Detection of the Anaerobic Threshold by Surface Electromyography
This work aims at presenting a method for automatic detection of the anaerobic thresholds by surface electromyography (RMS-slope) and compare with respective values identified by the analysis of ventilatory gas exchange. Thirteen healthy adults were submitted to a single maximal oxygen uptake test,...
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Published in | 2006 International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2006; pp. 6189 - 6192 |
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Main Authors | , , |
Format | Conference Proceeding Journal Article |
Language | English |
Published |
United States
IEEE
2006
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Subjects | |
Online Access | Get full text |
ISBN | 9781424400324 1424400325 |
ISSN | 1557-170X |
DOI | 10.1109/IEMBS.2006.260619 |
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Abstract | This work aims at presenting a method for automatic detection of the anaerobic thresholds by surface electromyography (RMS-slope) and compare with respective values identified by the analysis of ventilatory gas exchange. Thirteen healthy adults were submitted to a single maximal oxygen uptake test, being monitored the ventilatory parameters V O2 , V CO2 , and V E , and the surface EMG (SEMG) of the right vastus lateralis muscle. Each cycle of myoelectric activity was automatically detected and the time series of the mean RMS values of these cycles used for determining the SEMG threshold (SEMG-T) by linear regression. The method was successful to determine SEMG-T for all subjects, with consistent results when compared to respective anaerobic thresholds visually estimated in the ventilatory equivalent V E /VO 2 |
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AbstractList | This work aims at presenting a method for automatic detection of the anaerobic thresholds by surface electromyography (RMS-slope) and compare with respective values identified by the analysis of ventilatory gas exchange. Thirteen healthy adults were submitted to a single maximal oxygen uptake test, being monitored the ventilatory parameters V(O2), V(CO2), and V(E), and the surface EMG (SEMG) of the right vastus lateralis muscle. Each cycle of myoelectric activity was automatically detected and the time series of the mean RMS values of these cycles used for determining the SEMG threshold (SEMG-T) by linear regression. The method was successful to determine SEMG-T for all subjects, with consistent results when compared to respective anaerobic thresholds visually estimated in the ventilatory equivalent V(E)/VO(2). This work aims at presenting a method for automatic detection of the anaerobic thresholds by surface electromyography (RMS-slope) and compare with respective values identified by the analysis of ventilatory gas exchange. Thirteen healthy adults were submitted to a single maximal oxygen uptake test, being monitored the ventilatory parameters V(O2), V(CO2), and V(E), and the surface EMG (SEMG) of the right vastus lateralis muscle. Each cycle of myoelectric activity was automatically detected and the time series of the mean RMS values of these cycles used for determining the SEMG threshold (SEMG-T) by linear regression. The method was successful to determine SEMG-T for all subjects, with consistent results when compared to respective anaerobic thresholds visually estimated in the ventilatory equivalent V(E)/VO(2).This work aims at presenting a method for automatic detection of the anaerobic thresholds by surface electromyography (RMS-slope) and compare with respective values identified by the analysis of ventilatory gas exchange. Thirteen healthy adults were submitted to a single maximal oxygen uptake test, being monitored the ventilatory parameters V(O2), V(CO2), and V(E), and the surface EMG (SEMG) of the right vastus lateralis muscle. Each cycle of myoelectric activity was automatically detected and the time series of the mean RMS values of these cycles used for determining the SEMG threshold (SEMG-T) by linear regression. The method was successful to determine SEMG-T for all subjects, with consistent results when compared to respective anaerobic thresholds visually estimated in the ventilatory equivalent V(E)/VO(2). This work aims at presenting a method for automatic detection of the anaerobic thresholds by surface electromyography (RMS-slope) and compare with respective values identified by the analysis of ventilatory gas exchange. Thirteen healthy adults were submitted to a single maximal oxygen uptake test, being monitored the ventilatory parameters V O2 , V CO2 , and V E , and the surface EMG (SEMG) of the right vastus lateralis muscle. Each cycle of myoelectric activity was automatically detected and the time series of the mean RMS values of these cycles used for determining the SEMG threshold (SEMG-T) by linear regression. The method was successful to determine SEMG-T for all subjects, with consistent results when compared to respective anaerobic thresholds visually estimated in the ventilatory equivalent V E /VO 2 |
Author | Mello, R.G.T. Oliveira, L.F. Nadal, J. |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/17946746$$D View this record in MEDLINE/PubMed |
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Snippet | This work aims at presenting a method for automatic detection of the anaerobic thresholds by surface electromyography (RMS-slope) and compare with respective... |
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SubjectTerms | Adult Algorithms Anaerobic Threshold Automation Blood Blood Gas Analysis Carbon Dioxide Condition monitoring Electromyography Electromyography - instrumentation Electromyography - methods Electromyography Threshold Exercise Physiology Exercise Test Exercise Tolerance Frequency estimation Humans Linear Models Linear regression Male Muscles Oxygen - metabolism Oxygen Consumption Physiology Production Protocols Pulmonary Gas Exchange Surface EMG Testing |
Title | Detection of the Anaerobic Threshold by Surface Electromyography |
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