Accepted for/Published in: JMIR Aging
Date Submitted: Apr 26, 2026
Open Peer Review Period: Jun 9, 2026 - Aug 4, 2026
Date Accepted: Aug 2, 2026
(closed for review but you can still tweet)
A Smart Wheeled Walker With Integrated Physiological Monitoring to Improve Mobility in Older Adults: A Randomized Crossover Trial
ABSTRACT
Background:
Mobility limitations in older adults are associated with increased physiological cost of walking, reduced functional independence, and elevated fall risk. Conventional wheeled walkers improve stability but lack real-time physiological monitoring and safety feedback. Digital health enabled assistive devices integrating physiological monitoring and fall detection may enhance mobility performance and safety.
Objective:
This study aimed to evaluate the short term effects of a smart wheeled walker equipped with real-time physiological monitoring and fall detection compared with a standard wheeled walker in improving walking efficiency, dynamic balance, and fear of falling among community-dwelling older adults.
Methods:
A single-blind randomized crossover trial was conducted in 30 community-dwelling older adults aged 65–80 years with mild balance impairment (Timed Up and Go >13.5 seconds). Participants completed walking trials using both a standard wheeled walker and a smart wheeled walker in randomized order, with a 30-minute washout period. The smart walker integrated photoplethysmography based heart rate monitoring, pulse oximetry (SpO₂), and a tilt-based fall detection system with mobile alert functionality. The primary outcome was walking efficiency assessed using the Physiological Cost Index (PCI). Secondary outcomes included dynamic balance (Expanded Timed Up and Go) and fear of falling (Falls Efficacy Scale-International). Statistical analysis was performed using paired comparisons with a significance level of p < 0.05
Results:
Thirty participants (100%) completed both intervention conditions and were included in the final analysis. Walking speed was significantly higher with the smart wheeled walker than with the standard wheeled walker (28.77 ± 11.94 vs 18.14 ± 14.55 m/min; mean difference −10.63 m/min, 95% CI −17.51 to −3.75; p <0.001). The Physiological Cost Index was significantly lower with the smart wheeled walker (0.36 ± 0.38 vs 0.69 ± 1.23 beats/m; mean difference 0.33, 95% CI 0.06–0.60; p=0.017), indicating improved walking efficiency. Participants also completed the Expanded Timed Up and Go test significantly faster with the smart wheeled walker (50.06 ± 24.50 vs 64.47 ± 23.04 seconds; mean difference 14.41 seconds, 95% CI 2.12–26.70; p=0.048), indicating improved dynamic balance. Fear of falling did not differ significantly between walker conditions (31.56 ± 9.58 vs 32.91 ± 10.37; mean difference 1.35, 95% CI −3.81 to 6.51; p=0.624).
Conclusions:
A smart wheeled walker integrating real-time physiological monitoring and fall detection significantly improved walking efficiency and dynamic balance during short-term supervised testing in community-dwelling older adults. These findings support the potential clinical value of digital health enabled mobility aids. Further longitudinal studies conducted in real-world settings are warranted to evaluate long-term mobility, fall prevention, independent use, and comprehensive device safety. Clinical Trial: Thai Clinical Trials Registry TCTR20250302008.
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