A Pilot Study to Validate a Wearable Inertial Sensor for Gait Assessment in Older Adults with Falls.

Guillermo García-Villamil,Cristina Rodríguez-Sánchez,Elisabet Huertas-Hoyas,Marta Neira-Álvarez,Antonio Ramón-Jiménez

doi:10.3390/s21134334

Guillermo García-Villamil, Cristina Rodríguez-Sánchez + Show 3 more

Open Access

https://doi.org/10.3390/s21134334

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Abstract

The high prevalence of falls and the enormous impact they have on the elderly population is a cause for concern. We aimed to develop a walking-monitor gait pattern (G-STRIDE) for older adults based on a 6-axis inertial measurement (IMU) with the application of pedestrian dead reckoning algorithms and tested its structural and clinical validity. A cross-sectional case–control study was conducted with 21 participants (11 fallers and 10 non-fallers). We measured gait using an IMU attached to the foot while participants walked around different grounds (indoor flooring, outdoor floor, asphalt, etc.). The G-STRIDE consisted of a portable inertial device that monitored the gait pattern and a mobile app for telematic clinical analysis. G-STRIDE made it possible to measure gait parameters under normal living conditions when walking without assessing the patient in the outpatient clinic. Moreover, we verified concurrent validity with convectional outcome measures using intraclass correlation coefficients (ICCs) and analyzed the differences between participants. G-STRIDE showed high estimation accuracy for the walking speed of the elderly and good concurrent validity compared to conventional measures (ICC = 0.69; p < 0.000). In conclusion, the developed inertial-based G-STRIDE can accurately classify older people with risk to fall with a significance as high as using traditional but more subjective clinical methods (gait speed, Timed Up and Go Test).

Highlights

Falls are one of the most significant clinical problems in the elderly population
In primary and specialized care, this can be achieve using inexpensive methods based on physical examination and functional tests such as the gait speed test, the Short Physical Performance Battery (SPPB) [7], and the Timed Up and Go Test (TUG) [8], and the Environment-Adaptive TUG (EATUG) fall risk assessment system [9], which is an improvement of the standard TUG test
We demonstrated the concurrent validity of each model based on the intraclass correlation coefficients (ICCs) calculated using a two-way mixed model by comparing the walking speeds estimated from conventional measurement

Summary

Introduction

Falls are one of the most significant clinical problems in the elderly population. Onethird of the elderly living in the community falls every year, and about half of them suffer repeated falls. In primary and specialized care, this can be achieve using inexpensive methods based on physical examination and functional tests such as the gait speed test, the Short Physical Performance Battery (SPPB) [7], and the Timed Up and Go Test (TUG) [8], and the Environment-Adaptive TUG (EATUG) fall risk assessment system [9], which is an improvement of the standard TUG test. These conventional functional tests provide information on running times and the qualitative aspects of gait. They are, to some extent, subjective by using verbal instructions to the patient, manual temporal measures (e.g., handheld stopwatches) and they do not provide information on many other gait parameters of interest for recognizing aspects related to falls, such as cadence, stride length or swing phase time, for example

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