The Effects of Unilateral Versus Bilateral Motor Training on Upper Limb Function in Adults with Chronic Stroke: A Systematic Review

Richardson, Mark; Tears, Craig; Morris, Anna; Alexanders, Jenny

doi:10.1016/j.jstrokecerebrovasdis.2021.105617

Cited by 11 publications

(13 citation statements)

References 44 publications

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“…To obtain the optimal hyperparameters such as epoch, batch size, and the number of neurons in LSTM cells, a grid of parameter values with epoch in [50, 100, 150, 200], batch size in [8,16,32,64], and the number of neurons in [16,32,64] were defined. The best parameters were determined by grid search techniques for the highest cross-validation score.…”

Section: Decoding Modelmentioning

confidence: 99%

“…Two hands are mostly required to be used simultaneously to manipulate an object or perform a task [14]. Bilateral coordination training plays an irreplaceable role compared with unilateral training in robot-assisted rehabilitation and thus has been attracting lots of attention [15,16]. Furthermore, direction decoding is one of the most popular BCI topics to achieve independent multidimensional control, which can be used in many rehabilitation applications [17].…”

Section: Introductionmentioning

confidence: 99%

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Decoding Coordinated Directions of Bimanual Movements From EEG Signals

Zhang

Song

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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Bimanual coordination is common in human daily life, whereas current research focused mainly on decoding unimanual movement from electroencephalogram (EEG) signals. Here we developed a brain-computer interface (BCI) paradigm of task-oriented bimanual movements to decode coordinated directions from movement-related cortical potentials (MRCPs) of EEG. Eight healthy subjects participated in the target-reaching task, including (1) performing leftward, midward, and rightward bimanual movements, and (2) performing leftward and rightward unimanual movements. A combined deep learning model of convolution neural network and bidirectional long short-term memory network was proposed to classify movement directions from EEG. Results showed that the average peak classification accuracy for three coordinated directions of bimanual movements reached 73.39 ± 6.35%. The binary classification accuracies achieved 80.24 ± 6.25, 82.62 ± 7.82, and 86.28 ± 5.50% for leftward versus midward, rightward versus midward and leftward versus rightward, respectively. We also compared the binary classification (leftward versus rightward) of bimanual, left-hand, and right-hand movements, and accuracies achieved 86.28 ± 5.50%, 75.67 ± 7.18%, and 77.79 ± 5.65%, respectively. The results indicated the feasibility of decoding human coordinated directions of task-oriented bimanual movements from EEG.

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Section: Decoding Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Decoding Coordinated Directions of Bimanual Movements From EEG Signals

Zhang

Song

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…One strategy of MT involves actively synchronizing the affected limb with the mirror reflection of the unaffected limb, thus considering it as a form of BAT (Toh and Fong, 2012 ). Most of the previous systematic reviews examining the effectiveness of BAT excluded MT (Van Delden et al, 2012 ; Chen et al, 2019 ; Richardson et al, 2021 ). However, MT is cost-friendly, simple, and relatively less labor-intensive, and its effectiveness is of interest to be examined with other types of BAT.…”

Section: Methodsmentioning

confidence: 99%

“…However, the results should be cautiously interpreted since these reviews included non-RCTs, and some of the included studies did not comprise a comparison group, rendering it difficult to draw robust conclusions. In contrast, other reviews identified contradictory findings, claiming that BAT was similar or inferior to conventional therapy (CT) or UAT (Coupar et al, 2010 ; Van Delden et al, 2012 ; Lee et al, 2017b ; Richardson et al, 2021 ). A recently published systematic review highlighted that UAT and BAT improved paretic UE function equivocally in adults with chronic stroke.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness and Success Factors of Bilateral Arm Training After Stroke: A Systematic Review and Meta-Analysis

Chen

Qiu

Bassile

et al. 2022

Front. Aging Neurosci.

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Bilateral arm training (BAT) presents as a promising approach in upper extremity (UE) rehabilitation after a stroke as it may facilitate neuroplasticity. However, the effectiveness of BAT is inconclusive, and no systematic reviews and meta-analyses have investigated the impact of different factors on the outcomes of BAT. This systematic review and meta-analysis aimed to (1) compare the effects of bilateral arm training (BAT) with unilateral arm training (UAT) and conventional therapy (CT) on the upper limb (UL) motor impairments and functional performance post-stroke, and (2) investigate the different contributing factors that may influence the success of BAT. A comprehensive literature search was performed in five databases. Randomized control trials (RCTs) that met inclusion criteria were selected and assessed for methodological qualities. Data relating to outcome measures, characteristics of participants (stroke chronicity and severity), and features of intervention (type of BAT and dose) were extracted for meta-analysis. With 25 RCTs meeting the inclusion criteria, BAT demonstrated significantly greater improvements in motor impairments as measured by Fugl-Meyer Assessment of Upper Extremity (FMA-UE) than CT (MD = 3.94, p = < 0.001), but not in functional performance as measured by the pooled outcomes of Action Research Arm Test (ARAT), Box and Block Test (BBT), and the time component of Motor Function Test (WMFT-time) (SMD = 0.28, p = 0.313). The superior motor impairment effects of BAT were associated with recruiting mildly impaired individuals in the chronic phase of stroke (MD = 6.71, p < 0.001), and applying a higher dose of intervention (MD = 6.52, p < 0.001). Subgroup analysis showed that bilateral functional task training (BFTT) improves both motor impairments (MD = 7.84, p < 0.001) and functional performance (SMD = 1.02, p = 0.049). No significant differences were detected between BAT and UAT for motor impairment (MD = −0.90, p = 0.681) or functional performance (SMD = −0.09, p = 0.457). Thus, our meta-analysis indicates that BAT may be more beneficial than CT in addressing post-stroke UL motor impairment, particularly in the chronic phase with mild UL paresis. The success of BAT may be dose-dependent, and higher doses of intervention may be required. BFTT appears to be a valuable form of BAT that could be integrated into stroke rehabilitation programs. BAT and UAT are generally equivalent in improving UL motor impairments and functional performance.

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“…Rehabilitation to improve and maintain patients' functions plays a critical role in the recovery process [ 8 ]. Many rehabilitative therapies have been applied to improve UL function, such as robot-assisted therapy [ 9 ], virtual reality [ 10 ], mirror therapy [ 11 ], music playing [ 12 ], transcranial direct current stimulation [ 13 ], motor imagery [ 14 ], bilateral motor training [ 15 ], task-oriented training (TOT) [ 16 ], and constraint-induced movement therapy [ 17 ]. Among these approaches, TOT [ 18 ] and robot-assisted training are reported to be effective for improving patients' poststroke abilities to execute activities of daily living (ADL) and their UL function [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

The Effect of Applying Robot-Assisted Task-Oriented Training Using Human-Robot Collaborative Interaction Force Control Technology on Upper Limb Function in Stroke Patients: Preliminary Findings

Lin

et al. 2021

BioMed Research International

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Stroke is one of the leading causes of death and the primary cause of acquired disability worldwide. Many stroke survivors have difficulty using their upper limbs, which have important functional roles in the performance of daily life activities. Consequently, the independence and quality of life of most stroke patients are reduced. Robot-assisted therapy is an effective intervention for improving the upper limb function of individuals with stroke. Human-robot collaborative interaction force control technology is critical for improving the flexibility and followability of the robot’s motion, thereby improving rehabilitation training outcomes. However, there are few reports on the effect of robot-assisted rehabilitative training on upper limb function. We applied this technology using a robot to assist patients with task-oriented training. Posttreatment changes in Fugl-Meyer and modified Barthel index (MBI) scores were assessed to determine whether this technology could improve the upper limb function of stroke patients. One healthy adult and five stroke patients, respectively, participated in functional and clinical experiments. The MBI and Fugl-Meyer scores of the five patients in the clinical experiments showed significant improvements after the intervention. The experimental results indicate that human-robot collaborative interaction force control technology is valuable for improving robots’ properties and patients’ recovery. This trial was registered in the Chinese clinical trial registry (ChiCTR2000038676).

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The Effects of Unilateral Versus Bilateral Motor Training on Upper Limb Function in Adults with Chronic Stroke: A Systematic Review

Cited by 11 publications

References 44 publications

Decoding Coordinated Directions of Bimanual Movements From EEG Signals

Decoding Coordinated Directions of Bimanual Movements From EEG Signals

Effectiveness and Success Factors of Bilateral Arm Training After Stroke: A Systematic Review and Meta-Analysis

The Effect of Applying Robot-Assisted Task-Oriented Training Using Human-Robot Collaborative Interaction Force Control Technology on Upper Limb Function in Stroke Patients: Preliminary Findings

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