University of Oulu

H. Mir, H. Al-Nashash, J. Kortelainen and A. All, "Novel Modeling of Somatosensory Evoked Potentials for the Assessment of Spinal Cord Injury," in IEEE Transactions on Biomedical Engineering, vol. 65, no. 3, pp. 511-520, March 2018. doi: 10.1109/TBME.2017.2700498

Novel modeling of somatosensory evoked potentials for the assessment of spinal cord injury

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Author: Mir, Hasan1; Al-Nashash, Hasan2,3; Kortelainen, Jukka4;
Organizations: 1Department of Electrical Engineering, American University of Sharjah, UAE
2Department of Electrical Engineering, American University of Sharjah
3SINAPSE Institute, National University of Singapore
4Physiological Signal Analysis Team, Center for Machine Vision and Signal Analysis, and the Department of Clinical Neurophysiology, University of Oulu
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
Persistent link:
Language: English
Published: Institute of Electrical and Electronics Engineers, 2018
Publish Date: 2019-04-15


Objective: Previous work has shown that differences in the somatosensory evoked potential (SEP) signals between a normal spinal pathway and spinal pathway affected by spinal cord injury (SCI) provide a means to study the degree of injury. This paper proposes a novel quantitative SCI assessment method using time-domain SEP signals.

Methods: A pruned and unstructured fit between SEP signals from a normal spinal pathway and a spinal pathway affected by SCI is developed using methods inspired by recent results in sparse reconstruction theory. The coefficients from the resulting fit are used to develop a quantitative assessment of SCI that is tested on actual SEP signals collected from rodents that have been subjected to partial and complete spinal cord transection.

Results: The proposed method provides a rich parametric measure that integrates SEP amplitude, time latency, and morphology, while exhibiting a high degree of correlation with existing subjective and quantitative SCI assessment methods.

Conclusion: The proposed SCI encapsulates a model of the injury to quantify SCI. Significance: The proposed SCI quantification method may be used to complement existing SCI assessment methods.

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Series: IEEE transactions on bio-medical engineering
ISSN: 0018-9294
ISSN-E: 1558-2531
ISSN-L: 0018-9294
Volume: 65
Issue: 3
Pages: 511 - 520
DOI: 10.1109/TBME.2017.2700498
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
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