Cross time-frequency analysis of gastrocnemius electromyographic signals in hypertensive and nonhypertensive subjects

Patrick Mitchell, Debra Krotish, Yong June Shin, Victor Hirth

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

The effects of hypertension are chronic and continuous; it affects gait, balance, and fall risk. Therefore, it is desirable to assess gait health across hypertensive and nonhypertensive subjects in order to prevent or reduce the risk of falls. Analysis of electromyography (EMG) signals can identify age related changes of neuromuscular activation due to various neuropathies and myopathies, but it is difficult to translate these medical changes to clinical diagnosis. To examine and compare geriatrics patients with these gait-altering diseases, we acquire EMG muscle activation signals, and by use of a timesynchronized mat capable of recording pressure information, we localize the EMG data to the gait cycle, ensuring identical comparison across subjects. Using time-frequency analysis on the EMG signal, in conjunction with several parameters obtained from the time-frequency analyses, we can determine the statistical discrepancy between diseases. We base these parameters on physiological manifestations caused by hypertension, as well as other comorbities that affect the geriatrics community. Using these metrics in a small population, we identify a statistical discrepancy between a control group and subjects with hypertension, neuropathy, diabetes, osteoporosis, arthritis, and several other common diseases which severely affect the geriatrics community.

Original languageEnglish
Article number206560
JournalEurasip Journal on Advances in Signal Processing
Volume2010
DOIs
Publication statusPublished - 2010 Nov 19

Fingerprint

Electromyography
Geriatrics
Chemical activation
Medical problems
Muscle
Health

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

@article{1e6ab2aa4ba24db4b994027926f7b3ea,
title = "Cross time-frequency analysis of gastrocnemius electromyographic signals in hypertensive and nonhypertensive subjects",
abstract = "The effects of hypertension are chronic and continuous; it affects gait, balance, and fall risk. Therefore, it is desirable to assess gait health across hypertensive and nonhypertensive subjects in order to prevent or reduce the risk of falls. Analysis of electromyography (EMG) signals can identify age related changes of neuromuscular activation due to various neuropathies and myopathies, but it is difficult to translate these medical changes to clinical diagnosis. To examine and compare geriatrics patients with these gait-altering diseases, we acquire EMG muscle activation signals, and by use of a timesynchronized mat capable of recording pressure information, we localize the EMG data to the gait cycle, ensuring identical comparison across subjects. Using time-frequency analysis on the EMG signal, in conjunction with several parameters obtained from the time-frequency analyses, we can determine the statistical discrepancy between diseases. We base these parameters on physiological manifestations caused by hypertension, as well as other comorbities that affect the geriatrics community. Using these metrics in a small population, we identify a statistical discrepancy between a control group and subjects with hypertension, neuropathy, diabetes, osteoporosis, arthritis, and several other common diseases which severely affect the geriatrics community.",
author = "Patrick Mitchell and Debra Krotish and Shin, {Yong June} and Victor Hirth",
year = "2010",
month = "11",
day = "19",
doi = "10.1155/2010/206560",
language = "English",
volume = "2010",
journal = "Eurasip Journal on Advances in Signal Processing",
issn = "1687-6172",
publisher = "Springer Publishing Company",

}

Cross time-frequency analysis of gastrocnemius electromyographic signals in hypertensive and nonhypertensive subjects. / Mitchell, Patrick; Krotish, Debra; Shin, Yong June; Hirth, Victor.

In: Eurasip Journal on Advances in Signal Processing, Vol. 2010, 206560, 19.11.2010.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Cross time-frequency analysis of gastrocnemius electromyographic signals in hypertensive and nonhypertensive subjects

AU - Mitchell, Patrick

AU - Krotish, Debra

AU - Shin, Yong June

AU - Hirth, Victor

PY - 2010/11/19

Y1 - 2010/11/19

N2 - The effects of hypertension are chronic and continuous; it affects gait, balance, and fall risk. Therefore, it is desirable to assess gait health across hypertensive and nonhypertensive subjects in order to prevent or reduce the risk of falls. Analysis of electromyography (EMG) signals can identify age related changes of neuromuscular activation due to various neuropathies and myopathies, but it is difficult to translate these medical changes to clinical diagnosis. To examine and compare geriatrics patients with these gait-altering diseases, we acquire EMG muscle activation signals, and by use of a timesynchronized mat capable of recording pressure information, we localize the EMG data to the gait cycle, ensuring identical comparison across subjects. Using time-frequency analysis on the EMG signal, in conjunction with several parameters obtained from the time-frequency analyses, we can determine the statistical discrepancy between diseases. We base these parameters on physiological manifestations caused by hypertension, as well as other comorbities that affect the geriatrics community. Using these metrics in a small population, we identify a statistical discrepancy between a control group and subjects with hypertension, neuropathy, diabetes, osteoporosis, arthritis, and several other common diseases which severely affect the geriatrics community.

AB - The effects of hypertension are chronic and continuous; it affects gait, balance, and fall risk. Therefore, it is desirable to assess gait health across hypertensive and nonhypertensive subjects in order to prevent or reduce the risk of falls. Analysis of electromyography (EMG) signals can identify age related changes of neuromuscular activation due to various neuropathies and myopathies, but it is difficult to translate these medical changes to clinical diagnosis. To examine and compare geriatrics patients with these gait-altering diseases, we acquire EMG muscle activation signals, and by use of a timesynchronized mat capable of recording pressure information, we localize the EMG data to the gait cycle, ensuring identical comparison across subjects. Using time-frequency analysis on the EMG signal, in conjunction with several parameters obtained from the time-frequency analyses, we can determine the statistical discrepancy between diseases. We base these parameters on physiological manifestations caused by hypertension, as well as other comorbities that affect the geriatrics community. Using these metrics in a small population, we identify a statistical discrepancy between a control group and subjects with hypertension, neuropathy, diabetes, osteoporosis, arthritis, and several other common diseases which severely affect the geriatrics community.

UR - http://www.scopus.com/inward/record.url?scp=78249274963&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78249274963&partnerID=8YFLogxK

U2 - 10.1155/2010/206560

DO - 10.1155/2010/206560

M3 - Article

VL - 2010

JO - Eurasip Journal on Advances in Signal Processing

JF - Eurasip Journal on Advances in Signal Processing

SN - 1687-6172

M1 - 206560

ER -