Immediate Effects of Functional Electrical Stimulation-Assisted Cycling on the Paretic Muscles of Patients With Hemiparesis After Stroke: Evidence From Electrical Impedance Myography.

Background: Electrical impedance myography (EIM) has been applied to assess muscle health conditions in neuromuscular disorders. This study aimed to detect immediate muscle electrical impedance property alterations in lower extremity of chronic stroke survivors immediately after functional electrical stimulation (FES)-assisted cycling training. Methods: Fourteen chronic stroke survivors were recruited for the current study. EIM measurements were conducted before and immediately after 40-min FES-assisted cycling training for each subject. Four interested muscle groups [rectus femoris (RF), biceps femoris (BF), tibialis anterior (TA), and the medial head of gastrocnemius (MG)] were selected. Correlation analysis was performed to reveal a significant correlation between changes in EIM parameters and clinical scales [Fugl-Meyer Assessment of the lower extremity (FMA-LE); 6-min walking test (6MWT)]. Results: Immediately after training, reactance (X) and phase angle (θ) values significantly increased on the TA and MG muscles. Significant correlation was observed between X value and FMA-LE scores (r = 0.649, p = 0.012) at MG as well as X and FMA scores of the ankle joint (r = 0.612, p = 0.02). Resistance (R) and θ were significantly correlated with 6MWT score (R-6MWT: r = 0.651, p = 0.012; θ-6MWT: r = 0.621, p = 0.018). Conclusion: This brief report demonstrated that EIM can reveal the intrinsic property alteration in the paretic muscle of chronic stroke survivors immediately after FES-assisted cycling training. These alterations might be related to muscle hypertrophy (i.e., increases in muscle fiber size). This brief report might aid the understanding of the mechanism of electrical stimulation-assisted exercise in improving muscle function of stroke survivors.

Effects of wearable ankle robotics for stair and over-ground training on sub-acute stroke: a randomized controlled trial.

BACKGROUND: Wearable ankle robotics could potentially facilitate intensive repetitive task-specific gait training on stair environment for stroke rehabilitation. A lightweight (0.5 kg) and portable exoskeleton ankle robot was designed to facilitate over-ground and stair training either providing active assistance to move paretic ankle augmenting residual motor function (power-assisted ankle robot, PAAR), or passively support dropped foot by lock/release ankle joint for foot clearance in swing phase (swing-controlled ankle robot, SCAR). In this two-center randomized controlled trial, we hypothesized that conventional training integrated with robot-assisted gait training using either PAAR or SCAR in stair environment are more effective to enhance gait recovery and promote independency in early stroke, than conventional training alone. METHODS: Sub-acute stroke survivors (within 2 months after stroke onset) received conventional training integrated with 20-session robot-assisted training (at least twice weekly, 30-min per session) on over-ground and stair environments, wearing PAAR (n = 14) or SCAR (n = 16), as compared to control group receiving conventional training only (CT, n = 17). Clinical assessments were performed before and after the 20-session intervention, including functional ambulatory category as primary outcome measure, along with Berg balance scale and timed 10-m walk test. RESULTS: After the 20-session interventions, all three groups showed statistically significant and clinically meaningful within-group functional improvement in all outcome measures (p < 0.005). Between-group comparison showed SCAR had greater improvement in functional ambulatory category (mean difference + 0.6, medium effect size 0.610) with more than 56% independent walkers after training, as compared to only 29% for CT. Analysis of covariance results showed PAAR had greater improvement in walking speed than SCAR (mean difference + 0.15 m/s, large effect size 0.752), which was in line with the higher cadence and speed when wearing the robot during the 20-session robot-assisted training over-ground and on stairs. CONCLUSIONS: Robot-assisted stair training would lead to greater functional improvement in gait independency and walking speed than conventional training in usual care. The active powered ankle assistance might facilitate users to walk more and faster with their paretic leg during stair and over-ground walking. TRIAL REGISTRATION: ClinicalTrials.gov NCT03184259. Registered on 12 June 2017.

Functional brain networks assessed with surface electroencephalography for predicting motor recovery in a neural guided intervention for chronic stroke.

Predicting whether a chronic stroke patient is likely to benefit from a specific intervention can help patients establish reasonable expectations. It also provides the basis for candidates selecting for the intervention. Recent convergent evidence supports the value of network-based approach for understanding the relationship between dysfunctional neural activity and motor deficits after stroke. In this study, we applied resting-state brain connectivity networks to investigate intervention-specific predictive biomarkers of motor improvement in 22 chronic stroke participants who received either combined action observation with EEG-guided robot-hand training (Neural Guided-Action Observation Group, n = 12, age: 34-68 years) or robot-hand training without action observation and EEG guidance (non-Neural Guided-text group, n = 10, age: 42-57 years). The robot hand in Neural Guided-Action Observation training was activated only when significant mu suppression (8-12 Hz) was detected from participant's EEG signals in ipsilesional hemisphere while it was randomly activated in non-Neural Guided-text training. Only the Neural Guided-Action Observation group showed a significant long-term improvement in their upper-limb motor functions (P < 0.5). In contrast, no significant training effect on the paretic motor functions was found in the non-Neural Guided-text group (P > 0.5). The results of brain connectivity estimated via EEG coherence showed that the pre-training interhemispheric connectivity of delta, theta, alpha and contralesional connectivity of beta were motor improvement related in the Neural Guided-Action Observation group. They can not only differentiate participants with good and poor recovery (interhemispheric delta: P = 0.047, Hedges' g = 1.409; interhemispheric theta: P = 0.046, Hedges' g = 1.333; interhemispheric alpha: P = 0.038, Hedges' g = 1.536; contralesional beta: P = 0.027, Hedges' g = 1.613) but also significantly correlated with post-training intervention gains (interhemispheric delta: r = -0.901, P < 0.05; interhemispheric theta: r = -0.702, P < 0.05; interhemispheric alpha: r = -0.641, P < 0.05; contralesional beta: r = -0.729, P < 0.05). In contrast, no EEG coherence was significantly correlated with intervention gains in the non-Neural Guided-text group (all P s > 0.05 ). Partial least square regression showed that the combination of pre-training interhemispheric and contralesional local connectivity could precisely predict intervention gains in the Neural Guided-Action Observation group with a strong correlation between predicted and observed intervention gains (r = 0.82 r = 0.82 ) and between predicted and observed intervention outcomes (r = 0.90 r = 0.90 ). In summary, EEG-based resting-state brain connectivity networks may serve clinical decision-making by offering an approach to predicting Neural Guided-Action Observation training-induced motor improvement.

Modulation of Functional Connectivity and Low-Frequency Fluctuations After Brain-Computer Interface-Guided Robot Hand Training in Chronic Stroke: A 6-Month Follow-Up Study.

Hand function improvement in stroke survivors in the chronic stage usually plateaus by 6 months. Brain-computer interface (BCI)-guided robot-assisted training has been shown to be effective for facilitating upper-limb motor function recovery in chronic stroke. However, the underlying neuroplasticity change is not well understood. This study aimed to investigate the whole-brain neuroplasticity changes after 20-session BCI-guided robot hand training, and whether the changes could be maintained at the 6-month follow-up. Therefore, the clinical improvement and the neurological changes before, immediately after, and 6 months after training were explored in 14 chronic stroke subjects. The upper-limb motor function was assessed by Action Research Arm Test (ARAT) and Fugl-Meyer Assessment for Upper-Limb (FMA), and the neurological changes were assessed using resting-state functional magnetic resonance imaging. Repeated-measure ANOVAs indicated that long-term motor improvement was found by both FMA (F[2,26] = 6.367, p = 0.006) and ARAT (F[2,26] = 7.230, p = 0.003). Seed-based functional connectivity analysis exhibited that significantly modulated FC was observed between ipsilesional motor regions (primary motor cortex and supplementary motor area) and contralesional areas (supplementary motor area, premotor cortex, and superior parietal lobule), and the effects were sustained after 6 months. The fALFF analysis showed that local neuronal activities significantly increased in central, frontal and parietal regions, and the effects were also sustained after 6 months. Consistent results in FC and fALFF analyses demonstrated the increase of neural activities in sensorimotor and fronto-parietal regions, which were highly involved in the BCI-guided training. Clinical Trial Registration: This study has been registered at ClinicalTrials.gov with clinical trial registration number NCT02323061.

Muscle endurance time estimation during isometric training using electromyogram and supervised learning.

Constant-force isometric muscle training is useful for increasing the maximal strength , rehabilitation and work-fatigue assessment. Earlier studies have shown that muscle fatigue characteristics can be used for evaluating muscle endurance limit. STUDY OBJECTIVE: To predict muscle endurance time during isometric task using frequency spectrum characteristics of surface electromyography signals along with analysis of frequency spectrum shape and scale during fatigue accumulation. METHOD: Thirteen subjects performed isometric lateral raise at 60% MVC of deltoid (lateral) till endurance limit. Time windowed sEMG frequency spectrum was modelled using 2-parameter distributions namely Gamma and Weibull for spectrum analysis and endurance prediction. RESULTS: Gamma distribution provided better spectrum fitting (P < 0.001) than Weibull distribution. Spectrum Distribution demonstrated no change in shape but shifted towards lower frequency with increase of magnitude at characteristic mode frequency. Support Vector Regression based algorithm was developed for endurance time estimation using features derived from fitted frequency spectrum. Time taken till endurance limit for acquired dataset 38.53 ± 17.33 s (Mean ± Standard Deviation) was predicted with error of 0.029 ± 4.19 s . R-square: 0.956, training and test sets RMSE was calculated as 3.96 and 4.29 s respectively. The application of the algorithm suggested that model required 70% of sEMG signal from maximum time of endurance for high prediction accuracy. CONCLUSION: Endurance Limit prediction algorithm was developed for quantification of endurance time for optimizing isometric training and rehabilitation. Our method could help personalize and change conventional training method of same weight and duration for all subjects with optimized training parameters, based upon individual sEMG activity.

Design of a 3D Printed Soft Robotic Hand for Stroke Rehabilitation and Daily Activities Assistance.

In this paper, we present the new personalized 3D printed soft robotic hand for providing rehabilitation training and daily activities assistance to stroke survivors. The Soft-Elastic Composite Actuator (SECA) on the robotic hand is direct 3D printed to accommodate with different finger sizes. Flexion and extension can be actively facilitated on the SECA using the same pressurizing source. Iterative learning model predictive control (ILMPC) method is used to be the control algorithm of SECA. At 160 kPa of maximum input pressure, results show that the actuator bending angles can reach to 137 °, and tip output force can also reach to 2.45 N. Multiple 3D printed SECAs are integrated to a 3D printed hand base and then to be worn on stroke survivors. Two stroke survivors are recruited to evaluate the intention-based rehabilitation training with the 3D printed soft robotic hand, which improvement of their hand function can be observed on performing some daily tasks such as grasping a coin.

Robotic Glove with Soft-Elastic Composite Actuators for Assisting Activities of Daily Living.

Soft robotic hand/gloves for hand rehabilitation can aid the performance of activities of daily living (ADL). Although existing soft robotic hands can assist with finger flexion, few have addressed finger extension, which is a challenging task for stroke patients due to poststroke spasticity. In this article, we describe the design of a composite actuator, the soft-elastic composite actuator (SECA), to facilitate both finger flexion and extension. A double-segmented SECA comprising two serially connected fiber-reinforced actuators with two bottom torque-compensating layers was fabricated. The SECA bends and extends by pneumatic actuation, and the torque-compensating layers offer an assistive bending moment to configure the bending moment inside the SECA. The principles associated with selection of the torque-compensating layer are described. Analytical models were established to quantify the input pressure and the bending angle of SECA with free bending and when placed on a model compromised hand. The analytical models were validated experimentally and by the finite element method. Moreover, a stroke survivor was recruited to test the new robotic glove integrated with the multiple double-segmented SECA. The robotic glove facilitated hand opening and closing by the patient, and successfully assisted with grasp of a Chinese chess piece and twisting of a towel.

Development and Evaluation of a Kinect-based Rapid Movement Therapy Training Platform for Balance Rehabilitation.

With the growing aging and overall population, the demand for healthcare professionals and their burden increases by time. Effective balance recovery reaction is required to prevent falls. The aim of this project is to provide low-cost portable balance training system that trains the two important components of effective balance recovery reaction: faster movement completion time (MT) and larger range of motion (ROM). This is done by a Kinect-based interactive rapid movement therapy training platform for reaching and stepping actions. The platform provides real-time feedback to the patient, generates a report for healthcare professionals to monitor the patient's progress, and can be utilized in patient's home or community centers. A pilot study to test the platform was conducted on seventeen stroke patients and it has shown significant improvement in both MT (faster) and ROM (larger).

How to prepare a person with complete spinal cord injury to use surface electrodes for FES trike cycling.

Functional Electrical Stimulation (FES) cycling could benefit people with Spinal Cord Injury (SCI). The FES cycling involves large muscle groups during the training, and thus improves the cardiovascular function, increases the muscle bulk and reduces the secondary complications. This study developed an outdoor FES exercise cycling system for complete SCI persons to exercise their lower limbs without putting extra load on upper extremities. The mechanical structure of the cycling system was specially redesigned to secure the SCI persons in the cycling system. A six-phase-angle-driven control algorithm was designed to stimulate the quadriceps and hamstrings muscles. Two training modes, i.e., continuous mode and on-off mode, were designed and tested to increase the duration of the electrical stimulation to reduce muscle fatigue. A complete SCI volunteer participated in this training for six months. Beneficial effects could be observed such as paralyzed lower limb muscles had regained the muscle mass and reduced edema from the improved blood circulation. Moreover, the SCI volunteer attended the Cybathlon FES-bike competition in Zurich in October 2016 with Team Phoenix from the CUHK.

Fine finger motor skill training with exoskeleton robotic hand in chronic stroke: stroke rehabilitation.

Background and Purpose. Stroke survivors often show a limited recovery in the hand function to perform delicate motions, such as full hand grasping, finger pinching and individual finger movement. The purpose of this study is to describe the implementation of an exoskeleton robotic hand together with fine finger motor skill training on 2 chronic stroke patients. Case Descriptions. Two post-stroke patients participated in a 20-session training program by integrating 10 minutes physical therapy, 20 minutes robotic hand training and 15 minutes functional training tasks with delicate objects(card, pen and coin). These two patients (A and B) had cerebrovascular accident at 6 months and 11 months respectively when enrolled in this study. Outcomes. The results showed that both patients had improvements in Fugl-Meyer assessment (FM), Action Research Arm Test (ARAT). Patients had better isolation of the individual finger flexion and extension based on the reduced muscle co-contraction from the electromyographic(EMG) signals and finger extension force after 20 sessions of training. Discussion. This preliminary study showed that by focusing on the fine finger motor skills together with the exoskeleton robotic hand, it could improve the motor recovery of the upper extremity in the fingers and hand function, which were showed in the ARAT. Future randomized controlled trials are needed to evaluate the clinical effectiveness.

A pilot study of randomized clinical controlled trial of gait training in subacute stroke patients with partial body-weight support electromechanical gait trainer and functional electrical stimulation: six-month follow-up.

BACKGROUND AND PURPOSE: This study aimed to assess the effectiveness of gait training using an electromechanical gait trainer with or without functional electrical stimulation for people with subacute stroke. METHODS: This was a nonblinded randomized controlled trial with a 6-month follow-up. Fifty-four subjects were recruited within 6 weeks after stroke onset and were randomly assigned to 1 of 3 gait intervention groups: conventional overground gait training treatment (CT, n=21), electromechanical gait trainer (GT, n=17) and, electromechanical gait trainer with functional electrical stimulation (GT-FES, n=16). All subjects were to undergo an assigned intervention program comprising a 20-minute session every weekday for 4 weeks. The outcome measures were Functional Independence Measure, Barthel Index, Motricity Index leg subscale, Elderly Mobility Scale (EMS), Berg Balance Scale, Functional Ambulatory Category (FAC), and 5-meter walking speed test. Assessments were made at baseline, at the end of the 4-week intervention program, and 6 months after the program ended. RESULTS: By intention-to-treat and multivariate analysis, statistically significant differences showed up in EMS (Wilks' lambda=0.743, P=0.005), FAC (Wilks' lambda=0.744, P=0.005) and gait speed (Wilks' lambda=0.658, P<0.0001). Post hoc analysis (univariate 2-way ANCOVA) revealed that the GT and GT-FES groups showed significantly better improvement in comparison with the CT group at the end of the 4 weeks of training and in the 6-month follow-up. CONCLUSIONS: For the early stage after stroke, this study indicated a higher effectiveness in poststroke gait training that used an electromechanical gait trainer compared with conventional overground gait training. The training effect was sustained through to the 6-month follow-up after the intervention.

Gait training of patients after stroke using an electromechanical gait trainer combined with simultaneous functional electrical stimulation.

BACKGROUND AND PURPOSE: This case report describes the implementation of gait training intervention that used an electromechanical gait trainer with simultaneous functional electrical stimulation (FES) for 2 patients with acute ischemic stroke. CASE DESCRIPTION: Two individuals with post-stroke hemiplegia of less than 6 weeks' duration participated in a 4-week gait training program as an adjunct to physical therapy received at a hospital. After the 4-week intervention, both patients were discharged from the hospital, and they returned after 6 months for a follow-up evaluation. OUTCOMES: By the end of the 4-week intervention, both patients had shown improvements in scores on the Barthel Index, Berg Balance Scale, Functional Ambulation Categories Scale, 5-m timed walking test, and Motricity Index. In the 6-month follow-up evaluation, both patients continued to have improvements in all outcome measures. DISCUSSION: This case report shows that, following the use of an electromechanical gait trainer simultaneously with FES, patients after acute stroke had improvements in gait performance, functional activities, balance, and motor control in the long term.