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

Mir, Hasan; Al-Nashash, Hasan; Kortelainen, Jukka; All, Angelo (2017-05-02)
 
Avaa tiedosto
Lataukset: 

URL:
https://doi.org/10.1109/TBME.2017.2700498

Mir, Hasan
Al-Nashash, Hasan
Kortelainen, Jukka
All, Angelo
Institute of Electrical and Electronics Engineers
02.05.2017

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

https://rightsstatements.org/vocab/InC/1.0/
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
https://rightsstatements.org/vocab/InC/1.0/
doi:https://doi.org/10.1109/TBME.2017.2700498
Näytä kaikki kuvailutiedot
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2019041512353
Tiivistelmä

Abstract

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.

Kokoelmat