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Synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training

BACKGROUND: Vibroarthrographic (VAG) signals are used as useful indicators of knee osteoarthritis (OA) status. The objective was to build a template database of knee crepitus sounds. Internships can practice in the template database to shorten the time of training for diagnosis of OA. METHODS: A kne...

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Autores principales: Shieh, Chin-Shiuh, Tseng, Chin-Dar, Chang, Li-Yun, Lin, Wei-Chun, Wu, Li-Fu, Wang, Hung-Yu, Chao, Pei-Ju, Chiu, Chien-Liang, Lee, Tsair-Fwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4950531/
https://www.ncbi.nlm.nih.gov/pubmed/27435313
http://dx.doi.org/10.1186/s13104-016-2156-6
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author Shieh, Chin-Shiuh
Tseng, Chin-Dar
Chang, Li-Yun
Lin, Wei-Chun
Wu, Li-Fu
Wang, Hung-Yu
Chao, Pei-Ju
Chiu, Chien-Liang
Lee, Tsair-Fwu
author_facet Shieh, Chin-Shiuh
Tseng, Chin-Dar
Chang, Li-Yun
Lin, Wei-Chun
Wu, Li-Fu
Wang, Hung-Yu
Chao, Pei-Ju
Chiu, Chien-Liang
Lee, Tsair-Fwu
author_sort Shieh, Chin-Shiuh
collection PubMed
description BACKGROUND: Vibroarthrographic (VAG) signals are used as useful indicators of knee osteoarthritis (OA) status. The objective was to build a template database of knee crepitus sounds. Internships can practice in the template database to shorten the time of training for diagnosis of OA. METHODS: A knee sound signal was obtained using an innovative stethoscope device with a goniometer. Each knee sound signal was recorded with a Kellgren–Lawrence (KL) grade. The sound signal was segmented according to the goniometer data. The signal was Fourier transformed on the correlated frequency segment. An inverse Fourier transform was performed to obtain the time-domain signal. Haar wavelet transform was then done. The median and mean of the wavelet coefficients were chosen to inverse transform the synthesized signal in each KL category. The quality of the synthesized signal was assessed by a clinician. RESULTS: The sample signals were evaluated using different algorithms (median and mean). The accuracy rate of the median coefficient algorithm (93 %) was better than the mean coefficient algorithm (88 %) for cross-validation by a clinician using synthesis of VAG. CONCLUSIONS: The artificial signal we synthesized has the potential to build a learning system for medical students, internships and para-medical personnel for the diagnosis of OA. Therefore, our method provides a feasible way to evaluate crepitus sounds that may assist in the diagnosis of knee OA.
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spelling pubmed-49505312016-07-20 Synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training Shieh, Chin-Shiuh Tseng, Chin-Dar Chang, Li-Yun Lin, Wei-Chun Wu, Li-Fu Wang, Hung-Yu Chao, Pei-Ju Chiu, Chien-Liang Lee, Tsair-Fwu BMC Res Notes Research Article BACKGROUND: Vibroarthrographic (VAG) signals are used as useful indicators of knee osteoarthritis (OA) status. The objective was to build a template database of knee crepitus sounds. Internships can practice in the template database to shorten the time of training for diagnosis of OA. METHODS: A knee sound signal was obtained using an innovative stethoscope device with a goniometer. Each knee sound signal was recorded with a Kellgren–Lawrence (KL) grade. The sound signal was segmented according to the goniometer data. The signal was Fourier transformed on the correlated frequency segment. An inverse Fourier transform was performed to obtain the time-domain signal. Haar wavelet transform was then done. The median and mean of the wavelet coefficients were chosen to inverse transform the synthesized signal in each KL category. The quality of the synthesized signal was assessed by a clinician. RESULTS: The sample signals were evaluated using different algorithms (median and mean). The accuracy rate of the median coefficient algorithm (93 %) was better than the mean coefficient algorithm (88 %) for cross-validation by a clinician using synthesis of VAG. CONCLUSIONS: The artificial signal we synthesized has the potential to build a learning system for medical students, internships and para-medical personnel for the diagnosis of OA. Therefore, our method provides a feasible way to evaluate crepitus sounds that may assist in the diagnosis of knee OA. BioMed Central 2016-07-19 /pmc/articles/PMC4950531/ /pubmed/27435313 http://dx.doi.org/10.1186/s13104-016-2156-6 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Shieh, Chin-Shiuh
Tseng, Chin-Dar
Chang, Li-Yun
Lin, Wei-Chun
Wu, Li-Fu
Wang, Hung-Yu
Chao, Pei-Ju
Chiu, Chien-Liang
Lee, Tsair-Fwu
Synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training
title Synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training
title_full Synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training
title_fullStr Synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training
title_full_unstemmed Synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training
title_short Synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training
title_sort synthesis of vibroarthrographic signals in knee osteoarthritis diagnosis training
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4950531/
https://www.ncbi.nlm.nih.gov/pubmed/27435313
http://dx.doi.org/10.1186/s13104-016-2156-6
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