JMIR Publications

ABSTRACT

Background:

Gait speed is a valuable biomarker for mobility and health assessment in clinical and research settings. Existing methods to measure gait speed require expensive equipment or personal assistance, limiting their use in unsupervised, daily-life conditions.

Objective:

This study aimed to examine the validity and reliability of the inverted pendulum model approach to estimating gait speed and required spatial information (i.e., step length) from data collected with a single smartphone IMU placed in the user’s pants pocket, for both healthy younger and older adults.

Methods:

A custom-developed smartphone app was used to record gait data from healthy younger and older adults during normal and dual-task walking. Validity and reliability of gait speed and step length estimations from the smartphone were compared with the gold-standard GAITRite mat. A coefficient-based adjustment based upon a coefficient relative to the original estimation of step length was applied to improve the accuracy of gait speed estimation.

Results:

Smartphone-derived gait speed and step length showed good validity compared to the GAITRite mat, with minimal bias and acceptable limits of agreement. The test-retest reliability of app-derived gait speed was good to excellent within supervised laboratory settings and unsupervised home conditions. After adjustment, the accuracy of gait speed estimation improved, with reduced bias. The adjustment coefficients were applicable to a wide range of step lengths and gait speeds.

Conclusions:

The inverted pendulum approach is a valid and reliable method for estimating gait speed from a smartphone IMU placed in the pocket of younger and older adults. Adjusting step length by a coefficient derived from the original estimation of step length successfully removed bias and improved the accuracy of gait speed estimation. This novel method has potential applications in various settings and populations, though fine-tuning may be necessary for specific datasets.