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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Detalles Bibliográficos
Autor principal: Zahra, Noore
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Research Article
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
Descripción
Sumario: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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