Motion Symmetry Evaluation Using Accelerometers and Energy Distribution

Aleš Procházka,Martin Vališ,Hana Charvátová,Oldřich Vyšata

doi:10.3390/sym11070871

Abstract

Analysis of motion symmetry constitutes an important area with many applications in engineering, robotics, neurology and biomedicine. This paper presents the use of microelectromechanical sensors (MEMS), including accelerometers and gyrometers, to acquire data via mobile devices so as to monitor physical activities and their irregularities. Special attention is devoted to the analysis of the symmetry of the motion of the body when the same exercises are performed by the right and the left limb. The analyzed data include the motion of the legs on a home exercise bike under different levels of load. The method is based on signal analysis using the discrete wavelet transform and the evaluation of signal segment features such as the relative energy at selected decomposition levels. The subsequent classification of the evaluated features is performed by k-nearest neighbours, a Bayesian approach, a support vector machine, and neural networks. The highest average classification accuracy attained is 91.0% and the lowest mean cross-validation error is 0.091, resulting from the use of a neural network. This paper presents the advantages of the use of simple sensors, their combination and intelligent data processing for the numerical evaluation of motion features in the rehabilitation and monitoring of physical activities.

Highlights

The analysis of motion symmetry has a wide range of applications in rehabilitation, physical therapy, biomedicine and neurology allowing us to detect natural differences between the movement of the left and right limbs during walking, running or cycling [1,2,3], to study the dependence of motion symmetry on mental and environmental conditions and to enable early diagnostics of possible neurological disorders
The signals recorded by microelectromechanical sensors (MEMS) and handheld devices [4,5,6]
The goal of the paper is in the study of the effect of the load to motion features, motion symmetry and classification accuracy

Summary

Introduction

The analysis of motion symmetry has a wide range of applications in rehabilitation, physical therapy, biomedicine and neurology allowing us to detect natural differences between the movement of the left and right limbs during walking, running or cycling [1,2,3], to study the dependence of motion symmetry on mental and environmental conditions and to enable early diagnostics of possible neurological disorders This multidisciplinary area combines the knowledge and use of different sensor systems, wireless communication links and computational intelligence methods to detect appropriate features and process signals recorded by selected multichannel systems. Associated methods of symmetry analysis combined with motion tracking systems using inertial measurement units [13]

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