Hemiparetic Patients Research Articles

Effectiveness of Mirror Therapy through Telerehabilitation on Upper Extremity Performance in Hemiparetic Stroke Patients: An Experimental Study

Introduction: A major challenge in stroke rehabilitation is the paresis of the Upper Extremity (UE), resulting in limited functional performance. Recently, motor imagery and Mirror Therapy (MT) have been recommended as an additional rehabilitation strategies that could be beneficial for motor rehabilitation after a stroke. Aim: To determine the effectiveness of mirror visual feedback through Telerehabilitation (TR) on UE functional performance in hemiparetic stroke patients. Materials and Methods: An experimental pretest, post-test study design was conducted at SRM Medical College Hospital and Research Centre, SRMIST, Kattankulathur, Chengalpattu, Tamil Nadu, India from January 2021 to June 2021. Total of 60 patients diagnosed with hemiparetic stroke were included in the study through convenience sampling and divided into two groups. The experimental group (n=30) received TR, and the control group (n=30) received face-to-face MT for 12 weeks. A pretest and post-test evaluation were administered using the Wolf Motor Function Test (WMFT) and Fugl-Meyer Assessment for the Upper Extremity (FMA-UE). Within-group analysis was performed using the Wilcoxon Signed-Rank Test, while intergroup analysis was conducted using the Mann-Whitney U Test. Results: The study revealed statistical significance between the pretest and post-test scores of the WMFT-FAS (Functional Ability Score), WMFT-Time (Performance Time), and FMA-UE in the control and experimental groups. The results showed no statistically significant difference between the post-test scores of the control and experimental groups in the FMA and WMFTFAS. However, there was a statistically significant distinction in the post-test scores between the control and experimental groups in WMFT-Time. Conclusion: The study concluded that mirror visual feedback through TR was an effective treatment method to improve UE functional performance among hemiparetic stroke patients by offering an alternative service delivery model for occupational therapy

Investigating Activity Recognition for Hemiparetic Stroke Patients Using Wearable Sensors: A Deep Learning Approach with Data Augmentation.

Measuring the daily use of an affected limb after hospital discharge is crucial for hemiparetic stroke rehabilitation. Classifying movements using non-intrusive wearable sensors provides context for arm use and is essential for the development of a home rehabilitation system. However, the movement classification of stroke patients poses unique challenges, including variability and sparsity. To address these challenges, we collected movement data from 15 hemiparetic stroke patients (Stroke group) and 29 non-disabled individuals (ND group). The participants performed two different tasks, the range of motion (14 movements) task and the activities of daily living (56 movements) task, wearing five inertial measurement units in a home setting. We trained a 1D convolutional neural network and evaluated its performance for different training groups: ND-only, Stroke-only, and ND and Stroke jointly. We further compared the model performance with data augmentation from axis rotation and investigated how the performance varied based on the asymmetry of movements. The joint training of ND + Stroke yielded an increased F1-score by a margin of 31.6% and 10.6% compared to ND-only training and Stroke-only training, respectively. Data augmentation further enhanced F1-scores across all conditions by an average of 11.3%. Finally, asymmetric movements decreased the F1-score by 25.9% compared to symmetric movements in the Stroke group, indicating the importance of asymmetry in movement classification.

Robotic exoskeleton embodiment in post-stroke hemiparetic patients: an experimental study about the integration of the assistance provided by the REFLEX knee exoskeleton

Hemiparetic gait is the most common motor-disorder after stroke and, in spite of rehabilitation efforts, it is persistent in 50% of community dwelling stroke-survivors. Robotic exoskeletons have been proposed as assistive devices to support impaired joints. An example of these devices is the REFLEX knee exoskeleton, which assists the gait of hemiparetic subjects and whose action seems to be properly embodied by stroke survivors, who were able to adapt the motion of their non-assisted limbs and, therefore, reduce their compensation mechanisms. This paper presents an experimental validation carried out to deepen into the effects of REFLEX’s assistance in hemiparetic subjects. Special attention was paid to the effect produced in the muscular activity as a metric to evaluate the embodiment of this technology. Significant differences were obtained at the subject level due to the assistance; however, the high dispersion of the measured outcomes avoided extracting global effects at the group level. These results highlight the need of individually tailoring the action of the robot to the individual needs of each patient to maximize the beneficial outcomes. Extra research effort should be done to elucidate the neural mechanisms involved in the embodiment of external devices by stroke survivors.

The impact of lesion side on bilateral upper limb coordination after stroke

BackgroundA stroke frequently results in impaired performance of activities of daily life. Many of these are highly dependent on effective coordination between the two arms. In the context of bimanual movements, cyclic rhythmical bilateral arm coordination patterns can be classified into two fundamental modes: in-phase (bilateral homologous muscles contract simultaneously) and anti-phase (bilateral muscles contract alternately) movements. We aimed to investigate how patients with left (LHS) and right (RHS) hemispheric stroke are differentially affected in both individual-limb control and inter-limb coordination during bilateral movements.MethodsWe used kinematic measurements to assess bilateral coordination abilities of 18 chronic hemiparetic stroke patients (9 LHS; 9 RHS) and 18 age- and sex-matched controls. Using KINARM upper-limb exoskeleton system, we examined individual-limb control by quantifying trajectory variability in each hand and inter-limb coordination by computing the phase synchronization between hands during anti- and in-phase movements.ResultsRHS patients exhibited greater impairment in individual- and inter-limb control during anti-phase movements, whilst LHS patients showed greater impairment in individual-limb control during in-phase movements alone. However, LHS patients further showed a swap in hand dominance during in-phase movements.ConclusionsThe current study used individual-limb and inter-limb kinematic profiles and showed that bilateral movements are differently impaired in patients with left vs. right hemispheric strokes. Our results demonstrate that both fundamental bilateral coordination modes are differently controlled in both hemispheres using a lesion model approach. From a clinical perspective, we suggest that lesion side should be taken into account for more individually targeted bilateral coordination training strategies.Trial registration: the current experiment is not a health care intervention study.

Muscle quality improvement in subacute post-stroke patients after rehabilitation: Usefulness of segmental phase angle from bioelectrical impedance analysis

During stroke rehabilitation, the whole-body Phase Angle (PhA) from Bioelectrical Impedance Analysis (BIA) is measured to assess whole-body muscle quality, which reflects cellular integrity and function. The segmental BIA is a valuable method for assessing the body composition of specific body segments, such as the arms, legs, and hemisoma. After a stroke insult, patients frequently experience hemiparesis, and segmental PhA from segmental BIA appears to be an appropriate parameter for examining the muscle quality of affected and unaffected limbs separately. This study aims to investigate whether segmental PhA is more informative than whole-body PhA in (a) assessing the deterioration of muscle quality in post-stroke patients and (b) monitoring its recovery following rehabilitative treatment. This longitudinal study recruited subacute post-stroke patients who were admitted to our rehabilitation center. At admission, demographic, anamnestic, and clinical information, such as the presence of comorbidities, were recorded. BIA was used to evaluate the whole-body PhA and segmental PhA of the affected and unaffected hemisoma, arms, and legs at admission (T0) and after a six-week rehabilitation program (T1). The modified Barthel Index (mBI), Fugl-Meyer Assessment for the Upper Extremity (FMA-UE), and Motricity Index of the Upper (MI-UE) and Lower (MI-LE) Extremities were evaluated at T0 and T1 to determine the patient's Activity of Daily Living (ADL) performance, upper limb motor performance, and upper and lower limb muscle strength, respectively. We evaluated segmental and whole-body BIA in 70 subacute post-stroke patients (women n=34, ischemic n=56, mean age 70±11) at T0 and T1. Whole-body PhA values of the patients were below the normal range. Considering segmental data, the affected hemisoma, arm, and leg had considerably lower PhA values as compared to the unaffected body segments. Furthermore, at T1, the PhA values of all affected body segments improved, while those of the unaffected ones and whole-body PhA did not. At both T0 and T1, the segmental PhA values of the affected body segments showed to be related with all clinical outcome measures, while whole-body PhA correlated only with mBI. This study emphasizes the significance of measuring segmental PhA in hemiparetic subacute stroke patients undergoing rehabilitation treatment. Segmental PhA is a more accurate parameter to evaluate rehabilitation treatment in patients with hemiparesis because it can distinguish affected from unaffected body segments, hence facilitating accurate monitoring of muscle quality improvements resulting from a rehabilitation program.

Single-Belt Versus Split-Belt: Intelligent Treadmill Control via Microphase Gait Capture for Poststroke Rehabilitation.

Stroke is the leading long-term disability and causes a significant financial burden associated with rehabilitation. In poststroke rehabilitation, individuals with hemiparesis have a specialized demand for coordinated movement between the paretic and the nonparetic legs. The split-belt treadmill can effectively facilitate the paretic leg by slowing down the belt speed for that leg while the patient is walking on a split-belt treadmill. Although studies have found that split-belt treadmills can produce better gait recovery outcomes than traditional single-belt treadmills, the high cost of split-belt treadmills is a significant barrier to stroke rehabilitation in clinics. In this article, we design an AI-based system for the single-belt treadmill to make it act like a split-belt by adjusting the belt speed instantaneously according to the patient's microgait phases. This system only requires a low-cost RGB camera to capture human gait patterns. A novel microgait classification pipeline model is used to detect gait phases in real time. The pipeline is based on self-supervised learning that can calibrate the anchor video with the real-time video. We then use a ResNet-LSTM module to handle temporal information and increase accuracy. A real-time filtering algorithm is used to smoothen the treadmill control. We have tested the developed system with 34 healthy individuals and four stroke patients. The results show that our system is able to detect the gait microphase accurately and requires less human annotation in training, compared to the ResNet50 classifier. Our system "Splicer" is boosted by AI modules and performs comparably as a split-belt system, in terms of timely varying left/right foot speed, creating a hemiparetic gait in healthy individuals, and promoting paretic side symmetry in force exertion for stroke patients. This innovative design can potentially provide cost-effective rehabilitation treatment for hemiparetic patients.

Effectiveness of Motor Relearning Programme on Sit to Stand Performance Among Right and Left Hemiparesis Patients

OBJECTIVE: To compare the effectiveness of Motor Relearning Program (MRP) on sit to stand performance among right and left hemi paresis patients. Study design: Quasi experimental study design with two groups pre-test and post test. Participants: A total of 16 male right and left hemi paretic patients in the age group of 45 to 65 years participated in the study. The participants recruited were diagnosed with middle cerebral artery lesion with duration less than 3 weeks and a score of 1 on the Motor Assessment Scale for sitting to standing up item. The patients who satisfied inclusion criteria were conveniently assigned into 2 groups. Group A- right hemiparesis and Group B- left hemi paresis. Interventions: Motor Relearning Programme for sitting to standing for duration of 2 weeks (40 minutes/session, 5session/week, total 10 sessions). Outcome Measures: Measurements were taken using Sitting to standing functional item of Motor Assessment Scale (MAS) following 2 weeks of the training program. Results: Statistical analysis was done using the ‘t’ test, which showed a significant improvement in Motor Assessment Scale (MAS) for sitting to standing up item for both groups. But GROUP-A (Right hemi paresis) showed a more significant improvement than GROUP – B(Left hemi paresis) in Motor Assessment Scale (MAS) for sitting to standing up item. Conclusions: The findings of this study suggest Motor Relearning Programme improves sit to stand performance. And there was a significant difference in sit to stand performance between right and left hemi paresis patients following 2 weeks of Motor Relearning Programme. Keywords: Motor Relearning Programme, Sit to stand, Motor Assessment Scale, Hemi paresis.

Efficacy of MCIMT with Auditory Cueing in order to Augment Functional Motor Recovery of Chronic Hemiparetic Arm

Background: Stroke is a leading cause of functional impairments globally, often resulting in long-term disability and a substantial impact on individuals, families, and caregivers. Learned nonuse, a phenomenon where motor deficits persist after a stroke due to central nervous system suppression, is a significant challenge in stroke rehabilitation. Constraint-Induced Movement Therapy (CIMT) is a well-established neurorehabilitation approach based on behavioural training, which includes repetitive task-specific training, behavioural techniques, and constraining the use of the more affected upper extremity. CIMT has been successful in improving functionality in chronic hemiparetic stroke patients, promoting cortical reorganization and neural plasticity.
 Method: This study involved 60 stroke survivors aged 20 or older, selected purposively and meeting specific criteria. Participants underwent an 8-week Modified CIMT (M-CIMT) program with auditory cueing for the hemiparetic upper limb. Data collection included pre-test and post-test assessments using the Wolf Motor Function Test (WMFT) and the Motor Activity Log (MAL) to evaluate functional activity. The M-CIMT program comprised warm-up sessions, M-CIMT protocols, and cool-down exercises, conducted five days a week.
 Results: Following participation in the M-CIMT program, significant improvements were observed in WMFT and MAL scores. The mean pre-test score of 46.60 seconds decreased to a mean post-test score of 16.85 seconds, with highly significant t-values of 14.292 and -51.356 and a p-value of 0.0, indicating a strong correlation between the two datasets. The analysis revealed that M-CIMT effectively enhanced upper extremity function in chronic stroke patients.
 Conclusion: This study highlights the effectiveness of the Modified CIMT protocol, emphasizing repeated use and a distributed practice schedule, in reducing upper-limb impairment and improving upper-limb use and function in chronic stroke patients. The significant improvement in post-test scores underscores the promise of M-CIMT as a valuable approach for upper extremity rehabilitation following chronic stroke, offering hope for enhanced recovery and improved quality of life for affected individuals.
 Keywords: Stroke; Rehabilitation; Upper Extremity; Constraint-Induced Movement Therapy; Motor Activity

Efficacy of ultrasound-guided subacromial bursa steroid injection for treating shoulder pain in post-stroke hemiparetic patients

Purpose: To assess the efficacy of ultrasound-guided subacromial bursa (SAB) steroid injection for treating hemiplegic shoulder pain (HSP) after stroke (CS), as well as its impact on joint mobility, and inflammatory mediators.Methods: Seventy-two (72) patients with CS-related HSP were divided into two groups: study and control groups. The study group received ultrasound-guided SAB injection of triamcinolone acetonide in addition to conventional treatment, while control group received only conventional rehabilitation. Both groups received 4 weeks of treatment and were assessed using pain visual analogue scale (VAS) and passive range of motion (PROM) indices before treatment and at 1, 4, and 12 weeks after treatment. Additionally, the Fugl-Meyer motor function (FMA-U) scale score, activities of daily living (ADL) score, modified Barthel index (MBI), serum IL-1β, IL-6, nitric oxide (NO) levels, and incidence of adverse reactions were assessed before and after 4 weeks of treatment.Results: The study group had a significantly higher total efficacy/effectiveness (86.11 %) compared to control group (53.89 %). Both groups showed initial decreases and subsequent increases in VAS and PROM from week 1 to week 12 after treatment. However, the study group had significantly lower VAS scores, angle of forward flexion, abduction, and external rotation at all time points compared to control group (p < 0.05). At week 4, the study group had significantly higher FMA-U, ADL, and MBI scores, as well as significantly lower IL-1β, IL-6, and NO levels when compared to control group (p < 0.05).Conclusion: Ultrasound-guided SAB steroid injection improves the efficacy of HSP after CS, improves joint mobility, and reduces serum levels of IL-1β, IL-6, and NO. Further large-sample studies with increased sample sizes and longer investigation periods are needed to validate these findings.

Automated Quantifiable Assessments of Sensorimotor Function Using an Instrumented Fragile Object.

Accurate assessment of hand dexterity plays a critical role in informing rehabilitation and care of upper-limb hemiparetic stroke patients. Common upper-limb assessments, such as the Box and Blocks Test and Nine Hole Peg Test, primarily evaluate gross motor function in terms of speed. These assessments neglect an individual's ability to finely regulate grip force, which is critical in activities of daily living, such as manipulating fragile objects. Here we present the Electronic Grip Gauge (EGG), an instrumented fragile object that assesses both gross and fine motor function. Embedded with a load cell, accelerometer, and Hall-effect sensor, the EGG measures grip force, acceleration, and relative position (via magnetic fields) in real time. The EGG can emit an audible "break" sound when the applied grip force exceeds a threshold. The number of breaks, transfer duration, and applied forces are automatically logged in real-time. Using the EGG, we evaluated sensorimotor function in implicit grasping and gentle grasping for the non-paretic and paretic hands of 3 hemiparetic stroke patients. For all participants, the paretic hand took longer to transfer the EGG during implicit grasping. For 2 of 3 participants, grip forces were significantly greater for the paretic hand during gentle grasping. Differences in implicit grasping forces were unique to each participant. This work constitutes an important step towards more widespread and quantitative measures of sensorimotor function, which may ultimately lead to improved personalized rehabilitation and better patient outcomes.

Virtual reality-based exercises to improve balance and hand grip strength in patients with hemiparesis caused by an electrical burn: A randomized controlled study

There are many complications after an electrical burn injury, including neuromuscular defects, paresis or paralysis, Gillian barre syndrome, transverse myelitis, or amyotrophic lateral sclerosis. The aim of this study was to investigate the effect of virtual reality-based exercises on balance and hand grip strength in post electrical burn-induced hemiparetic patients. A randomized control trial pre- and post-experimental design with intra-rater reliability and inter-rater agreement was undertaken. Thirty post-electrical burn-induced hemiparetic patients (19 males and 11 females, aged 15 to 25 years) were randomly allocated into two equal groups (group A and B). Group A (n = 15) received virtual reality-based exercise in addition to the conventional physical therapy program. Group B (n = 15) received conventional physical therapy program only. The treatment was applied 3 sessions per week for 12 consecutive weeks. Posture stability and hand grip strength were measured by the Biodex balance system and handheld dynamometer, respectively. Data was collected prior to the first treatment and at the end of the 12-week trial and all statistical calculations were done using the computer program IBM SPSS. A statistically significant increase in the overall stability index and the power of hand grip strength was observed in both groups after treatment (p < 0.05), especially in group A, which received VR - based exercise training. Thus, group A showed a greater improvement in postural stability and hand grip strength than group B (p < 0.05). Virtual reality-based exercises as well as conventional physical therapy program were effective in improving posture stability and hand grip strength in post electrical burn-induced hemiparetic patients.

Effect of high-intensity laser therapy versus shockwave therapy on selected outcome measures in osteoporotic long-term hemiparetic patients: a randomized control trial

BackgroundThis study aimed to compare the effects of high-intensity laser therapy (HILT) and extracorporeal shock wave therapy (ESWT) in treating consequences of osteoporosis in hemiparetic patients.MethodsA randomized controlled trial was conducted on hemiplegic patients with osteoporosis. They were randomly classified into three equal groups (n = 40 in each group). The control group received medication and traditional physiotherapy programs for stroke patients. The high-intensity laser (HIL) group received the same intervention as the control group in addition to high-intensity laser therapy. The shock wave (SW) group received the same intervention as the control group in addition to shock wave therapy. The three groups received an intervention that lasted 3 sessions/week for 12 weeks). All groups were assessed before and after therapy for the degree of pain, fall risk, and quality of life.ResultsA statistically significant difference (p < 0.05) was found concerning VAS, which had a significant difference in favor of HILT and ESWT groups compared to the control group; however, no significant difference was determined between HIL and SW groups. Regarding the overall stability index, SFBBS, and QUALEFFO-41, there was a significant difference in favor of HIL and SW groups compared to the control group, and a significant difference was found in HIL when compared to SW.ConclusionThe current study indicates that the combined traditional physical therapy and HILT and ESWT have clinical significance in improving osteoporotic long-term hemiparetic patients with more favor to HILT.Trial registration: The study was registered as a clinical trial at ClinicalTrial.gov ID (NCT05616611).

Does Accelerometry at the Centre of Mass Accurately Predict the Gait Energy Expenditure in Patients with Hemiparesis?

The aim of this study was to compare energy expenditure (EE) predicted by accelerometery (EEAcc) with indirect calorimetry (EEMETA) in individuals with hemiparesis. Twenty-four participants (12 with stroke and 12 healthy controls) performed a six-minute walk test (6MWT) during which EEMETA was measured using a portable indirect calorimetry system and EEACC was calculated using Bouten's equation (1993) with data from a three-axis accelerometer positioned between L3 and L4. The median EEMETA was 9.85 [8.18;11.89] W·kg-1 in the stroke group and 5.0 [4.56;5.46] W·kg-1 in the control group. The median EEACC was 8.57 [7.86;11.24] W·kg-1 in the control group and 8.2 [7.05;9.56] W·kg-1 in the stroke group. The EEACC and EEMETA were not significantly correlated in either the control (p = 0.8) or the stroke groups (p = 0.06). The Bland-Altman method showed a mean difference of 1.77 ± 3.65 W·kg-1 between the EEACC and EEMETA in the stroke group and -2.08 ± 1.59 W·kg-1 in the controls. The accuracy of the predicted EE, based on the accelerometer and the equations proposed by Bouten et al., was low in individuals with hemiparesis and impaired gait. This combination (sensor and Bouten's equation) is not yet suitable for use as a stand-alone measure in clinical practice for the evaluation of hemiparetic patients.

Sliding Window Along With EEGNet-Based Prediction of EEG Motor Imagery

The need for repeated calibration and accounting for inter subject variability is a major challenge for the practical applications of a brain-computer interface. The problem becomes more severe when it is applied for the neurorehabilitation of stroke patients where the brain-activation pattern may differ quite a bit as compared to healthy individuals due to the altered neurodynamics because of a lesion. There were several approaches to handle this problem in the past that depend on creating customized features that can be generalized among the individual subjects. Recently, several deep learning architectures came into the picture although they often failed to produce superior accuracy as compared to the traditional approaches and mostly do not follow an end-to-end architecture as they depend on custom features. However, a few of them have the promising ability to create more generalizable features in an end-to-end fashion such as the popular EEGNet architecture. Although EEGNet was applied for decoding stroke patient’s motor imagery (MI) data with limited success it failed to achieve superior performance over the traditional methods. In this study, we have augmented the EEGNet based decoding by introducing a post-processing step called the longest consecutive repetition (LCR) in a sliding window-based approach and named it EEGNet+LCR. The proposed approach was tested on a dataset of 10 hemiparetic stroke patients’ MI data set yielding superior performance against the only EEGNet and a more traditional approach such as common spatial pattern (CSP)+support vector machine (SVM) for both within- and cross-subject decoding of MI signals. We also observed comparable and satisfactory performance of the EEGNet+LCR in both the within- and cross-subject categories which are rarely found in literature making it a promising candidate to realize practically feasible BCI for stroke rehabilitation.

Effects of Training with a Powered Exoskeleton on Cortical Activity Modulation in Hemiparetic Chronic Stroke Patients: A Randomized Controlled Pilot Trial

ObjectivesTo investigate the effects of exoskeleton-assisted gait training in stroke patients. DesignProspective randomized controlled trial. SettingRehabilitation department in a single tertiary hospital. ParticipantsThirty (N=30) chronic stroke patients with Functional Ambulatory Category scale (FAC) between 2 and 4. InterventionPatients were randomly assigned to 1 of 2 groups: training with Healbot G, a wearable powered exoskeleton (Healbot G group; n=15), or treadmill training (control group; n=15). All participants received 30 minutes of training, 10 times per week, for 4 weeks. Outcome MeasurementsThe primary outcome was oxyhemoglobin level changes, representing cortical activity in both motor cortices using functional near-infrared spectroscopy. The secondary outcomes included FAC, Berg Balance Scale, Motricity Index for the lower extremities (MI-Lower), 10-meter walk test, and gait symmetry ratio (spatial step and temporal symmetry ratio). ResultsCompared to the control group, during the entire training session, the pre-training and post-training mean cortical activity, and the amount of increment between pre- and post-training were significantly higher in the Healbot G group (∆mean ± SD; pre-training, 0.245±0.119, post-training, 0.697±0.429, between pre- and post-training, 0.471±0.401μmol, P<.001). There was no significant difference in cortical activity between affected- and unaffected hemispheres after Healbot G training. FAC (∆mean ± SD; 0.35 ± 0.50, P=.012), MI-Lower (∆mean ± SD; 7.01 ± 0.14, P=.001), and spatial step gait symmetry ratio (∆mean ± SD; -0.32 ± 0.25, P=.049) were improved significantly in the Healbot G group. ConclusionExoskeleton-assisted gait training induces cortical modulation effect in both motor cortices, a balanced cortical activation pattern with improvements in spatial step symmetry ratio, walking ability, and voluntary strength.

ID: 219084 The Effects of Transcranial Direct Current Stimulation and Rehab on CVA Patients: Preliminary Results

After strokes, many patients suffer from impaired upper extremity function which adversely affects the performance of activities of daily living [4,5]. Conventional rehabilitation such as task-oriented exercises may not always result in full recovery [2]. Applying Transcranial Direct Current Stimulation (tDCS) with motor training can improve motor recovery and neuroplasticity [1,3,4,6]. This study aims to explore the effects of combined occupational therapy on upper extremity and tDCS on hemiparetic stroke patients. The Cognitive and psychological outcomes will be measured along with physiological outcomes, consisting of motor evoked potential (MEP) amplitude by single-pulse transcranial magnetic stimulation(sTMS). Functional outcomes will be measured by the Fugl-Meyer Assessment.

Therapeutic Effects of Robotic-Exoskeleton-Assisted Gait Rehabilitation and Predictive Factors of Significant Improvements in Stroke Patients: A Randomized Controlled Trial.

Robotic-exoskeleton-assisted gait rehabilitation improves lower limb strength and functions in post-stroke patients. However, the predicting factors of significant improvement are unclear. We recruited 38 post-stroke hemiparetic patients whose stroke onsets were <6 months. They were randomly assigned to two groups: a control group receiving a regular rehabilitation program, and an experimental group receiving in addition a robotic exoskeletal rehabilitation component. After 4 weeks of training, both groups showed significant improvement in the strength and functions of their lower limbs, as well as health-related quality of life. However, the experimental group showed significantly better improvement in the following aspects: knee flexion torque at 60°/s, 6 min walk test distance, and the mental subdomain and the total score on a 12-item Short Form Survey (SF-12). Further logistic regression analyses showed that robotic training was the best predictor of a greater improvement in both the 6 min walk test and the total score on the SF-12. In conclusion, robotic-exoskeleton-assisted gait rehabilitation improved lower limb strength, motor performance, walking speed, and quality of life in these stroke patients.

Designing Ecological Auditory Feedback on Lower Limb Kinematics for Hemiparetic Gait Training.

Auditory feedback has earlier been explored as a tool to enhance patient awareness of gait kinematics during rehabilitation. In this study, we devised and tested a novel set of concurrent feedback paradigms on swing phase kinematics in hemiparetic gait training. We adopted a user-centered design approach, where kinematic data recorded from 15 hemiparetic patients was used to design three feedback algorithms (wading sounds, abstract, musical) based on filtered gyroscopic data from four inexpensive wireless inertial units. The algorithms were tested (hands-on) by a focus group of five physiotherapists. They recommended that the abstract and musical algorithms be discarded due to sound quality and informational ambiguity. After modifying the wading algorithm (as per their feedback), we conducted a feasibility test involving nine hemiparetic patients and seven physiotherapists, where variants of the algorithm were applied to a conventional overground training session. Most patients found the feedback meaningful, enjoyable to use, natural-sounding, and tolerable for the typical training duration. Three patients exhibited immediate improvements in gait quality when the feedback was applied. However, minor gait asymmetries were found to be difficult to perceive in the feedback, and there was variability in receptiveness and motor change among the patients. We believe that our findings can advance current research in inertial sensor-based auditory feedback for motor learning enhancement during neurorehabilitation.

Co-simulation of human digital twins and wearable inertial sensors to analyse gait event estimation.

We propose a co-simulation framework comprising biomechanical human body models and wearable inertial sensor models to analyse gait events dynamically, depending on inertial sensor type, sensor positioning, and processing algorithms. A total of 960 inertial sensors were virtually attached to the lower extremities of a validated biomechanical model and shoe model. Walking of hemiparetic patients was simulated using motion capture data (kinematic simulation). Accelerations and angular velocities were synthesised according to the inertial sensor models. A comprehensive error analysis of detected gait events versus reference gait events of each simulated sensor position across all segments was performed. For gait event detection, we considered 1-, 2-, and 4-phase gait models. Results of hemiparetic patients showed superior gait event estimation performance for a sensor fusion of angular velocity and acceleration data with lower nMAEs (9%) across all sensor positions compared to error estimation with acceleration data only. Depending on algorithm choice and parameterisation, gait event detection performance increased up to 65%. Our results suggest that user personalisation of IMU placement should be pursued as a first priority for gait phase detection, while sensor position variation may be a secondary adaptation target. When comparing rotatory and translatory error components per body segment, larger interquartile ranges of rotatory errors were observed for all phase models i.e., repositioning the sensor around the body segment axis was more harmful than along the limb axis for gait phase detection. The proposed co-simulation framework is suitable for evaluating different sensor modalities, as well as gait event detection algorithms for different gait phase models. The results of our analysis open a new path for utilising biomechanical human digital twins in wearable system design and performance estimation before physical device prototypes are deployed.

New Artificial Intelligence-Integrated Electromyography-Driven Robot Hand for Upper Extremity Rehabilitation of Patients With Stroke: A Randomized, Controlled Trial

Background An artificial intelligence (AI)-integrated electromyography (EMG)-driven robot hand was devised for upper extremity (UE) rehabilitation. This robot detects patients’ intentions to perform finger extension and flexion based on the EMG activities of 3 forearm muscles. Objective This study aimed to assess the effect of this robot in patients with chronic stroke. Methods This was a single-blinded, randomized, controlled trial with a 4-week follow-up period. Twenty patients were assigned to the active (n = 11) and control (n = 9) groups. Patients in the active group received 40 minutes of active finger training with this robot twice a week for 4 weeks. Patients in the control group received passive finger training with the same robot. The Fugl-Meyer assessment of UE motor function (FMA), motor activity log-14 amount of use score (MAL-14 AOU), modified Ashworth scale (MAS), H reflex, and reciprocal inhibition were assessed before, post, and post-4 weeks (post-4w) of intervention. Results FMA was significantly improved at both post (P = .011) and post-4w (P = .021) in the active group. The control group did not show significant improvement in FMA at the post. MAL-14 AOU was improved at the post in the active group (P = .03). In the active group, there were significant improvements in wrist MAS at post (P = .024) and post-4w (P = .026). Conclusions The AI-integrated EMG-driven robot improved UE motor function and spasticity, which persisted for 4 weeks. This robot hand might be useful for UE rehabilitation of patients with stroke. Clinical Trial Registry Name: The effect of robotic rehabilitation using XMM-HR2 for the paretic upper extremity among hemiparetic patients with stroke. Clinical Trial Registration-URL: https://jrct.niph.go.jp/ Unique Identifier: jRCTs032200045.