Effectiveness of robot-assisted task-oriented training intervention for upper limb and daily living skills in stroke patients: A meta-analysis
2025

Effectiveness of Robot-Assisted Training for Stroke Patients

Sample size: 574 publication 20 minutes Evidence: moderate

Author Information

Author(s): Jin Chengzhu, Chen Yonghuan, Ma Yuanyuan

Primary Institution: Physical education College, Yanbian University, Yanji, China

Hypothesis

This study aims to determine the intervention effects of robot-assisted task-oriented training on enhancing the upper limb function and daily living skills of stroke patients.

Conclusion

Robot-assisted task-oriented training significantly enhances the rehabilitation of upper limb function and the recovery of daily living skills in stroke patients.

Supporting Evidence

  • Robot-assisted training significantly improved Fugl-Meyer Assessment-Upper Extremity scores compared to the control group.
  • Robot-assisted training demonstrated a significant effect on the Modified Barthel Index scores.
  • Subgroup analyses revealed no significant sources of high heterogeneity.

Takeaway

Using robots to help stroke patients practice daily tasks can make their arms work better and help them do everyday things more easily.

Methodology

A systematic search was conducted across multiple databases, yielding 15 studies with 574 samples for meta-analysis.

Potential Biases

The included studies were at risk of bias regarding randomization, allocation concealment, and blinding.

Limitations

The included studies exhibited significant heterogeneity, and the variety of robot types used may affect the generalizability of the results.

Participant Demographics

The study population consisted of stroke patients, with a total sample size of 574 participants, evenly distributed between experimental and control groups.

Statistical Information

P-Value

0.76 (Begg’s test), 0.93 (Egger’s test)

Confidence Interval

95% CI (0.57, 1.45) for FMA-UE, 95% CI (0.41, 0.82) for MBI

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1371/journal.pone.0316633

Want to read the original?

Access the complete publication on the publisher's website

View Original Publication