Cargando…

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

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 (C...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Yazhou, Li, Guangsheng, Luk, Keith D. K., Hu, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5443771/
https://www.ncbi.nlm.nih.gov/pubmed/28539587
http://dx.doi.org/10.1038/s41598-017-02555-w
_version_ 1783238614672474112
author Wang, Yazhou
Li, Guangsheng
Luk, Keith D. K.
Hu, Yong
author_facet Wang, Yazhou
Li, Guangsheng
Luk, Keith D. K.
Hu, Yong
author_sort Wang, Yazhou
collection PubMed
description 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 Online
Article
Text
id pubmed-5443771
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-54437712017-05-26 Component analysis of somatosensory evoked potentials for identifying spinal cord injury location Wang, Yazhou Li, Guangsheng Luk, Keith D. K. Hu, Yong Sci Rep Article 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. Nature Publishing Group UK 2017-05-24 /pmc/articles/PMC5443771/ /pubmed/28539587 http://dx.doi.org/10.1038/s41598-017-02555-w Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Wang, Yazhou
Li, Guangsheng
Luk, Keith D. K.
Hu, Yong
Component analysis of somatosensory evoked potentials for identifying spinal cord injury location
title 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_short 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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5443771/
https://www.ncbi.nlm.nih.gov/pubmed/28539587
http://dx.doi.org/10.1038/s41598-017-02555-w
work_keys_str_mv AT wangyazhou componentanalysisofsomatosensoryevokedpotentialsforidentifyingspinalcordinjurylocation
AT liguangsheng componentanalysisofsomatosensoryevokedpotentialsforidentifyingspinalcordinjurylocation
AT lukkeithdk componentanalysisofsomatosensoryevokedpotentialsforidentifyingspinalcordinjurylocation
AT huyong componentanalysisofsomatosensoryevokedpotentialsforidentifyingspinalcordinjurylocation