Nonlinear Analysis of Electromiography Time Series as A Diagnostic Tool for Low Back Pain

Paul Sung; Ulrich Zurcher; Miron Kaufman

Nonlinear Analysis of Electromiography Time Series as A Diagnostic Tool for Low Back Pain

Paul Sung, Ulrich Zurcher, Miron Kaufman

Cleveland State University

Research output: Contribution to journal › Article › peer-review

Abstract

A number of studies have evaluated lumbar spinal muscle fatigue using the electromyography (EMG) signal. However, back muscle fatigue studies do not consistently report endurance levels for patients with or without low back pain (LBP). In this case report, we investigated a nonlinear analysis of EMG time series that characterizes their complexity.

Original language	American English
Journal	Medical Science Monitor
Volume	11
State	Published - Jan 1 2005

Keywords

nonlinear time series
electromyography
low back pain

Disciplines

Physics

Access to Document

http://www.medscimonit.com/download/index/idArt/13880

Cite this

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title = "Nonlinear Analysis of Electromiography Time Series as A Diagnostic Tool for Low Back Pain",

abstract = " A number of studies have evaluated lumbar spinal muscle fatigue using the electromyography (EMG) signal. However, back muscle fatigue studies do not consistently report endurance levels for patients with or without low back pain (LBP). In this case report, we investigated a nonlinear analysis of EMG time series that characterizes their complexity.",

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AU - Zurcher, Ulrich

AU - Kaufman, Miron

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N2 - A number of studies have evaluated lumbar spinal muscle fatigue using the electromyography (EMG) signal. However, back muscle fatigue studies do not consistently report endurance levels for patients with or without low back pain (LBP). In this case report, we investigated a nonlinear analysis of EMG time series that characterizes their complexity.

AB - A number of studies have evaluated lumbar spinal muscle fatigue using the electromyography (EMG) signal. However, back muscle fatigue studies do not consistently report endurance levels for patients with or without low back pain (LBP). In this case report, we investigated a nonlinear analysis of EMG time series that characterizes their complexity.

KW - nonlinear time series

KW - electromyography

KW - low back pain

UR - https://engagedscholarship.csuohio.edu/sciphysics_facpub/290

UR - http://www.medscimonit.com/download/index/idArt/13880

M3 - Article

VL - 11

JO - Medical Science Monitor

JF - Medical Science Monitor

ER -

Nonlinear Analysis of Electromiography Time Series as A Diagnostic Tool for Low Back Pain

Abstract

Keywords

Disciplines

Access to Document

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Cite this