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 compared to a standard wheeled walker.
Key Findings
Results
Walking speed was significantly higher with the smart wheeled walker than the standard wheeled walker.
Mean walking speed was 28.77 (SD 11.94) m/min with the smart wheeled walker versus 18.14 (SD 14.55) m/min with the standard wheeled walker.
Mean difference was -10.63 m/min (95% CI -17.51 to -3.75 m/min; P<.001).
Study involved 30 community-dwelling older adults aged 65 to 80 years with mild balance impairment (Timed Up and Go >13.5 seconds).
A single-blind randomized crossover design was used with a 30-minute washout period between conditions.
Results
Walking efficiency, measured by the Physiological Cost Index (PCI), was significantly improved with the smart wheeled walker.
Mean PCI was 0.36 (SD 0.38) beats/m with the smart wheeled walker versus 0.69 (SD 1.23) beats/m with the standard wheeled walker.
Mean difference was 0.33 beats/m (95% CI 0.06-0.60 beats/m; P=.02).
A lower PCI value indicates improved walking efficiency.
PCI was the primary outcome measure of the study.
Results
Dynamic balance, assessed using the Expanded Timed Up and Go (ETUG) test, was significantly better with the smart wheeled walker.
Participants completed the ETUG test in a mean of 50.06 (SD 24.50) seconds with the smart wheeled walker versus 64.47 (SD 23.04) seconds with the standard wheeled walker.
Mean difference was 14.41 seconds (95% CI 2.12-26.70 s; P=.048).
ETUG was a secondary outcome measure.
Faster completion of the ETUG test indicates improved dynamic balance.
Results
Fear of falling did not differ significantly between the smart wheeled walker and standard wheeled walker conditions.
Mean Falls Efficacy Scale-International score was 31.56 (SD 9.58) with the smart wheeled walker versus 32.91 (SD 10.37) with the standard wheeled walker.
Mean difference was 1.35 (95% CI -3.81 to 6.51; P=.62), which was not statistically significant.
Fear of falling was a secondary outcome measure assessed using the Falls Efficacy Scale-International.
Methods
The smart wheeled walker integrated multiple digital health features including photoplethysmography-based heart rate monitoring, pulse oximetry, and a tilt-based fall detection system with mobile alert functionality.
The device monitored heart rate (HR) via photoplethysmography and oxygen saturation (SpO₂) via pulse oximetry in real time.
A tilt-based fall detection system with mobile alert functionality was incorporated.
The study compared this device to a conventional wheeled walker, which lacks real-time physiological monitoring and safety feedback.
All 30 participants (100%) completed both intervention conditions and were included in the final analysis.
Methods
The study population consisted of community-dwelling older adults with mild balance impairment, and the trial was conducted under short-term supervised conditions.
Participants were aged 65 to 80 years with a Timed Up and Go score greater than 13.5 seconds, indicating mild balance impairment.
The trial was single-blind and used a randomized crossover design.
The authors note that further longitudinal studies in real-world settings are warranted to evaluate long-term mobility, fall prevention, independent use, and comprehensive device safety.
What This Means
This research suggests that a 'smart' wheeled walker equipped with sensors to monitor heart rate, blood oxygen levels, and detect falls can help older adults walk more efficiently and with better balance compared to a standard wheeled walker. The study tested 30 older adults aged 65–80 who already had some difficulty with balance, asking each person to use both types of walkers in a randomized order during a single supervised session. People walked faster, used less physical effort per meter walked, and completed a standard balance-and-mobility test more quickly when using the smart walker versus the regular one.
However, the smart walker did not meaningfully change how afraid participants felt of falling, at least over this short testing period. The study was designed as a crossover trial, meaning each participant served as their own comparison, which helps control for individual differences. The testing took place in a supervised setting with only a 30-minute rest between walker conditions, so the results reflect short-term, immediate effects rather than long-term use in everyday life.
This research suggests that adding real-time health monitoring technology to mobility aids commonly used by older adults may offer benefits beyond simple physical support, potentially improving how efficiently and safely people move. However, because this was a brief, controlled study, it is not yet clear whether these benefits would hold up over weeks or months of real-world use, or whether the fall detection features would reduce actual falls. The authors call for longer studies in real-world settings to answer those questions.
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Werasirirat P, Muanjai P, Sukkho O, Luangpon N, Snieckus A, Namsawang J. (2026). A Smart Wheeled Walker With Integrated Physiological Monitoring to Improve Mobility in Older Adults: Randomized Crossover Trial.. JMIR aging. https://doi.org/10.2196/99522