Evidence Hub

Effects of Robot-Assisted Therapy for the Upper Limb After Stroke

Veerbeek JM, Langbroek-Amersfoort AC, van Wegen EE, Meskers CG, Kwakkel G

Neurorehabilitation and neural repair, 2017

1,362 participants

Abstract

BACKGROUND: Robot technology for poststroke rehabilitation is developing rapidly. A number of new randomized controlled trials (RCTs) have investigated the effects of robot-assisted therapy for the paretic upper limb (RT-UL).

OBJECTIVE: To systematically review the effects of poststroke RT-UL on measures of motor control of the paretic arm, muscle strength and tone, upper limb capacity, and basic activities of daily living (ADL) in comparison with nonrobotic treatment.

METHODS: Relevant RCTs were identified in electronic searches. Meta-analyses were performed for measures of motor control (eg, Fugl-Meyer Assessment of the arm; FMA arm), muscle strength and tone, upper limb capacity, and basic ADL. Subgroup analyses were applied for the number of joints involved, robot type, timing poststroke, and treatment contrast.

RESULTS: Forty-four RCTs (N = 1362) were included. No serious adverse events were reported. Meta-analyses of 38 trials (N = 1206) showed significant but small improvements in motor control (~2 points FMA arm) and muscle strength of the paretic arm and a negative effect on muscle tone. No effects were found for upper limb capacity and basic ADL. Shoulder/elbow robotics showed small but significant effects on motor control and muscle strength, while elbow/wrist robotics had small but significant effects on motor control.

CONCLUSIONS: RT-UL allows patients to increase the number of repetitions and hence intensity of practice poststroke, and appears to be a safe…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 1,362 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free