Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals
Appropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entr...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2017-09-01
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| Series: | Frontiers in Physiology |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fphys.2017.00679/full |
| _version_ | 1818922750477074432 |
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| author | Emma F. Hodson-Tole James M. Wakeling |
| author_facet | Emma F. Hodson-Tole James M. Wakeling |
| author_sort | Emma F. Hodson-Tole |
| collection | DOAJ |
| description | Appropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entropy. Here we developed a theoretical framework to simulate the effect of variability in burst duration, activation duty cycle, and intensity on the Entropic Half-Life (EnHL) in myoelectric signals. EnHLs were predicted to be <40 ms, and to vary with fluctuations in myoelectric signal amplitude and activation duty cycle. Comparison with myoelectic data from rats walking and running at a range of speeds and inclines confirmed the range of EnHLs, however, the direction of EnHL change in response to altered locomotor demand was not correctly predicted. The discrepancy reflected different associations between the ratio of the standard deviation and mean signal intensity (Ist:It¯) and duty factor in simulated and physiological data, likely reflecting additional information in the signals from the physiological data (e.g., quiescent phase content; variation in action potential shapes). EnHL could have significant value as a novel marker of neuromuscular responses to alterations in perceived locomotor task complexity and intensity. |
| first_indexed | 2024-12-20T01:58:30Z |
| format | Article |
| id | doaj.art-3036906eb03c4105b1708ad9ab3f9ad6 |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-12-20T01:58:30Z |
| publishDate | 2017-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-3036906eb03c4105b1708ad9ab3f9ad62022-12-21T19:57:25ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2017-09-01810.3389/fphys.2017.00679271630Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric SignalsEmma F. Hodson-Tole0James M. Wakeling1School of Healthcare Science, Manchester Metropolitan UniversityManchester, United KingdomDepartment of Biomedical Physiology and Kinesiology, Simon Fraser UniversityBurnaby, BC, CanadaAppropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entropy. Here we developed a theoretical framework to simulate the effect of variability in burst duration, activation duty cycle, and intensity on the Entropic Half-Life (EnHL) in myoelectric signals. EnHLs were predicted to be <40 ms, and to vary with fluctuations in myoelectric signal amplitude and activation duty cycle. Comparison with myoelectic data from rats walking and running at a range of speeds and inclines confirmed the range of EnHLs, however, the direction of EnHL change in response to altered locomotor demand was not correctly predicted. The discrepancy reflected different associations between the ratio of the standard deviation and mean signal intensity (Ist:It¯) and duty factor in simulated and physiological data, likely reflecting additional information in the signals from the physiological data (e.g., quiescent phase content; variation in action potential shapes). EnHL could have significant value as a novel marker of neuromuscular responses to alterations in perceived locomotor task complexity and intensity.http://journal.frontiersin.org/article/10.3389/fphys.2017.00679/fullEMGsample entropylocomotionmotor controlcycling |
| spellingShingle | Emma F. Hodson-Tole James M. Wakeling Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals Frontiers in Physiology EMG sample entropy locomotion motor control cycling |
| title | Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
| title_full | Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
| title_fullStr | Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
| title_full_unstemmed | Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
| title_short | Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
| title_sort | movement complexity and neuromechanical factors affect the entropic half life of myoelectric signals |
| topic | EMG sample entropy locomotion motor control cycling |
| url | http://journal.frontiersin.org/article/10.3389/fphys.2017.00679/full |
| work_keys_str_mv | AT emmafhodsontole movementcomplexityandneuromechanicalfactorsaffecttheentropichalflifeofmyoelectricsignals AT jamesmwakeling movementcomplexityandneuromechanicalfactorsaffecttheentropichalflifeofmyoelectricsignals |