Orientation-Invariant Spatio-Temporal Gait Analysis Using Foot-Worn Inertial Sensors

Inertial sensors can potentially assist clinical decision making in gait-related disorders. Methods for objective spatio-temporal gait analysis usually assume the careful alignment of the sensors on the body, so that sensor data can be evaluated using the body coordinate system. Some studies infer s...

Full description

Bibliographic Details
Main Authors: Vânia Guimarães, Inês Sousa, Miguel Velhote Correia
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Sensors
Subjects:
IMU
Online Access:https://www.mdpi.com/1424-8220/21/11/3940
Description
Summary:Inertial sensors can potentially assist clinical decision making in gait-related disorders. Methods for objective spatio-temporal gait analysis usually assume the careful alignment of the sensors on the body, so that sensor data can be evaluated using the body coordinate system. Some studies infer sensor orientation by exploring the cyclic characteristics of walking. In addition to being unrealistic to assume that the sensor can be aligned perfectly with the body, the robustness of gait analysis with respect to differences in sensor orientation has not yet been investigated—potentially hindering use in clinical settings. To address this gap in the literature, we introduce an orientation-invariant gait analysis approach and propose a method to quantitatively assess robustness to changes in sensor orientation. We validate our results in a group of young adults, using an optical motion capture system as reference. Overall, good agreement between systems is achieved considering an extensive set of gait metrics. Gait speed is evaluated with a relative error of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>−</mo><mn>3.1</mn><mo>±</mo><mn>9.2</mn></mrow></semantics></math></inline-formula> cm/s, but precision improves when turning strides are excluded from the analysis, resulting in a relative error of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>−</mo><mn>3.4</mn><mo>±</mo><mn>6.9</mn></mrow></semantics></math></inline-formula> cm/s. We demonstrate the invariance of our approach by simulating rotations of the sensor on the foot.
ISSN:1424-8220