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Exploring the Impact of Delayed Neural Feedback on Motor Performance: A Meta-Analysis of Robotic Balance Training Interventions

M. Elsayed, A. Abdelsalhin, M. Mustafa, N. Elmestkawy, O. Hafez, N. Abdeltawab, M. Alomari, M. M. Elsayed (Mansoura, Egypt)

Meeting: 2025 International Congress

Keywords: Parkinson’s

Category: Artificial Intelligence (AI) and Machine Learning

Objective: To evaluate the effect of delayed neural feedback on motor performance by conducting a meta-analysis of robotic balance training interventions in neurological rehabilitation.

Background: Delayed neural feedback has been implicated in altered motor control and rehabilitation outcomes in neurological disorders such as stroke, Parkinson’s disease, and spinal cord injuries. While robotic-assisted balance training aims to optimize motor recovery, the role of feedback latency remains unclear. Understanding its impact is critical for refining rehabilitation strategies and improving motor function.

Method: A systematic review and meta-analysis were conducted following PRISMA guidelines. We searched PubMed, Scopus, Web of Science, and IEEE Xplore for randomized controlled trials (RCTs) and observational studies published up to March 2024. Inclusion criteria required studies investigating robotic balance training with varying neural feedback delays in individuals with neurological impairments. Data were extracted on intervention type, delay duration, motor performance outcomes, and neurophysiological measures. Statistical analysis included pooled effect sizes using a random-effects model.

Results: A total of 22 studies (n = 785 participants) met inclusion criteria. Meta-analysis revealed that short feedback delays (<100 ms) significantly enhanced motor adaptation (Hedges’ g = 0.78, p < 0.01), whereas prolonged delays (>250 ms) impaired balance control and task retention (Hedges’ g = -0.52, p = 0.03). Subgroup analysis indicated that stroke survivors exhibited the greatest sensitivity to feedback delays. Robotic training incorporating adaptive latency adjustments improved gait stability and reaction times by 23% compared to fixed-delay interventions.

Conclusion: Delayed neural feedback significantly influences motor performance in robotic balance training. While short delays enhance adaptation, excessive feedback latency may hinder rehabilitation outcomes. These findings highlight the importance of optimizing feedback timing in robotic therapy to enhance neuromuscular recovery. Future research should explore real-time adaptive feedback mechanisms tailored to individual neurological profiles.

To cite this abstract in AMA style:

M. Elsayed, A. Abdelsalhin, M. Mustafa, N. Elmestkawy, O. Hafez, N. Abdeltawab, M. Alomari, M. M. Elsayed. Exploring the Impact of Delayed Neural Feedback on Motor Performance: A Meta-Analysis of Robotic Balance Training Interventions [abstract]. Mov Disord. 2025; 40 (suppl 1). https://www.mdsabstracts.org/abstract/exploring-the-impact-of-delayed-neural-feedback-on-motor-performance-a-meta-analysis-of-robotic-balance-training-interventions/. Accessed October 5, 2025.
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