Effects of Augmented Reality Dual-Task Training with ChatGPT-Assisted Development on Strength, Balance, Spatiotemporal Gait Parameters, and Fall-Related Self-Efficacy in Patients with Chronic Stroke: A Randomized Controlled Trial.

IF 2 4区 医学 Q3 CLINICAL NEUROLOGY
NeuroRehabilitation Pub Date : 2026-08-01 Epub Date: 2026-05-16 DOI:10.1177/10538135261449483
Sangyong Han, Jeongeun Yoon, Donghwan Park
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引用次数: 0

Abstract

BackgroundDual-task and augmented reality (AR)-based interventions have been used to improve balance and gait in patients with stroke; however, evidence for AR programs developed using accessible approaches such as ChatGPT-assisted programming remains limited.ObjectiveThis study aimed to investigate the effects of ChatGPT-assisted AR dual-task training on muscle strength, balance, gait parameters, and fall-related self-efficacy in patients with chronic stroke.MethodsTwenty-eight patients with chronic stroke were randomly assigned to an experimental group receiving ChatGPT-assisted AR dual-task training or a control group receiving lunge training combined with a throwing task. Both groups trained for 10 min per session, five times per week for four weeks. Primary outcomes were lower-limb strength and balance (static and dynamic). Secondary outcomes included gait parameters and fall-related self-efficacy. Gait speed and step length were measured using the GAITRite system, and step-length symmetry was calculated using a symmetry index derived from paretic and nonparetic step lengths. Group × time interactions were analyzed using mixed-design ANOVA.ResultsSignificant group × time interactions were observed for most primary and secondary outcomes (p < 0.05), in favor of the experimental group; however, the interaction for paretic step length was not statistically significant. Notably, improvement in dynamic balance, as assessed by the timed up and go test, exceeded the minimal clinically important difference in the experimental group.ConclusionsChatGPT-assisted AR dual-task training improved muscle strength, balance, gait performance, and fall-related self-efficacy more than conventional dual-task training, providing preliminary evidence of short-term benefits for ambulatory patients with chronic stroke.

增强现实双任务训练与chatgpt辅助发展对慢性脑卒中患者力量、平衡、时空步态参数和跌倒相关自我效能的影响:一项随机对照试验
基于双任务和增强现实(AR)的干预措施已被用于改善中风患者的平衡和步态;然而,使用chatgpt辅助编程等可访问方法开发AR程序的证据仍然有限。目的探讨chatgpt辅助AR双任务训练对慢性脑卒中患者肌力、平衡、步态参数和跌倒相关自我效能的影响。方法将28例慢性脑卒中患者随机分为实验组和对照组,实验组接受chatgpt辅助AR双任务训练,对照组接受弓步训练和投掷任务训练。两组每次训练10分钟,每周训练5次,持续4周。主要结局是下肢力量和平衡(静态和动态)。次要结局包括步态参数和跌倒相关的自我效能。使用GAITRite系统测量步态速度和步长,并使用由pareg和non - pareg步长导出的对称指数计算步长对称性。采用混合设计方差分析分析组×时间交互作用。结果在大多数主要和次要结局中观察到显著的组×时间相互作用(p
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来源期刊
NeuroRehabilitation
NeuroRehabilitation CLINICAL NEUROLOGY-REHABILITATION
CiteScore
3.20
自引率
0.00%
发文量
178
审稿时长
6-12 weeks
期刊介绍: NeuroRehabilitation, an international, interdisciplinary, peer-reviewed journal, publishes manuscripts focused on scientifically based, practical information relevant to all aspects of neurologic rehabilitation. We publish unsolicited papers detailing original work/research that covers the full life span and range of neurological disabilities including stroke, spinal cord injury, traumatic brain injury, neuromuscular disease and other neurological disorders. We also publish thematically organized issues that focus on specific clinical disorders, types of therapy and age groups. Proposals for thematic issues and suggestions for issue editors are welcomed.
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