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Updated: Dec 13, 2025
Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
Published on: November 7, 2014
Cross-Comparisons of Gait Speeds by Automatic Sensors and a Stopwatch to Provide Converting Formula Between Measuring
Hee-Won Jung1, Hyun-Chul Roh2, Sun-Wook Kim3
1Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
Background:
We aimed to compare 4 automatic devices with a conventional stopwatch for measuring gait speed.
Methods:
We used 4 experimental devices to automatically measure gait speed: 1) Gaitspeedometer (GSM) 1, with laser sensors; 2) GSM2, with ultrasound sensors; 3) GSM3, with infrared sensors; and 4) GSM4, with a light detection and ranging sensor. To assess compatibility between different versions of GSMs, we collected 426 data points from 4 young engineers walking at random speeds and with varying postures. We used these data to convert gait speed measured by GSM1 and 2 for compatibility with GSM3 in the Korean Frailty and Aging Cohort Study (KFACS) dataset.
Results:
Mean gait speeds measured with GSMs 1-4 were 1.7% slower (R2=0.997), 12.2% faster (R2=0.993), 1.3% slower (R2=0.999), and 4.3% slower (R2=0.996), respectively, than the gait speed measured with a stopwatch. The concordance correlation coefficient between each GSM and the stopwatch was higher than 0.9. Using linear regression analysis with no constant term, conversion formulas for GSMs were established for the KFACS dataset using GSM1 and GSM2.
Conclusion:
The 4 methods of automatic gait speed measurement and the manually measured gait speed correlated well with each other, and we hope these new technologies reduce barriers to measuring older people's gait speed in busy clinical settings.
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