Dataset Information

Investigation of Fatigability during Repetitive Robot-Mediated Arm Training in People with Multiple Sclerosis.

ABSTRACT:

Background

People with multiple sclerosis (MS) are encouraged to engage in exercise programs but an increased experience of fatigue may impede sustained participation in training sessions. A high number of movements is, however, needed for obtaining optimal improvements after rehabilitation.

Methods

This cross-sectional study investigated whether people with MS show abnormal fatigability during a robot-mediated upper limb movement trial. Sixteen people with MS and sixteen healthy controls performed five times three minutes of repetitive shoulder anteflexion movements. Movement performance, maximal strength, subjective upper limb fatigue and surface electromyography (median frequency and root mean square of the amplitude of the electromyography (EMG) signal of the anterior deltoid) were recorded during or in-between these exercises. After fifteen minutes of rest, one extra movement bout was performed to investigate how rest influences performance.

Results

A fifteen minutes upper limb movement protocol increased the perceived upper limb fatigue and induced muscle fatigue, given a decline in maximal anteflexion strength and changes of both the amplitude and the median frequency of EMG the anterior deltoid. In contrast, performance during the 3 minutes of anteflexion movements did not decline. There was no relation between changes in subjective fatigue and the changes in the amplitude and the median frequency of the anterior deltoid muscle, however, there was a correlation between the changes in subjective fatigue and changes in strength in people with MS. People with MS with upper limb weakness report more fatigue due to the repetitive movements, than people with MS with normal upper limb strength, who are comparable to healthy controls. The weak group could, however, keep up performance during the 15 minutes of repetitive movements.

Discussion and conclusion

Albeit a protocol of repetitive shoulder anteflexion movements did not elicit a performance decline, fatigue feelings clearly increased in both healthy controls and people with MS, with the largest increase in people with MS with upper limb weakness. Objective fatigability was present in both groups with a decline in the muscle strength and increase of muscle fatigue, shown by changes in the EMG parameters. However, although weak people with multiple sclerosis experienced more fatigue, the objective signs of fatigability were less obvious in weak people with MS, perhaps because this subgroup has central limiting factors, which influence performance from the start of the movements.

SUBMITTER: Severijns D

PROVIDER: S-EPMC4516328 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Investigation of Fatigability during Repetitive Robot-Mediated Arm Training in People with Multiple Sclerosis.

Severijns Deborah D Octavia Johanna Renny JR Kerkhofs Lore L Coninx Karin K Lamers Ilse I Feys Peter P

PloS one 20150727 7

<h4>Background</h4>People with multiple sclerosis (MS) are encouraged to engage in exercise programs but an increased experience of fatigue may impede sustained participation in training sessions. A high number of movements is, however, needed for obtaining optimal improvements after rehabilitation.<h4>Methods</h4>This cross-sectional study investigated whether people with MS show abnormal fatigability during a robot-mediated upper limb movement trial. Sixteen people with MS and sixteen healthy ...[more]

PMID: 26213990

Similar Datasets

Project description:Background and Objectives: Gait disorders represent one of the most disabling aspects in multiple sclerosis (MS) that strongly influence patient quality of life. The improvement of walking ability is a primary goal for rehabilitation treatment. The aim of this study is to evaluate the effectiveness of robot-assisted gait training (RAGT) in association with physiotherapy treatment in patients affected by MS in comparison with ground conventional gait training. Study design: Randomized controlled crossover trial. Materials and Methods: Twenty-seven participants affected by MS with EDSS scores between 3.5 and 7 were enrolled, of whom seventeen completed the study. They received five training sessions per week over five weeks of conventional gait training with (experimental group) or without (control group) the inclusion of RAGT. The patients were prospectively evaluated before and after the first treatment session and, after the crossover phase, before and after the second treatment session. The evaluation was based on the 25-foot walk test (25FW, main outcome), 6 min walk test (6MWT), Tinetti Test, Modified Ashworth Scale, and modified Motricity Index for lower limbs. We also measured disability parameters using Functional Independence Measure and Quality of Life Index, and instrumental kinematic and gait parameters: knee extensor strength, double-time support, step length ratio; 17 patients reached the final evaluation. Results: Both groups significantly improved on gait parameters, motor abilities, and autonomy recovery in daily living activities with generally better results of RAGT over control treatment. In particular, the RAGT group improved more than control group in the 25FW (p = 0.004) and the 6MWT (p = 0.022). Conclusions: RAGT is a valid treatment option that in association with physiotherapy could induce positive effects in MS-correlated gait disorders. Our results showed greater effectiveness in recovering gait speed and resistance than conventional gait training.

Project description:BackgroundRehabilitation robotics is progressing towards developing robots that can be used as advanced tools to augment the role of a therapist. These robots are capable of not only offering more frequent and more accessible therapies but also providing new insights into treatment effectiveness based on their ability to measure interaction parameters. A requirement for having more advanced therapies is to identify how robots can 'adapt' to each individual's needs at different stages of recovery. Hence, our research focused on developing an adaptive interface for the GENTLE/A rehabilitation system. The interface was based on a lead-lag performance model utilising the interaction between the human and the robot. The goal of the present study was to test the adaptability of the GENTLE/A system to the performance of the user.MethodsPoint-to-point movements were executed using the HapticMaster (HM) robotic arm, the main component of the GENTLE/A rehabilitation system. The points were displayed as balls on the screen and some of the points also had a real object, providing a test-bed for the human-robot interaction (HRI) experiment. The HM was operated in various modes to test the adaptability of the GENTLE/A system based on the leading/lagging performance of the user. Thirty-two healthy participants took part in the experiment comprising of a training phase followed by the actual-performance phase.ResultsThe leading or lagging role of the participant could be used successfully to adjust the duration required by that participant to execute point-to-point movements, in various modes of robot operation and under various conditions. The adaptability of the GENTLE/A system was clearly evident from the durations recorded. The regression results showed that the participants required lower execution times with the help from a real object when compared to just a virtual object. The 'reaching away' movements were longer to execute when compared to the 'returning towards' movements irrespective of the influence of the gravity on the direction of the movement.ConclusionsThe GENTLE/A system was able to adapt so that the duration required to execute point-to-point movement was according to the leading or lagging performance of the user with respect to the robot. This adaptability could be useful in the clinical settings when stroke subjects interact with the system and could also serve as an assessment parameter across various interaction sessions. As the system adapts to user input, and as the task becomes easier through practice, the robot would auto-tune for more demanding and challenging interactions. The improvement in performance of the participants in an embedded environment when compared to a virtual environment also shows promise for clinical applicability, to be tested in due time. Studying the physiology of upper arm to understand the muscle groups involved, and their influence on various movements executed during this study forms a key part of our future work.

Project description:BACKGROUND:Electromechanical and robot-assisted arm training devices are used in rehabilitation, and may help to improve arm function after stroke. OBJECTIVES:To assess the effectiveness of electromechanical and robot-assisted arm training for improving activities of daily living, arm function, and arm muscle strength in people after stroke. We also assessed the acceptability and safety of the therapy. SEARCH METHODS:We searched the Cochrane Stroke Group's Trials Register (last searched January 2018), the Cochrane Central Register of Controlled Trials (CENTRAL) (the Cochrane Library 2018, Issue 1), MEDLINE (1950 to January 2018), Embase (1980 to January 2018), CINAHL (1982 to January 2018), AMED (1985 to January 2018), SPORTDiscus (1949 to January 2018), PEDro (searched February 2018), Compendex (1972 to January 2018), and Inspec (1969 to January 2018). We also handsearched relevant conference proceedings, searched trials and research registers, checked reference lists, and contacted trialists, experts, and researchers in our field, as well as manufacturers of commercial devices. SELECTION CRITERIA:Randomised controlled trials comparing electromechanical and robot-assisted arm training for recovery of arm function with other rehabilitation or placebo interventions, or no treatment, for people after stroke. DATA COLLECTION AND ANALYSIS:Two review authors independently selected trials for inclusion, assessed trial quality and risk of bias, used the GRADE approach to assess the quality of the body of evidence, and extracted data. We contacted trialists for additional information. We analysed the results as standardised mean differences (SMDs) for continuous variables and risk differences (RDs) for dichotomous variables. MAIN RESULTS:We included 45 trials (involving 1619 participants) in this update of our review. Electromechanical and robot-assisted arm training improved activities of daily living scores (SMD 0.31, 95% confidence interval (CI) 0.09 to 0.52, P = 0.0005; I² = 59%; 24 studies, 957 participants, high-quality evidence), arm function (SMD 0.32, 95% CI 0.18 to 0.46, P < 0.0001, I² = 36%, 41 studies, 1452 participants, high-quality evidence), and arm muscle strength (SMD 0.46, 95% CI 0.16 to 0.77, P = 0.003, I² = 76%, 23 studies, 826 participants, high-quality evidence). Electromechanical and robot-assisted arm training did not increase the risk of participant dropout (RD 0.00, 95% CI -0.02 to 0.02, P = 0.93, I² = 0%, 45 studies, 1619 participants, high-quality evidence), and adverse events were rare. AUTHORS' CONCLUSIONS:People who receive electromechanical and robot-assisted arm training after stroke might improve their activities of daily living, arm function, and arm muscle strength. However, the results must be interpreted with caution although the quality of the evidence was high, because there were variations between the trials in: the intensity, duration, and amount of training; type of treatment; participant characteristics; and measurements used.

Project description:ObjectivesTo explore the experiences and acceptability of music-cued motor imagery (MCMI), music-cued gait training (MCGT), and combined MCMI and MCGT (MCMI-MCGT) in people with multiple sclerosis (pwMS). We also aimed to explore participants' self-rated health status postintervention and gather recommendations for further programme development.DesignQualitative study alongside the double-blind randomised controlled real and imagined gait training with music-cueing (RIGMUC) multicentre trial of MCMI, MCGT and MCMI-MCGT.SettingPwMS recruited for the RIGMUC trial from Departments of Neurology at Medical Universities of Innsbruck and Graz and Clinic for Rehabilitation Muenster, Austria.ParticipantsAll 132 pwMS with mild to moderate disability randomised into the trial were included in the analysis.MethodsParticipants practised home-based MCMI, MCGT or MCMI-MCGT for 30 min, 4×/week, for 4 weeks. Three trained researchers conducted weekly semistructured telephone interviews during the intervention period, supporting adherence, addressing problems, sharing experiences and assessing intervention acceptability. Follow-up interviews at 4-week postintervention aimed to understand participants' self-rated changes in walking, fatigue and overall health compared with their prestudy condition. Investigator triangulation was employed among the researchers to enhance trustworthiness and credibility.ResultsUsing thematic analysis, we identified five themes: (1) empowerment, (2) remaining in sync, (3) interconnection between imagined and actual walking, (4) sustaining focus and (5) real-world transfer. Participants appreciated and found the imagined and actual MCGT innovative. Problems included concentration issues, early fatigue in advanced disability and difficulty synchronising with music cues. Positive changes in walking, fatigue and overall health postinterventions were reported offering valuable insights for programme development.ConclusionsA participatory study to codevelop a music-cued exercise programme for pwMS seems appropriate as participants appreciated the innovation and effectiveness of both imagined and actual MCGT. Future studies should also investigate pwMS' potential and limitations in enhancing their MCMI abilities with intensive therapist-supported practice.Trial registration numberDRKS00023978.

Dataset Information

Investigation of Fatigability during Repetitive Robot-Mediated Arm Training in People with Multiple Sclerosis.

Background

Methods

Results

Discussion and conclusion

Publications

Investigation of Fatigability during Repetitive Robot-Mediated Arm Training in People with Multiple Sclerosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets