| Literature DB >> 36188915 |
Kailynn Mannella1, Alan C Cudlip1, Michael W R Holmes1.
Abstract
Muscular weakness and loss of motor function are common symptoms of multiple sclerosis. Robotic rehabilitation can improve sensorimotor function and motor control in this population. However, many studies using robotics for rehabilitation have overlooked changes in muscular strength, despite research demonstrating its utility in combating functional impairments. The purpose of this scoping review was to critically examine changes in muscular strength following robotic rehabilitation interventions for individuals with multiple sclerosis. A literature search of five databases was conducted and search terms included a combination of three primary terms: robotic rehabilitation/training, muscular strength, and multiple sclerosis. Thirty one articles were found, and following inclusion criteria, 5 remained for further investigation. Although muscular strength was not the primary targeted outcome of the training for any of the included articles, increases in muscular strength were present in most of the studies suggesting that robotic therapy with a resistive load can be an effective alternative to resistance training for increasing muscular strength. Outcome measures of isometric knee-extensor force (kg) (right: p < 0.05, left: p < 0.05), isometric knee flexion and extension torque (Nm) (p < 0.05), ankle dorsiflexion and plantarflexion torque (Nm) (all p < 0.05) and handgrip force (kg) (p < 0.05) all improved following a robotic training intervention. These adaptations occurred with sustained low resistive loads of hand grip or during gait training. This scoping review concludes that, despite a lack of studies focusing on strength, there is evidence robotics is a useful modality to improve muscular strength in combination with motor control and neuromotor improvements. A call for more studies to document changes in strength during robotic rehabilitation protocols is warranted.Entities:
Keywords: multiple sclerosis; neurorehabilitation; rehabilitation; robotics; strength
Year: 2022 PMID: 36188915 PMCID: PMC9397874 DOI: 10.3389/fresc.2022.882614
Source DB: PubMed Journal: Front Rehabil Sci ISSN: 2673-6861
Figure 1PRISMA flow-chart of literature search strategy and results.
Article quality assessment using Downs and Black checklist.
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| Beer et al. ( | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | U | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 16 |
| Feys et al. ( | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | U | 13 |
| Lee et al. ( | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | U | U | 0 | 1 | 1 | U | 0 | 1 | 11 |
| Lyp et al. ( | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | U | U | 1 | 1 | 1 | U | U | 1 | 12 |
| Maris et al. ( | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | U | 0 | 1 | 1 | 1 | U | 0 | 1 | 11 |
1, “yes” 0, “no”; U, “unable to determine”.
Risk of bias assessment using Cochrane Handbook for Systematic Reviews of Interventions.
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| Beer et al. ( | L | L | L | L | L | L |
| Feys et al. ( | L | L | L | L | L | L |
| Lee et al. ( | L | L | L | L | L | L |
| Lyp et al. ( | L | L | L | S | L | S |
| Maris et al. ( | L | L | L | L | L | L |
L, “low risk”; H, “high risk”; S, “some concerns”.
Bias arising from the randomization process, (2) bias due to deviations from intended interventions, (3) bias due to missing outcome data, (4) bias in measurement of the outcome, (5) bias in selection of the reported result.
Summary of extracted articles included in this re.
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| Beer et al. ( | To evaluate feasibility and perform an explanatory analysis of the efficacy of robotic gait training in MS patients with severe walking disabilities. | Exp | 14 | 6.0-7.5 | 15 ± 8 | RR: 2 |
| Lyp et al. ( | To examine the effect of a robot-assisted body weight supported treadmill training on the walking ability of MS patients with impaired gait. | Exp | 20 | NR | NR | RR: 7 |
| Lee et al. ( | To perform and evaluate the efficacy of a 6-week robot-assisted training program for the treatment of ankle sensorimotor function in MS patients with lower limb impairments. | Exp | 6 | 5.2 ± 2.5 | 16.0 ± 6.5 | NR |
| Feys et al. ( | To investigate the effects of additional robot-supported upper limb training in persons with MS compared to conventional treatment only. | Exp | 17 | 8.0 | 25 | NR |
| Maris et al. ( | To investigate proof-of-concept efficacy of an individualized, robot-mediated training regime for people with MS and stroke patients. | Exp | 13 | 6.5 | 17 | RR: 5 |
Detailed data extraction from included articles.
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| Beer et al. ( | Lokomat | 5 | 15 | 60 | Knee-extensor strength— | Right: | Right: | 0.47 | 6-month: |
| Lyp et al. ( | Lokomat | 2 | 12 | 35 | Flexion/extension muscles of the hip and knee joints (torque, Nm) | NR | Δ Torque | NR | No follow-up |
| Lee et al. ( | Intellistretch | 3 | 18 | 45 | Dorsiflexion and plantarflexion MVC (Nm) | Dorsiflexion: | Dorsiflexion: | 0.93 | 6-week: |
| Feys et al. ( | Haptic Master | 3 | 24 | 30 | Handgrip strength (kg) | 21.3 ± 12.0 | 21.0 ± 10.7 | 0.02 | No follow-up |
| Maris et al. ( | Haptic Master with | 5 | 10 | 30 | Handgrip strength (kg) | Handgrip: | Handgrip: | 0.15 | 3-month: |
Intervention volume, pre- post-intervention strength measurement results and effect size are reported. VAS; visual analog scale, NR; not reported.