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An in-silico study of the effect of non-linear skin dynamics on skin-mounted accelerometer inference of skull motion

Frederick Wright, Paul D. Docherty, Elisabeth Williams Orcid Logo, Desney Greybe, Hari Arora Orcid Logo, Natalia Kabaliuk

Biomedical Signal Processing and Control, Volume: 70, Start page: 102986

Swansea University Authors: Elisabeth Williams Orcid Logo, Desney Greybe, Hari Arora Orcid Logo

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DOI (Published version): 10.1016/j.bspc.2021.102986

Abstract

Accurate and precise analysis of head impact telemetry data is important for development of biomechanical models and methodologies to decrease the risk of traumatic brain injury. Systematic review suggests that much existing data lacks verification. Soft tissue artefact is a common problem that is n...

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Published in: Biomedical Signal Processing and Control
ISSN: 1746-8094
Published: Elsevier BV 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa57618
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Systematic review suggests that much existing data lacks verification. Soft tissue artefact is a common problem that is not frequently addressed. This paper outlines a method of modelling the coupled, non-linear, skull-skin-sensor system. The model is based on a second order underdamped spring mass damper system that incorporates non-linear values to account for the complex dynamic nature of skin. MATLAB was used to simulate the estimated movement of a sensor mounted to the skin relative to measurements collected via a mouthguard sensor. The non-linear elastic and damping models were developed from descriptions in literature. The model assumed a sensor of 8 g, mounted behind the ear. Results were compared to a typical linear system. In small impacts, the linear and non-linear models provided similar accelerations to the skull. However, in large impacts, the acceleration of the sensor was estimated to be 158% greater than the skull acceleration when modelled non-linearly, while a linear model showed only a 0.7% increase. This implies that for small impacts, the nonlinearity of skin-skull dynamics is not an important characteristic for modelling. 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spelling 2021-09-07T15:22:27.9554265 v2 57618 2021-08-16 An in-silico study of the effect of non-linear skin dynamics on skin-mounted accelerometer inference of skull motion 2c5b3af00392058866bfd4af84bef390 0000-0002-8422-5842 Elisabeth Williams Elisabeth Williams true false bd05f59773276ec086d23e454b603c45 Desney Greybe Desney Greybe true false ed7371c768e9746008a6807f9f7a1555 0000-0002-9790-0907 Hari Arora Hari Arora true false 2021-08-16 STSC Accurate and precise analysis of head impact telemetry data is important for development of biomechanical models and methodologies to decrease the risk of traumatic brain injury. Systematic review suggests that much existing data lacks verification. Soft tissue artefact is a common problem that is not frequently addressed. This paper outlines a method of modelling the coupled, non-linear, skull-skin-sensor system. The model is based on a second order underdamped spring mass damper system that incorporates non-linear values to account for the complex dynamic nature of skin. MATLAB was used to simulate the estimated movement of a sensor mounted to the skin relative to measurements collected via a mouthguard sensor. The non-linear elastic and damping models were developed from descriptions in literature. The model assumed a sensor of 8 g, mounted behind the ear. Results were compared to a typical linear system. In small impacts, the linear and non-linear models provided similar accelerations to the skull. However, in large impacts, the acceleration of the sensor was estimated to be 158% greater than the skull acceleration when modelled non-linearly, while a linear model showed only a 0.7% increase. This implies that for small impacts, the nonlinearity of skin-skull dynamics is not an important characteristic for modelling. However, in large impacts, the non-linearity of the skin-skull dynamic can lead to drastic over-estimates of skull acceleration when using skin mounted accelerometers. Journal Article Biomedical Signal Processing and Control 70 102986 Elsevier BV 1746-8094 Soft tissue artefact, Skin modelling, Head impact, Skin-mounted sensor, Accelerometer 1 9 2021 2021-09-01 10.1016/j.bspc.2021.102986 COLLEGE NANME Sport and Exercise Sciences COLLEGE CODE STSC Swansea University 2021-09-07T15:22:27.9554265 2021-08-16T09:33:40.8689762 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Sport and Exercise Sciences Frederick Wright 1 Paul D. Docherty 2 Elisabeth Williams 0000-0002-8422-5842 3 Desney Greybe 4 Hari Arora 0000-0002-9790-0907 5 Natalia Kabaliuk 6 57618__20708__d1311f497984403d8c73221534bd7f86.pdf 57618.pdf 2021-08-27T14:03:54.2353091 Output 1303086 application/pdf Accepted Manuscript true 2022-08-12T00:00:00.0000000 ©2021 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND) true eng https://creativecommons.org/licenses/by-nc-nd/4.0/
title An in-silico study of the effect of non-linear skin dynamics on skin-mounted accelerometer inference of skull motion
spellingShingle An in-silico study of the effect of non-linear skin dynamics on skin-mounted accelerometer inference of skull motion
Elisabeth Williams
Desney Greybe
Hari Arora
title_short An in-silico study of the effect of non-linear skin dynamics on skin-mounted accelerometer inference of skull motion
title_full An in-silico study of the effect of non-linear skin dynamics on skin-mounted accelerometer inference of skull motion
title_fullStr An in-silico study of the effect of non-linear skin dynamics on skin-mounted accelerometer inference of skull motion
title_full_unstemmed An in-silico study of the effect of non-linear skin dynamics on skin-mounted accelerometer inference of skull motion
title_sort An in-silico study of the effect of non-linear skin dynamics on skin-mounted accelerometer inference of skull motion
author_id_str_mv 2c5b3af00392058866bfd4af84bef390
bd05f59773276ec086d23e454b603c45
ed7371c768e9746008a6807f9f7a1555
author_id_fullname_str_mv 2c5b3af00392058866bfd4af84bef390_***_Elisabeth Williams
bd05f59773276ec086d23e454b603c45_***_Desney Greybe
ed7371c768e9746008a6807f9f7a1555_***_Hari Arora
author Elisabeth Williams
Desney Greybe
Hari Arora
author2 Frederick Wright
Paul D. Docherty
Elisabeth Williams
Desney Greybe
Hari Arora
Natalia Kabaliuk
format Journal article
container_title Biomedical Signal Processing and Control
container_volume 70
container_start_page 102986
publishDate 2021
institution Swansea University
issn 1746-8094
doi_str_mv 10.1016/j.bspc.2021.102986
publisher Elsevier BV
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Sport and Exercise Sciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Sport and Exercise Sciences
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description Accurate and precise analysis of head impact telemetry data is important for development of biomechanical models and methodologies to decrease the risk of traumatic brain injury. Systematic review suggests that much existing data lacks verification. Soft tissue artefact is a common problem that is not frequently addressed. This paper outlines a method of modelling the coupled, non-linear, skull-skin-sensor system. The model is based on a second order underdamped spring mass damper system that incorporates non-linear values to account for the complex dynamic nature of skin. MATLAB was used to simulate the estimated movement of a sensor mounted to the skin relative to measurements collected via a mouthguard sensor. The non-linear elastic and damping models were developed from descriptions in literature. The model assumed a sensor of 8 g, mounted behind the ear. Results were compared to a typical linear system. In small impacts, the linear and non-linear models provided similar accelerations to the skull. However, in large impacts, the acceleration of the sensor was estimated to be 158% greater than the skull acceleration when modelled non-linearly, while a linear model showed only a 0.7% increase. This implies that for small impacts, the nonlinearity of skin-skull dynamics is not an important characteristic for modelling. However, in large impacts, the non-linearity of the skin-skull dynamic can lead to drastic over-estimates of skull acceleration when using skin mounted accelerometers.
published_date 2021-09-01T04:13:30Z
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