Component analysis of somatosensory evoked potentials for identifying spinal cord injury location

Abstract This study aims to determine whether the time-frequency components (TFCs) of somatosensory evoked potentials (SEPs) can be used to identify the specific location of a compressive spinal cord injury using a classification technique. Waveforms of SEPs after compressive injuries at various loc...

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Autores principales:	Yazhou Wang, Guangsheng Li, Keith D. K. Luk, Yong Hu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9463bc3df4d5486ab4e9ef0da6a8f6a2
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spelling	oai:doaj.org-article:9463bc3df4d5486ab4e9ef0da6a8f6a22021-12-02T16:07:03ZComponent analysis of somatosensory evoked potentials for identifying spinal cord injury location10.1038/s41598-017-02555-w2045-2322https://doaj.org/article/9463bc3df4d5486ab4e9ef0da6a8f6a22017-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-02555-whttps://doaj.org/toc/2045-2322Abstract This study aims to determine whether the time-frequency components (TFCs) of somatosensory evoked potentials (SEPs) can be used to identify the specific location of a compressive spinal cord injury using a classification technique. Waveforms of SEPs after compressive injuries at various locations (C4, C5 and C6) in rat spinal cords were decomposed into a series of TFCs using a high-resolution time-frequency analysis method. A classification method based on support vector machine (SVM) was applied to the distributions of these TFCs among different pathological locations. The difference among injury locations manifests itself in different categories of SEP TFCs. High-energy TFCs of normal-state SEPs have significantly higher power and frequency than those of injury-state SEPs. The location of C5 is characterized by a unique distribution pattern of middle-energy TFCs. The difference between C4 and C6 is evidenced by the distribution pattern of low-energy TFCs. The proposed classification method based on SEP TFCs offers a discrimination accuracy of 80.2%. In this study, meaningful information contained in various SEP components was investigated and used to propose a new application of SEPs for identification of the location of pathological changes in the cervical spinal cord.Yazhou WangGuangsheng LiKeith D. K. LukYong HuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yazhou Wang Guangsheng Li Keith D. K. Luk Yong Hu Component analysis of somatosensory evoked potentials for identifying spinal cord injury location
description	Abstract This study aims to determine whether the time-frequency components (TFCs) of somatosensory evoked potentials (SEPs) can be used to identify the specific location of a compressive spinal cord injury using a classification technique. Waveforms of SEPs after compressive injuries at various locations (C4, C5 and C6) in rat spinal cords were decomposed into a series of TFCs using a high-resolution time-frequency analysis method. A classification method based on support vector machine (SVM) was applied to the distributions of these TFCs among different pathological locations. The difference among injury locations manifests itself in different categories of SEP TFCs. High-energy TFCs of normal-state SEPs have significantly higher power and frequency than those of injury-state SEPs. The location of C5 is characterized by a unique distribution pattern of middle-energy TFCs. The difference between C4 and C6 is evidenced by the distribution pattern of low-energy TFCs. The proposed classification method based on SEP TFCs offers a discrimination accuracy of 80.2%. In this study, meaningful information contained in various SEP components was investigated and used to propose a new application of SEPs for identification of the location of pathological changes in the cervical spinal cord.
format	article
author	Yazhou Wang Guangsheng Li Keith D. K. Luk Yong Hu
author_facet	Yazhou Wang Guangsheng Li Keith D. K. Luk Yong Hu
author_sort	Yazhou Wang
title	Component analysis of somatosensory evoked potentials for identifying spinal cord injury location
title_short	Component analysis of somatosensory evoked potentials for identifying spinal cord injury location
title_full	Component analysis of somatosensory evoked potentials for identifying spinal cord injury location
title_fullStr	Component analysis of somatosensory evoked potentials for identifying spinal cord injury location
title_full_unstemmed	Component analysis of somatosensory evoked potentials for identifying spinal cord injury location
title_sort	component analysis of somatosensory evoked potentials for identifying spinal cord injury location
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/9463bc3df4d5486ab4e9ef0da6a8f6a2
work_keys_str_mv	AT yazhouwang componentanalysisofsomatosensoryevokedpotentialsforidentifyingspinalcordinjurylocation AT guangshengli componentanalysisofsomatosensoryevokedpotentialsforidentifyingspinalcordinjurylocation AT keithdkluk componentanalysisofsomatosensoryevokedpotentialsforidentifyingspinalcordinjurylocation AT yonghu componentanalysisofsomatosensoryevokedpotentialsforidentifyingspinalcordinjurylocation
_version_	1718384791023255552

Component analysis of somatosensory evoked potentials for identifying spinal cord injury location

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