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Signal Characteristics Of EMG During Fatigue

J. H. Viitasalo, P. Komi
Published 2004 · Medicine

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SummaryElectromyographic (EMG) activity of m. rectus femoris muscle was registered from young male and female subjects during maintained isometric knee extension at 60% of maximal voluntary contraction. The following EMG parameters were analyzed for the entire fatigue time: integrated EMG (IEMG), averaged motor unit potential (AMUP) and power spectral density function (PSDF). The results indicated a slight but continuous rise of IEMG during the fatigue period. AMUP showed sensitivity to fatigue with increase in amplitude, rise time, and number of spikes counted. PSDF was also easily affected by fatigue so that the total power density curve was shifted towards lower frequencies with a high frequency decay. The mean power frequency decreased linearily as a function of fatigue time. The findings suggest that in addition to natural recruitment of new motor units the fatigue is characterized by marked reduction in the conduction velocities of action potential along the used muscle fibers.
This paper references
10.1111/j.1748-1716.1976.tb10195.x
Signal characteristics of EMG at different levels of muscle tension.
P. Komi (1976)
10.1016/0013-4694(71)90237-9
Automatic sampling and averaging of electromyographic unit potentials.
A. Lang (1971)
Dynamic spectrum analysis of myo-potentials and with special reference to muscle fatigue.
R. Kadefors (1968)
voluntary contraction of muscle
J. Vredenbregt (1972)
The relationship between the EMG activity and the force during voluntary static contractions of ' the human m . biceps
G. Rau (1970)
Localized muscle fatigue--definiton and measurement.
D. Chaffin (1973)
Quantitative evaluation of mechanical and electrical changes during fatigue loading of eccentric and concentric work.
P. Komi (1974)
"Efficiency of electrical activity" as a physiological measure of the functional state of muscle tissue.
H. Devries (1968)
10.1159/000394064
Spectral Analysis of Events in the Electromyogram
R. Kadefors (1973)
10.1113/jphysiol.1956.sp005558
The relation between force and integrated electrical activity in fatigued muscle.
R. Edwards (1956)
10.1159/000394062
Surface Electromyography in Relation to Force, Muscle Length and Endurance
J. Vredenbregt (1973)
10.1177/154193127501900405
“Measurement of Muscle Fatigue Using Electromyography”
M. M. Ayoub (1975)
Electromyography of fatigue.
G. Knowlton (1951)
10.1016/0013-4694(72)90058-2
Discharge frequency and discharge pattern of human motor units during voluntary contraction of muscle.
R. Person (1972)
10.1152/jappl.1970.29.3.358
Electrical and metabolic activities and fatigue in human isometric contraction.
E. Kuroda (1970)
10.1109/TBME.1970.4502758
An application of signal processing techniques to the study of myoelectric signals.
E. Kwatny (1970)
Measurement of muscle
D. P. Courier (1969)
10.1159/000394063
The Relationship between Integrated Electrical Activity and Force in Normal and Fatiguing Human Voluntary Muscle Contractions
J. Stephens (1973)
Autospectral and coherence patterns from two locations in the contracting biceps.
R. O'donnell (1973)
Electromyographic activity during voluntary static muscle contractions
G. Eindhoven 1970a Ran (1970)
10.1111/j.1748-1716.1975.tb05845.x
Signal characteristics of EMG with special reference to reproducibility of measurements.
J. H. Viitasalo (1975)



This paper is referenced by
10.1016/S0761-8425(07)74261-4
Étude de la fonction neuromusculaire chez des patients atteints de mucoviscidose
L. Mély (2007)
The physiological demands of 'hiking' on dinghy sailors
Ioannis Vogiatzis (1995)
10.1109/IECBES.2018.8626661
The Study and Comparison between Various Digital Filters for ECG De-noising
Thion Ming Chieng (2018)
10.1080/00140139.2020.1759699
Measurement and identification of mental workload during simulated computer tasks with multimodal methods and machine learning
Y. Ding (2020)
10.1088/1361-6579/ab2664
Hybrid scattering-LSTM networks for automated detection of sleep arousals.
P. Warrick (2019)
10.1007/BF00636598
Muscle fibre conduction velocity, mean power frequency, mean EMG voltage and force during submaximal fatiguing contractions of human quadriceps
L. Arendt-Nielsen (2004)
10.1016/j.jbiomech.2015.04.043
The influence of cycle time on shoulder fatigue responses for a fixed total overhead workload.
Clark R. Dickerson (2015)
Combined strength and endurance exercise induced fatigue and recovery
Eeva-Maria Kilpelänaho (2012)
10.1016/S0360-8352(02)00237-1
Effects of window size and load on estimated myoelectric signal power spectrum
S. M. Waly (2003)
10.1016/j.clinbiomech.2010.09.001
The specificity of fatiguing protocols affects scapular orientation: Implications for subacromial impingement.
Jaclyn N. Chopp (2011)
10.5057/KEI.11.147
Evaluation of Driver-vehicle Matching using Neck Muscle Activity and Vehicle Dynamics
Yoshiki Iwamoto (2012)
10.9746/JCMSI.8.312
On the Well-Timed Assistance in Power-Assisted Sit-to-Stand Movement
Haisong Dong (2015)
10.1007/BF00423202
Effects of fatigue and recovery on electromyographic and isometric force- and relaxation-time characteristics of human skeletal muscle
K. Häkkinen (2004)
and frequency during fatiguing dynamic contractions Effects of muscle kinematics on surface EMG amplitude
Jim R. Potvin (2015)
10.1080/17461391.2015.1068869
Measuring human locomotor control using EMG and EEG: Current knowledge, limitations and future considerations
Hendrik Enders (2016)
10.1109/ICA.2017.8068428
Real-time muscle fatigue monitoring based on median frequency of electromyography signal
Moehammad Dzaky Fauzan Ma'as (2017)
Quantifying Localized Muscle Fatigue of the Forearm during Simulations of High Pressure Cleaning Lance Tasks
Sandra Quinones-Vientos (2005)
10.1007/BF00262820
Effect of acute normobaric hypoxia on quadriceps integrated electromyogram and blood metabolites during incremental exercise to exhaustion
A. D. Taylor (2004)
10.1080/00140139.2016.1242782
Responsive upper limb and cognitive fatigue measures during light precision work: an 8-hour simulated micro-pipetting study
M. Yung (2017)
10.1016/j.medengphy.2011.04.016
Effects of monopolar and bipolar electrode configurations on surface EMG spike analysis.
David A. Gabriel (2011)
10.1109/CBMS.2014.41
EMG-Miner: Automatic Acquisition and Processing of Electromyographic Signals: First Experimentation in a Clinical Context for Gait Disorders Evaluation
Nicola Ielpo (2014)
10.1016/j.jse.2010.03.017
Superior humeral head migration occurs after a protocol designed to fatigue the rotator cuff: a radiographic analysis.
Jaclyn N. Chopp (2010)
10.1371/journal.pone.0099060
EMG and Heart Rate Responses Decline within 5 Days of Daily Whole-Body Vibration Training with Squatting
A. Rosenberger (2014)
10.1007/s00421-010-1624-2
Evaluation of muscle fatigue during 100-m front crawl
Igor Štirn (2010)
10.1155/2018/4759232
Effect of Task Failure on Intermuscular Coherence Measures in Synergistic Muscles
A. M. Castronovo (2018)
10.1109/EMBC.2012.6346712
Modeling the impulse response between pairs of EMG signals to estimate conduction delay distribution
Tahsin Hassan (2012)
Muscle activity in m.pectoralis major during bench press variations in healthy young males
A. Sahlén (2015)
10.1007/S12541-012-0194-0
Development of mirror image motion system with sEMG for shoulder rehabilitation of post-stroke hemiplegic patients
Kihan Park (2012)
The effects of neuromuscular fatigue on the complexity of isometric torque output in humans
Jamie Pethick (2016)
10.1177/00220345860650031401
Comparison of the Reproducibility of EMG Signals Recorded from Human Masseter and Lateral Pterygoid Muscles
J. Dahan (1986)
10.1136/thx.2003.020636
Peripheral muscle endurance and the oxidative profile of the quadriceps in patients with COPD
J. Allaire (2004)
10.1016/S1050-6411(02)00046-9
Amplitude-related characteristics of motor unit and M-wave potentials during fatigue. A simulation study using literature data on intracellular potential changes found in vitro.
N. Dimitrova (2002)
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