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Application of Wavelet in Quantitative Evaluation of Gait Events of Parkinson's Disease

RESULTS: Systems detected FOG and other gait postures and showed time-frequency range by examining differentiated decomposed signals by DWT. Energy distribution and PSD graph proved the accuracy of the system. Validation is done by the LOSO method which shows 90% accuracy for the proposed method. CO...

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Autor principal: Zahra, Noore
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8677364/
https://www.ncbi.nlm.nih.gov/pubmed/34925552
http://dx.doi.org/10.1155/2021/7199007
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author Zahra, Noore
author_facet Zahra, Noore
author_sort Zahra, Noore
collection PubMed
description RESULTS: Systems detected FOG and other gait postures and showed time-frequency range by examining differentiated decomposed signals by DWT. Energy distribution and PSD graph proved the accuracy of the system. Validation is done by the LOSO method which shows 90% accuracy for the proposed method. CONCLUSION: Observations of the clinical trials validate the proposed technique. In comparison to the previous techniques reported in literature, it is seen that the proposed method shows improvement in time and frequency resolution as well as processing time.
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spelling pubmed-86773642021-12-17 Application of Wavelet in Quantitative Evaluation of Gait Events of Parkinson's Disease Zahra, Noore Appl Bionics Biomech Research Article RESULTS: Systems detected FOG and other gait postures and showed time-frequency range by examining differentiated decomposed signals by DWT. Energy distribution and PSD graph proved the accuracy of the system. Validation is done by the LOSO method which shows 90% accuracy for the proposed method. CONCLUSION: Observations of the clinical trials validate the proposed technique. In comparison to the previous techniques reported in literature, it is seen that the proposed method shows improvement in time and frequency resolution as well as processing time. Hindawi 2021-12-09 /pmc/articles/PMC8677364/ /pubmed/34925552 http://dx.doi.org/10.1155/2021/7199007 Text en Copyright © 2021 Noore Zahra. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zahra, Noore
Application of Wavelet in Quantitative Evaluation of Gait Events of Parkinson's Disease
title Application of Wavelet in Quantitative Evaluation of Gait Events of Parkinson's Disease
title_full Application of Wavelet in Quantitative Evaluation of Gait Events of Parkinson's Disease
title_fullStr Application of Wavelet in Quantitative Evaluation of Gait Events of Parkinson's Disease
title_full_unstemmed Application of Wavelet in Quantitative Evaluation of Gait Events of Parkinson's Disease
title_short Application of Wavelet in Quantitative Evaluation of Gait Events of Parkinson's Disease
title_sort application of wavelet in quantitative evaluation of gait events of parkinson's disease
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8677364/
https://www.ncbi.nlm.nih.gov/pubmed/34925552
http://dx.doi.org/10.1155/2021/7199007
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