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Filtering Biomechanical Signals in Movement Analysis
Biomechanical analysis of human movement is based on dynamic measurements of reference points on the subject’s body and orientation measurements of body segments. Collected data include positions’ measurement, in a three-dimensional space. Signal enhancement by proper filtering is often recommended....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271607/ https://www.ncbi.nlm.nih.gov/pubmed/34283131 http://dx.doi.org/10.3390/s21134580 |
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author | Crenna, Francesco Rossi, Giovanni Battista Berardengo, Marta |
author_facet | Crenna, Francesco Rossi, Giovanni Battista Berardengo, Marta |
author_sort | Crenna, Francesco |
collection | PubMed |
description | Biomechanical analysis of human movement is based on dynamic measurements of reference points on the subject’s body and orientation measurements of body segments. Collected data include positions’ measurement, in a three-dimensional space. Signal enhancement by proper filtering is often recommended. Velocity and acceleration signal must be obtained from position/angular measurement records, needing numerical processing effort. In this paper, we propose a comparative filtering method study procedure, based on measurement uncertainty related parameters’ set, based upon simulated and experimental signals. The final aim is to propose guidelines to optimize dynamic biomechanical measurement, considering the measurement uncertainty contribution due to the processing method. Performance of the considered methods are examined and compared with an analytical signal, considering both stationary and transient conditions. Finally, four experimental test cases are evaluated at best filtering conditions for measurement uncertainty contributions. |
format | Online Article Text |
id | pubmed-8271607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82716072021-07-11 Filtering Biomechanical Signals in Movement Analysis Crenna, Francesco Rossi, Giovanni Battista Berardengo, Marta Sensors (Basel) Article Biomechanical analysis of human movement is based on dynamic measurements of reference points on the subject’s body and orientation measurements of body segments. Collected data include positions’ measurement, in a three-dimensional space. Signal enhancement by proper filtering is often recommended. Velocity and acceleration signal must be obtained from position/angular measurement records, needing numerical processing effort. In this paper, we propose a comparative filtering method study procedure, based on measurement uncertainty related parameters’ set, based upon simulated and experimental signals. The final aim is to propose guidelines to optimize dynamic biomechanical measurement, considering the measurement uncertainty contribution due to the processing method. Performance of the considered methods are examined and compared with an analytical signal, considering both stationary and transient conditions. Finally, four experimental test cases are evaluated at best filtering conditions for measurement uncertainty contributions. MDPI 2021-07-04 /pmc/articles/PMC8271607/ /pubmed/34283131 http://dx.doi.org/10.3390/s21134580 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Crenna, Francesco Rossi, Giovanni Battista Berardengo, Marta Filtering Biomechanical Signals in Movement Analysis |
title | Filtering Biomechanical Signals in Movement Analysis |
title_full | Filtering Biomechanical Signals in Movement Analysis |
title_fullStr | Filtering Biomechanical Signals in Movement Analysis |
title_full_unstemmed | Filtering Biomechanical Signals in Movement Analysis |
title_short | Filtering Biomechanical Signals in Movement Analysis |
title_sort | filtering biomechanical signals in movement analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271607/ https://www.ncbi.nlm.nih.gov/pubmed/34283131 http://dx.doi.org/10.3390/s21134580 |
work_keys_str_mv | AT crennafrancesco filteringbiomechanicalsignalsinmovementanalysis AT rossigiovannibattista filteringbiomechanicalsignalsinmovementanalysis AT berardengomarta filteringbiomechanicalsignalsinmovementanalysis |