6 points, and first mobilization of this population was 6.4 ± 5.2 days. Thirteen [25%] patients had a favorable outcome. Hazards analysis showed a favorable outcome due to first mobilization (adjusted hazards ratio 0.80, 95% confidence interval 0.65-0.98; p < 0.05). The cutoff point for first mobilization to produce a favorable outcome was 6.5 days after the stroke onset (area under the curve 0.729; p < 0.05). Conclusion: As seen in stroke units, early first mobilization is associated with improved clinical outcomes in ischemic stroke patients admitted to a general ward.     

早期功能锻炼对乳腺癌患者术后康复影响的研究

为探讨早期功能锻炼对乳腺癌患者术后肢体功能的影响,对120例行早期功能锻炼的乳腺癌患者术后患者及66例未行早期功能锻炼的乳腺癌术后患者的临床资料进行了回顾性对照分析。结果表明,早期功能锻炼组患者上肢功能障碍的发生率明显低于对照组(P<0.05)。提示乳腺癌患者术后进行早期功能锻炼,可明显降低上肢功能障碍的发生率,明显改善患者的生活质量。     

基于Kinect体感器的康复机械手臂系统算法设计与实现

设计实现一种新的机械手臂康复系统。利用Kinect体感器获取人体右肩、右肘和右腕3个关节的三维坐标,计算得出所需控制参数。建立体感器与机械手臂之间通信机制,通过数据反馈调整所需控制参数。实现多自由度同时协调运动的康复型机械手臂控制方法。实验表明,该系统控制下的机械手臂能够平滑无明显停顿感地模仿人类手臂的自然动作,提高患者使用时的舒适度,增强康复效果。     

A decentralised iterative learning control framework for collaborative tracking

Collaborative tracking control involves two or more subsystems working together to perform a global objective, and is increasingly used within a diverse range of applications. Decentralised iterative learning control schemes have demonstrated highly accurate collaborative tracking by using past experience gained over repeated attempts at the task. However they impose highly restrictive constraints on the system dynamics, and their reliance on inverse dynamics has degraded their robustness to model uncertainty.This paper proposes the first general decentralised iterative learning framework to address this problem, thereby enabling a wide range of existing iterative learning control methodologies to be applied in a decentralised manner to collaborative subsystems. This framework is illustrated through the derivation of a variety of new decentralised iterative learning control algorithms which balance collaborative tracking performance with optimisation of a general objective function. The framework is illustrated by application to wearable stroke rehabilitation technology in which each subsystem is a muscle artificially activated by electrical stimulation. These verify the framework’s simplified design and reduced hardware and communication overheads.     

Progression‐Preserving Dimension Reduction for High‐Dimensional Sensor Data Visualization

This letter presents Progression‐Preserving Projection, a dimension reduction technique that finds a linear projection that maps a high‐dimensional sensor dataset into a two‐ or three‐dimensional subspace with a particularly useful property for visual exploration. As a demonstration of its effectiveness as a visual exploration and diagnostic means, we empirically evaluate the proposed technique over a dataset acquired from our own virtual‐reality‐enhanced ball‐intercepting training system designed to promote the upper extremity movement skills of individuals recovering from stroke‐related hemiparesis.