Automated detection and explainability of pathological gait patterns using a one-class support vector machine trained on inertial measurement unit based gait data.
Journal:
Clinical biomechanics (Bristol, Avon)
Published Date:
Aug 17, 2021
Abstract
BACKGROUND: Machine learning approaches for the classification of pathological gait based on kinematic data, e.g. derived from inertial sensors, are commonly used in terms of a multi-class classification problem. However, there is a lack of research regarding one-class classifiers that are independent of certain pathologies. Therefore, it was the aim of this work to design a one-class classifier based on healthy norm-data that provides not only a prediction probability but rather an explanation of the classification decision, increasing the acceptance of this machine learning approach.