Walking-speed estimation using a single inertial measurement unit for the older adults

Autoři: Seonjeong Byun aff001;  Hyang Jun Lee aff003;  Ji Won Han aff003;  Jun Sung Kim aff004;  Euna Choi aff005;  Ki Woong Kim aff001
Působiště autorů: Department of Psychiatry, Seoul National University, College of Medicine, Seoul, Korea aff001;  Department of Neuropsychiatry, National Medical Center, Seoul, Korea aff002;  Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea aff003;  Department of Brain and Cognitive Science, Seoul National University College of Natural Sciences, Seoul, Korea aff004;  Korean National Institute of Dementia, Seongnam, Korea aff005
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0227075



Although walking speed is associated with important clinical outcomes and designated as the sixth vital sign of the elderly, few walking-speed estimation algorithms using an inertial measurement unit (IMU) have been derived and tested in the older adults, especially in the elderly with slow speed. We aimed to develop a walking-speed estimation algorithm for older adults based on an IMU.


We used data from 659 of 785 elderly enrolled from the cohort study. We measured gait using an IMU attached on the lower back while participants walked around a 28 m long round walkway thrice at comfortable paces. Best-fit linear regression models were developed using selected demographic, anthropometric, and IMU features to estimate the walking speed. The accuracy of the algorithm was verified using mean absolute error (MAE) and root mean square error (RMSE) in an independent validation set. Additionally, we verified concurrent validity with GAITRite using intraclass correlation coefficients (ICCs).


The proposed algorithm incorporates the age, sex, foot length, vertical displacement, cadence, and step-time variability obtained from an IMU sensor. It exhibited high estimation accuracy for the walking speed of the elderly and remarkable concurrent validity compared to the GAITRite (MAE = 4.70%, RMSE = 6.81 ??/?, concurrent validity (ICC (3,1)) = 0.937). Moreover, it achieved high estimation accuracy even for slow walking by applying a slow-speed-specific regression model sequentially after estimation by a general regression model. The accuracy was higher than those obtained with models based on the human gait model with or without calibration to fit the population.


The developed inertial-sensor-based walking-speed estimation algorithm can accurately estimate the walking speed of older adults.

Klíčová slova:

Acceleration – Algorithms – Elderly – Feet – Gait analysis – Geriatrics – Inertia – Walking


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Článek vyšel v časopise


2019 Číslo 12