Dataset Information

Decoding upper limb residual muscle activity in severe chronic stroke.

ABSTRACT:

Objective

Stroke is a leading cause of long-term motor disability. Stroke patients with severe hand weakness do not profit from rehabilitative treatments. Recently, brain-controlled robotics and sequential functional electrical stimulation allowed some improvement. However, for such therapies to succeed, it is required to decode patients' intentions for different arm movements. Here, we evaluated whether residual muscle activity could be used to predict movements from paralyzed joints in severely impaired chronic stroke patients.

Methods

Muscle activity was recorded with surface-electromyography (EMG) in 41 patients, with severe hand weakness (Fugl-Meyer Assessment [FMA] hand subscores of 2.93 ± 2.7), in order to decode their intention to perform six different motions of the affected arm, required for voluntary muscle activity and to control neuroprostheses. Decoding of paretic and nonparetic muscle activity was performed using a feed-forward neural network classifier. The contribution of each muscle to the intended movement was determined.

Results

Decoding of up to six arm movements was accurate (>65%) in more than 97% of nonparetic and 46% of paretic muscles.

Interpretation

These results demonstrate that some level of neuronal innervation to the paretic muscle remains preserved and can be used to implement neurorehabilitative treatments in 46% of patients with severe paralysis and extensive cortical and/or subcortical lesions. Such decoding may allow these patients for the first time after stroke to control different motions of arm prostheses through muscle-triggered rehabilitative treatments.

SUBMITTER: Ramos-Murguialday A

PROVIDER: S-EPMC4301668 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Publications

Decoding upper limb residual muscle activity in severe chronic stroke.

Ramos-Murguialday Ander A García-Cossio Eliana E Walter Armin A Cho Woosang W Broetz Doris D Bogdan Martin M Cohen Leonardo G LG Birbaumer Niels N

Annals of clinical and translational neurology 20141209 1

<h4>Objective</h4>Stroke is a leading cause of long-term motor disability. Stroke patients with severe hand weakness do not profit from rehabilitative treatments. Recently, brain-controlled robotics and sequential functional electrical stimulation allowed some improvement. However, for such therapies to succeed, it is required to decode patients' intentions for different arm movements. Here, we evaluated whether residual muscle activity could be used to predict movements from paralyzed joints in ...[more]

PMID: 25642429

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Project description:Upper limb motor deficits in severe stroke survivors often remain unresolved over extended time periods. Novel neurotechnologies have the potential to significantly support upper limb motor restoration in severely impaired stroke individuals. Here, we review recent controlled clinical studies and reviews focusing on the mechanisms of action and effectiveness of single and combined technology-aided interventions for upper limb motor rehabilitation after stroke, including robotics, muscular electrical stimulation, brain stimulation and brain computer/machine interfaces. We aim at identifying possible guidance for the optimal use of these new technologies to enhance upper limb motor recovery especially in severe chronic stroke patients. We found that the current literature does not provide enough evidence to support strict guidelines, because of the variability of the procedures for each intervention and of the heterogeneity of the stroke population. The present results confirm that neurotechnology-aided upper limb rehabilitation is promising for severe chronic stroke patients, but the combination of interventions often lacks understanding of single intervention mechanisms of action, which may not reflect the summation of single intervention's effectiveness. Stroke rehabilitation is a long and complex process, and one single intervention administrated in a short time interval cannot have a large impact for motor recovery, especially in severely impaired patients. To design personalized interventions combining or proposing different interventions in sequence, it is necessary to have an excellent understanding of the mechanisms determining the effectiveness of a single treatment in this heterogeneous population of stroke patients. We encourage the identification of objective biomarkers for stroke recovery for patients' stratification and to tailor treatments. Furthermore, the advantage of longitudinal personalized trial designs compared to classical double-blind placebo-controlled clinical trials as the basis for precise personalized stroke rehabilitation medicine is discussed. Finally, we also promote the necessary conceptual change from 'one-suits-all' treatments within in-patient clinical rehabilitation set-ups towards personalized home-based treatment strategies, by adopting novel technologies merging rehabilitation and motor assistance, including implantable ones.

Project description:Introduction Robotic therapy allow to propose sessions of controlled and identical exercises, customizing settings, and characteristics on the individual patient. The effectiveness of robotic assisted therapy is still under study and the use of robots in clinical practice is still limited. Moreover, the possibility of treatment at home allows to reduce the economic costs and time to be borne by the patient and the caregiver and is a valid tool during periods of pandemic such as covid. The aim of this study is to assess whether a robotic home-based treatment rehabilitation using the iCONE robotic device has effects on a stroke population, despite the chronic condition of patients involved and the absence of a therapist next to the patient while performing the exercises. Materials and methods All patients underwent an initial (T0) and final (T1) assessment with the iCONE robotic device and clinical scales. After T0 evaluation, the robot was delivered to the patient's home for 10 days of at-home treatment (5 days a week for 2 weeks). Results Comparison between T0 and T1 evaluations revealed some significant improvements in robot-evaluated indices such as Independence and Size for the Circle Drawing exercise and Movement Duration for Point-to-Point exercise, but also in the MAS of the elbow. From the analysis of the acceptability questionnaire, a general appreciation of the robot emerged: patients spontaneously asked for the addition of further sessions and to continue therapy. Discussion Telerehabilitation of patients suffering from a chronic stroke is an area that is still little explored. From our experience, this is one of the first studies to carry out a telerehabilitation with these characteristics. The use of robots can become a method to reduce the rehabilitation health costs, to ensure continuity of care, and to arrive in more distant places or where the availability of resources is limited. Conclusion From the data obtained, this rehabilitation seems to be promising for this population. Moreover, promoting the recovery of the upper limb, iCONE can improve patient's quality of life. It would be interesting to conduct RCT studies to compare a conventional treatment in structure with a robotic telematics treatment.

Project description:Background: The combined use of Robot-assisted UL training and Botulinum toxin (BoNT) appear to be a promising therapeutic synergism to improve UL function in chronic stroke patients. Objective: To evaluate the effects of Robot-assisted UL training on UL spasticity, function, muscle strength and the electromyographic UL muscles activity in chronic stroke patients treated with Botulinum toxin. Methods: This single-blind, randomized, controlled trial involved 32 chronic stroke outpatients with UL spastic hemiparesis. The experimental group (n = 16) received robot-assisted UL training and BoNT treatment. The control group (n = 16) received conventional treatment combined with BoNT treatment. Training protocols lasted for 5 weeks (45 min/session, two sessions/week). Before and after rehabilitation, a blinded rater evaluated patients. The primary outcome was the Modified Ashworth Scale (MAS). Secondary outcomes were the Fugl-Meyer Assessment Scale (FMA) and the Medical Research Council Scale (MRC). The electromyographic activity of 5 UL muscles during the "hand-to-mouth" task was explored only in the experimental group and 14 healthy age-matched controls using a surface Electromyography (EMGs). Results: No significant between-group differences on the MAS and FMA were measured. The experimental group reported significantly greater improvements on UL muscle strength (p = 0.004; Cohen's d = 0.49), shoulder abduction (p = 0.039; Cohen's d = 0.42), external rotation (p = 0.019; Cohen's d = 0.72), and elbow flexion (p = 0.043; Cohen's d = 1.15) than the control group. Preliminary observation of muscular activity showed a different enhancement of the biceps brachii activation after the robot-assisted training. Conclusions: Robot-assisted training is as effective as conventional training on muscle tone reduction when combined with Botulinum toxin in chronic stroke patients with UL spasticity. However, only the robot-assisted UL training contributed to improving muscle strength. The single-group analysis and the qualitative inspection of sEMG data performed in the experimental group showed improvement in the agonist muscles activity during the hand-to-mouth task. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03590314.

Dataset Information

Decoding upper limb residual muscle activity in severe chronic stroke.

Objective

Methods

Results

Interpretation

Publications

Decoding upper limb residual muscle activity in severe chronic stroke.

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