Impact of Wearable Device-Based Walking Programs on Gait Speed in Older Adults: A Systematic Review and Meta-Analysis.

Abstract

Background As walking abilities are widely affected among the aging population, investigating the effectiveness of wearable device-based walking programs is essential. The intentions of this meta-analysis were to investigate their effects on gait speed among older adults, as well as to include subgroup analysis to evaluate potential effects on individuals with aging-related conditions such as Parkinson's disease (PD) and stroke. Methods Systematic retrieval of Pubmed, The Cochrane Library, Embase and Web of Science databases were searched up to February 2024. Outcomes such as gait speed, balance, cadence, and stride length were extracted and analyzed. Study quality was evaluated using the Rob 2 tool and heterogeneity was tested using I2 statistics through STATA 16. Results Nine studies with 284 participants were analyzed. The intervention group showed a significant improvement in gait speed (weighted mean difference (WMD) 0.12; 95% CI 0.03 to 0.21). There is a subgroup analysis suggesting differential effects: significant improvements in PD and stroke subgroups, but not in the normal aging group. Balance (WMD: 1.93; 95% CI: 0.20 to 3.66) and stride length (WMD: 8.58; 95% CI: 3.04 to 14.12) were also shown to improve, but the heterogeneity across the studies was moderate (I2 = 63.91%). No significant changes were observed in the Timed Up and Go test, Gait Variability, and Step Width. Conclusions Wearable device-based walking programs improve gait speed in older adults, with top notch advantages in the ones tormented by PD or stroke. These findings advocate that such interventions can be a valuable part of individualized treatment strategies in geriatric care, aiming to enhance mobility and usual satisfactory of existence.