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 language | English |
|---|---|
| Article number | 206560 |
| Journal | Eurasip Journal on Advances in Signal Processing |
| Volume | 2010 |
| DOIs | |
| Publication status | Published - 2010 Nov 19 |
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All Science Journal Classification (ASJC) codes
- Signal Processing
- Information Systems
- Hardware and Architecture
- Electrical and Electronic Engineering
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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 journal › Article
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
AN - SCOPUS:78249274963
VL - 2010
JO - Eurasip Journal on Advances in Signal Processing
JF - Eurasip Journal on Advances in Signal Processing
SN - 1687-6172
M1 - 206560
ER -