An exoskeleton hand robotic training device is specially designed for persons after stroke to provide training on their impaired hand by using an exoskeleton robotic hand which is actively driven by their own muscle signals. It detects the stroke person's intention using his/her surface electromyography (EMG) signals from the hemiplegic side and assists in hand opening or hand closing functional tasks. The robotic system is made up of an embedded controller and a robotic hand module which can be adjusted to fit for different finger length. Eight chronic stroke subjects had been recruited to evaluate the effects of this device. The preliminary results showed significant improvement in hand functions (ARAT) and upper limb functions (FMA) after 20 sessions of robot-assisted hand functions task training. With the use of this light and portable robotic device, stroke patients can now practice more easily for the opening and closing of their hands at their own will, and handle functional daily living tasks at ease. A video is included together with this paper to give a demonstration of the hand robotic system on chronic stroke subjects and it will be presented in the conference.

A novel design of a hand functions task training robotic system was developed for the stroke rehabilitation. It detects the intention of hand opening or hand closing from the stroke person using the electromyography (EMG) signals measured from the hemiplegic side. This training system consists of an embedded controller and a robotic hand module. Each hand robot has 5 individual finger assemblies capable to drive 2 degrees of freedom (DOFs) of each finger at the same time. Powered by the linear actuator, the finger assembly achieves 55 degree range of motion (ROM) at the metacarpophalangeal (MCP) joint and 65 degree range of motion (ROM) at the proximal interphalangeal (PIP) joint. Each finger assembly can also be adjusted to fit for different finger length. With this task training system, stroke subject can open and close their impaired hand using their own intention to carry out some of the daily living tasks.

It is a challenge to reduce the muscular discoordination in the paretic upper limb after stroke in the traditional rehabilitation programs. In this study, a neuromuscular electrical stimulation (NMES) and robot hybrid system was developed for multi-joint coordinated upper limb physical training. The system could assist the elbow, wrist and fingers to conduct arm reaching out, hand opening/grasping and arm withdrawing by tracking an indicative moving cursor on the screen of a computer, with the support from the joint motors and electrical stimulations on target muscles, under the voluntary intention control by electromyography (EMG). Subjects with chronic stroke (n = 11) were recruited for the investigation on the assistive capability of the NMES-robot and the evaluation of the rehabilitation effectiveness through a 20-session device assisted upper limb training. In the evaluation, the movement accuracy measured by the root mean squared error (RMSE) during the tracking was significantly improved with the support from both the robot and NMES, in comparison with those without the assistance from the system (P < 0.05). The intra-joint and inter-joint muscular co-contractions measured by EMG were significantly released when the NMES was applied to the agonist muscles in the different phases of the limb motion (P < 0.05). After the physical training, significant improvements (P < 0.05) were captured by the clinical scores, i.e., Modified Ashworth Score (MAS, the elbow and the wrist), Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT), and Wolf Motor Function Test (WMFT). The EMG-driven NMES-robotic system could improve the muscular coordination at the elbow, wrist and fingers. ClinicalTrials.gov. NCT02117089 ; date of registration: April 10, 2014

Responsiveness of clinical assessments is an important element in the report of clinical effectiveness after rehabilitation. The correlation could reflect the validity of assessments as an indication of clinical performance before and after interventions. This study investigated the correlation and responsiveness of Fugl-Meyer Assessment (FMA), Motor Status Scale (MSS), Action Research Arm Test (ARAT) and the Modified Ashworth Scale (MAS), which are used frequently in effectiveness studies of robotic upper-extremity training in stroke rehabilitation. Twenty-seven chronic stroke patients were recruited for a 20-session upper-extremity rehabilitation robotic training program. This was a rater-blinded randomized controlled trial. All participants were evaluated with FMA, MSS, ARAT, MAS, and Functional Independent Measure before and after robotic training. Spearman's rank correlation coefficient was applied for the analysis of correlation. The standardized response mean (SRM) and Guyatt's responsiveness index (GRI) were used to analyze responsiveness. Spearman's correlation coefficient showed a significantly high correlation (ρ=0.91-0.96) among FMA, MSS, and ARAT and a fair-to-moderate correlation (ρ=0.40-0.62) between MAS and the other assessments. FMA, MSS, and MAS on the wrist showed higher responsiveness (SRM=0.85-0.98, GRI=1.59-3.62), whereas ARAT showed relatively less responsiveness (SRM=0.22, GRI=0.81). The results showed that FMA or MSS would be the best choice for evaluating the functional improvement in stroke studies on robotic upper-extremity training with high responsiveness and good correlation with ARAT. MAS could be used separately to evaluate the spasticity changes after intervention in terms of high responsiveness.