Ann Geriatr Med Res.  2019 Jun;23(2):71-76. 10.4235/agmr.19.0016.

Cross-Comparisons of Gait Speeds by Automatic Sensors and a Stopwatch to Provide Converting Formula Between Measuring Modalities

• Jung HW
• Roh HC
• Kim SW
• Kim S
• Kim M
• Won CW

• KMID: 2452841
• DOI: http://doi.org/10.4235/agmr.19.0016

Abstract

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.

Keyword

Walking speed; Screening; Diagnosis; Data analysis

MeSH Terms

Aging
Cohort Studies
Dataset
Diagnosis
Gait*
Hope
Linear Models
Mass Screening
Posture
Statistics as Topic
Ultrasonography
Walking