RESEARCH ARTICLE


Entropy Measures with Three-axis Motion Time-series Data: Comparison of Dominant and Non-dominant Hand in Multi-directional Reach



Nuttaporn Praditpod1, 2, Phongpan Tantipoon2, Xinyu Zhang3, Petra Rauchhaus4, Chunhui Li1, *, Zhihong Huang1
1 Department of Biomedical Engineering, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
2 Department of Physical Therapy, Faculty of Allied Health Sciences, Thammasat University, Bangkok, Thailand
3 School of Medicine, University of Dundee, Dundee, United Kingdom
4 Tayside Clinical Trials Unit (TCTU), School of Medicine, University of Dundee, Dundee, United Kingdom


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Creative Commons License
© 2023 Praditpod et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Biomedical Engineering, School of Science and Engineering, University of Dundee, Dundee, United Kingdom; Tel.: (+44)1382386730; E-mail c.li@dundee.ac.uk


Abstract

Background:

Motion variance differs among individuals, knowing as the differences in dominant and non-dominant hand functions provide beneficial information to clinicians or therapists regarding accurate diagnosis and rehabilitation purposes. However, due to subjective considerations, there are some limitations of the handedness questionnaires, which are one of the standard methods for evaluating interlimb function differences.

Objective:

This study aims to quantify the differences in upper limb motions between the dominant and non-dominant hands in the reaching task using approximate entropy (ApEn) and sample entropy (SampEn) measures. This study also provides proper combinations of parameter values m and r for the ApEn and SampEn measures in the hand movement data of the reaching task.

Methods:

Twenty volunteers performed a multi-directional reaching task. The acceleration data of hand motions were recorded by GENEActiv 3D acceleration sensor (Activinsights Ltd., UK) with a sampling frequency of 1000 Hz. In addition, the ApEn and SampEn values were analysed.

Results:

The ApEn values of the dominant hand were statistically significantly lower than those of the non-dominant hand for parameter combinations of m=2,3,4,5 with r=0.15,0.20,0.25 for the Y- and Z-axis (p<0.05). The SampEn values of the dominant hand significantly demonstrated lower than those of the non-dominant hand for all axes when computing on combinations of parameter m=2,3,4,5 with r=0.15,0.20 (p<0.05).

Conclusion:

The ApEn and SampEn measures could be used to predict the degree of regularity or complexity of the reaching hand motion time-series data. These entropy measures also reveal the differences between the dominant and non-dominant hand movements, quantifying movement differences in the dynamic motor tasks associated with hemispheric brain asymmetry.

Keywords: Approximate entropy, Sample entropy, Reaching, Acceleration data, Dominant hand, and Non-dominant hand.