Calibration-Free Gait Assessment by Foot-Worn Inertial Sensors.

Daniel Laidig,Klemens Adamer,Bernhard Guggenberger,Thomas Seel,Michael Fischer,Andreas J Jocham

doi:10.3389/fdgth.2021.736418

Abstract

Walking is a central activity of daily life, and there is an increasing demand for objective measurement-based gait assessment. In contrast to stationary systems, wearable inertial measurement units (IMUs) have the potential to enable non-restrictive and accurate gait assessment in daily life. We propose a set of algorithms that uses the measurements of two foot-worn IMUs to determine major spatiotemporal gait parameters that are essential for clinical gait assessment: durations of five gait phases for each side as well as stride length, walking speed, and cadence. Compared to many existing methods, the proposed algorithms neither require magnetometers nor a precise mounting of the sensor or dedicated calibration movements. They are therefore suitable for unsupervised use by non-experts in indoor as well as outdoor environments. While previously proposed methods are rarely validated in pathological gait, we evaluate the accuracy of the proposed algorithms on a very broad dataset consisting of 215 trials and three different subject groups walking on a treadmill: healthy subjects (n = 39), walking at three different speeds, as well as orthopedic (n = 62) and neurological (n = 36) patients, walking at a self-selected speed. The results show a very strong correlation of all gait parameters (Pearson's r between 0.83 and 0.99, p < 0.01) between the IMU system and the reference system. The mean absolute difference (MAD) is 1.4 % for the gait phase durations, 1.7 cm for the stride length, 0.04 km/h for the walking speed, and 0.7 steps/min for the cadence. We show that the proposed methods achieve high accuracy not only for a large range of walking speeds but also in pathological gait as it occurs in orthopedic and neurological diseases. In contrast to all previous research, we present calibration-free methods for the estimation of gait phases and spatiotemporal parameters and validate them in a large number of patients with different pathologies. The proposed methods lay the foundation for ubiquitous unsupervised gait assessment in daily-life environments.

Highlights

Walking is a central activity of daily life, and restrictions of this ability lead to a reduction in the quality of life [1, 2]
The results are presented separately for each of the three subject groups in scatter plots and Bland-Altman plots [50] and can be found in Figure 10, for the healthy participants walking at three different speeds; in Figure 11, for the participants with orthopedic diseases; and in Figure 12, for the participants with neurological diseases
We have proposed a set of methods for spatiotemporal gait analysis based on two inertial sensors attached to the feet

Summary

Introduction

Walking is a central activity of daily life, and restrictions of this ability lead to a reduction in the quality of life [1, 2]. Gait can be measured by spatial (e.g., step or stride length) and temporal (e.g., stride time, cadence) parameters, relative durations of gait phases, and kinematic and kinetic gait variables [5] These parameters are used to quantify gait deviation in both clinical practice and research, and their use varies with the medical field, the research question, and the analysis options. While gait assessment in clinical practice is mostly based on visual observation by medical experts [6], it is desirable to support expert knowledge and time by objective measurements This is important because relevant gait changes are often too subtle to be detected by the naked eye [7]

Objectives

Methods

Results

Discussion

Conclusion