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A Smart Wheeled Walker With Integrated Physiological Monitoring to Improve Mobility in Older Adults: Randomized
Phurichaya Werasirirat1, Pornpimol Muanjai1, Oranat Sukkho1
1Department of Physical Therapy, Faculty of Allied Health Sciences, Burapha University, 169 Longhard Bangsaen Road, Muang District, Saen Suk, Chonburi, 20131, Thailand, 66 18788842.
Background:
Mobility limitations in older adults are associated with an 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 to 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 a randomized order, with a 30-minute washout period. The smart walker integrated photoplethysmography-based heart rate (HR) monitoring, pulse oximetry (oxygen saturation [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 [ETUG]) and fear of falling (Falls Efficacy Scale-International). Statistical analysis was performed using paired comparisons with a significance level of P<.05.
Results:
Thirty (100%) participants completed both intervention conditions and were included in the final analysis. Walking speed was significantly higher with the smart wheeled walker than the standard wheeled walker (mean 28.77, SD 11.94 vs mean 18.14, SD 14.55 m/min; mean difference -10.63 m/min, 95% CI -17.51 to -3.75 m/min; P<.001). The PCI was significantly lower with the smart wheeled walker (mean 0.36, SD 0.38 vs mean 0.69, SD 1.23 beats/m; mean difference 0.33 beats/m, 95% CI 0.06-0.60 beats/m; P=.02), indicating improved walking efficiency. Participants also completed the ETUG test significantly faster with the smart wheeled walker (mean 50.06, SD 24.50 vs mean 64.47, SD 23.04 s; mean difference 14.41 s, 95% CI 2.12-26.70 s; P=.048), indicating improved dynamic balance. Fear of falling did not differ significantly between walker conditions (mean 31.56, SD 9.58 vs mean 32.91, SD 10.37; mean difference 1.35, 95% CI -3.81 to 6.51; P=.62).
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.
