Frequency analysis of lower extremity electromyography signals for the quantitative diagnosis of dystonia

Shanette A. Go; Krista Coleman-Wood; Kenton R. Kaufman

doi:10.1016/j.jelekin.2013.11.002

Frequency analysis of lower extremity electromyography signals for the quantitative diagnosis of dystonia

Shanette A. Go
, Krista Coleman-Wood
, Kenton R. Kaufman

Orthopedic Surgery

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

9 Scopus citations

Abstract

The purpose of this study was to develop an objective, quantitative tool for the diagnosis of lower extremity dystonia. Frequency domain analysis was performed on surface and fine-wire electromyography (EMG) signals collected from the lower extremity musculature of ten patients with suspected dystonia while performing walking trials at self-selected speeds. The median power frequency (MdPF) and percentage of total power contained in the low frequency range (%AUC_Total) were determined for each muscle studied. Muscles exhibiting clinical signs of dystonia were found to have a shift of the MdPF to lower frequencies and a simultaneous increase in the %AUC_Total. A threshold frequency of 70Hz identified dystonic muscles with 73% sensitivity and 63% specificity. These results indicate that frequency analysis can accurately distinguish dystonic from non-dystonic muscles.

Original language	English (US)
Pages (from-to)	31-36
Number of pages	6
Journal	Journal of Electromyography and Kinesiology
Volume	24
Issue number	1
DOIs	https://doi.org/10.1016/j.jelekin.2013.11.002
State	Published - Feb 2014

Keywords

Dystonia
Electromyography
Frequency analysis
Lower extremity

ASJC Scopus subject areas

Neuroscience (miscellaneous)
Biophysics
Clinical Neurology

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10.1016/j.jelekin.2013.11.002

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@article{8c8ab19a04064093a5c33843e706d6d2,

title = "Frequency analysis of lower extremity electromyography signals for the quantitative diagnosis of dystonia",

abstract = "The purpose of this study was to develop an objective, quantitative tool for the diagnosis of lower extremity dystonia. Frequency domain analysis was performed on surface and fine-wire electromyography (EMG) signals collected from the lower extremity musculature of ten patients with suspected dystonia while performing walking trials at self-selected speeds. The median power frequency (MdPF) and percentage of total power contained in the low frequency range (\%AUCTotal) were determined for each muscle studied. Muscles exhibiting clinical signs of dystonia were found to have a shift of the MdPF to lower frequencies and a simultaneous increase in the \%AUCTotal. A threshold frequency of 70Hz identified dystonic muscles with 73\% sensitivity and 63\% specificity. These results indicate that frequency analysis can accurately distinguish dystonic from non-dystonic muscles.",

keywords = "Dystonia, Electromyography, Frequency analysis, Lower extremity",

author = "Go, \{Shanette A.\} and Krista Coleman-Wood and Kaufman, \{Kenton R.\}",

note = "Funding Information: Shanette Go was supported by the National Institute of General Medical Sciences (T32 GM 65841). The authors would also like to thank Kathie Bernhardt and Diana Hansen for their assistance with data collection and reduction. ",

year = "2014",

month = feb,

doi = "10.1016/j.jelekin.2013.11.002",

language = "English (US)",

volume = "24",

pages = "31--36",

journal = "Journal of Electromyography and Kinesiology",

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publisher = "Elsevier Ltd",

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AU - Go, Shanette A.

AU - Coleman-Wood, Krista

AU - Kaufman, Kenton R.

N1 - Funding Information: Shanette Go was supported by the National Institute of General Medical Sciences (T32 GM 65841). The authors would also like to thank Kathie Bernhardt and Diana Hansen for their assistance with data collection and reduction.

PY - 2014/2

Y1 - 2014/2

N2 - The purpose of this study was to develop an objective, quantitative tool for the diagnosis of lower extremity dystonia. Frequency domain analysis was performed on surface and fine-wire electromyography (EMG) signals collected from the lower extremity musculature of ten patients with suspected dystonia while performing walking trials at self-selected speeds. The median power frequency (MdPF) and percentage of total power contained in the low frequency range (%AUCTotal) were determined for each muscle studied. Muscles exhibiting clinical signs of dystonia were found to have a shift of the MdPF to lower frequencies and a simultaneous increase in the %AUCTotal. A threshold frequency of 70Hz identified dystonic muscles with 73% sensitivity and 63% specificity. These results indicate that frequency analysis can accurately distinguish dystonic from non-dystonic muscles.

AB - The purpose of this study was to develop an objective, quantitative tool for the diagnosis of lower extremity dystonia. Frequency domain analysis was performed on surface and fine-wire electromyography (EMG) signals collected from the lower extremity musculature of ten patients with suspected dystonia while performing walking trials at self-selected speeds. The median power frequency (MdPF) and percentage of total power contained in the low frequency range (%AUCTotal) were determined for each muscle studied. Muscles exhibiting clinical signs of dystonia were found to have a shift of the MdPF to lower frequencies and a simultaneous increase in the %AUCTotal. A threshold frequency of 70Hz identified dystonic muscles with 73% sensitivity and 63% specificity. These results indicate that frequency analysis can accurately distinguish dystonic from non-dystonic muscles.

KW - Dystonia

KW - Electromyography

KW - Frequency analysis

KW - Lower extremity

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UR - https://www.scopus.com/pages/publications/84892483357#tab=citedBy

U2 - 10.1016/j.jelekin.2013.11.002

DO - 10.1016/j.jelekin.2013.11.002

M3 - Article

C2 - 24295542

AN - SCOPUS:84892483357

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SP - 31

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JO - Journal of Electromyography and Kinesiology

JF - Journal of Electromyography and Kinesiology

IS - 1

ER -

Frequency analysis of lower extremity electromyography signals for the quantitative diagnosis of dystonia

Abstract

Keywords

ASJC Scopus subject areas

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