An examination of the Runs Test, Reverse Arrangements Test, and modified Reverse Arrangements Test for assessing surface EMG signal stationarity

The purpose of this study was to examine the accuracy of the Runs Test, Reverse Arrangements Test, and modified Reverse Arrangements Test for assessing stationarity of surface electromyographic (EMG) signals. Five stationary signals were generated by custom programs written with LabVIEW programming software. These signals consisted of sine waves, sums of sine waves, and sums of sine waves and random noise. The sixth signal was a stationary computer generated surface EMG signal downloaded from the surface EMG for the non-invasive assessment of muscles (SENIAM) project database. There were no changes in the amplitude or frequency contents of the stationary signals over time. Several nonstationary signals were also created, including a nonstationary chirp signal generated with LabVIEW programming software, a nonstationary computer generated surface EMG signal downloaded from the SENIAM project database, and a real surface EMG signal recorded from the biceps brachii during a concentric isokinetic muscle action of the forearm flexors at a velocity of 30 degrees s(-1). Both the stationary and nonstationary signals were tested for stationarity using the Runs Test, Reverse Arrangements Test, and modified Reverse Arrangements Test. The results indicated that each of the three stationarity tests demonstrated at least one form of inaccuracy (i.e. false positive and/or false negative results) in examining the stationarity of the test signals. These findings may reflect the fact that these tests were designed to determine whether or not a signal is random, rather than examine signal stationarity exclusively. Thus, the Runs Test, Reverse Arrangements Test, and modified Reverse Arrangements Test may not be appropriate for assessing stationarity in surface EMG signals.

[1]  M Solomonow,et al.  Electromyogram power spectra frequencies associated with motor unit recruitment strategies. , 1990, Journal of applied physiology.

[2]  T. Moritani,et al.  Motor unit activity and surface electromyogram power spectrum during increasing force of contraction , 2004, European Journal of Applied Physiology and Occupational Physiology.

[3]  H. Hermens,et al.  European recommendations for surface electromyography: Results of the SENIAM Project , 1999 .

[4]  R E Gander,et al.  Changes in the myoelectric signal (MES) power spectra during dynamic contractions. , 1989, Electroencephalography and clinical neurophysiology.

[5]  S. Siegel,et al.  Nonparametric Statistics for the Behavioral Sciences , 2022, The SAGE Encyclopedia of Research Design.

[6]  Travis W. Beck,et al.  Mechanomyographic and electromyographic time and frequency domain responses during submaximal to maximal isokinetic muscle actions of the biceps brachii , 2004, European Journal of Applied Physiology.

[7]  N Ishii,et al.  Stationarity and normality test for biomedical data. , 1977, Computer programs in biomedicine.

[8]  Joseph P Weir,et al.  MECHANOMYOGRAPHIC AND ELECTROMYOGRAPHIC RESPONSES OF THE VASTUS MEDIALIS MUSCLE DURING ISOMETRIC AND CONCENTRIC MUSCLE ACTIONS , 2005, Journal of strength and conditioning research.

[9]  Alan V. Oppenheim,et al.  Discrete-Time Signal Pro-cessing , 1989 .

[10]  M Knaflitz,et al.  Time-frequency methods applied to muscle fatigue assessment during dynamic contractions. , 1999, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[11]  M. Knaflitz,et al.  Analysis of myoelectric signals recorded during dynamic contractions , 1996 .

[12]  D. Gravel,et al.  Normality and stationarity of EMG signals of elbow flexor muscles during ramp and step isometric contractions. , 1997, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[13]  G. Inbar,et al.  Autoregressive Modeling of Surface EMG and Its Spectrum with Application to Fatigue , 1987, IEEE Transactions on Biomedical Engineering.

[14]  J. Karlsson,et al.  An estimation of the influence of force decrease on the mean power spectral frequency shift of the EMG during repetitive maximum dynamic knee extensions. , 2003, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[15]  J. S. Petrofsky,et al.  Frequency and amplitude analysis of the EMG during exercise on the bicycle ergometer , 1979, European Journal of Applied Physiology and Occupational Physiology.

[16]  R. Merletti,et al.  Surface EMG signal processing during isometric contractions. , 1997, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[17]  Gideon F. Inbar,et al.  On Surface EMG Spectral Characterization and Its Application to Diagnostic Classification , 1984, IEEE Transactions on Biomedical Engineering.

[18]  G. Inbar,et al.  Monitoring surface EMG spectral changes by the zero crossing rate , 2006, Medical and Biological Engineering and Computing.

[19]  Jessica Elert,et al.  The influences of muscle fibre proportions and areas upon EMG during maximal dynamic knee extensions , 2000, European Journal of Applied Physiology.

[20]  T J Housh,et al.  Comparison of Fourier and wavelet transform procedures for examining mechanomyographic and electromyographic frequency versus isokinetic torque relationships. , 2005, Electromyography and clinical neurophysiology.

[21]  L. Lindstrom,et al.  Muscular fatigue and action potential conduction velocity changes studied with frequency analysis of EMG signals. , 1970, Electromyography.

[22]  R. Quiroga,et al.  Stationarity of the EEG series , 1995 .

[23]  P. Zipp,et al.  Recommendations for the standardization of lead positions in surface electromyography , 1982, European Journal of Applied Physiology and Occupational Physiology.

[24]  Sergio Silvestri,et al.  On the robust utilization of non-parametric tests for evaluation of combined cyclical and monotonic drift , 2001 .

[25]  C. D. De Luca,et al.  Myoelectric signal conduction velocity and spectral parameters: influence of force and time. , 1985, Journal of applied physiology.

[26]  J Duchêne,et al.  Surface electromyogram during voluntary contraction: processing tools and relation to physiological events. , 1993, Critical reviews in biomedical engineering.

[27]  Joseph P Weir,et al.  Comparison of Fourier and wavelet transform procedures for examining the mechanomyographic and electromyographic frequency domain responses during fatiguing isokinetic muscle actions of the biceps brachii. , 2005, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[28]  T. Chau,et al.  Investigating the stationarity of paediatric aspiration signals , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[29]  B Gerdle,et al.  Do the fibre-type proportion and the angular velocity influence the mean power frequency of the electromyogram? , 1988, Acta physiologica Scandinavica.

[30]  Toshihiro Ishiko,et al.  Relationships between muscle lactate accumulation and surface EMG activities during isokinetic contractions in man , 2004, European Journal of Applied Physiology and Occupational Physiology.

[31]  R Merletti,et al.  Comparison of algorithms for estimation of EMG variables during voluntary isometric contractions. , 2000, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[32]  J. Bendat,et al.  Random Data: Analysis and Measurement Procedures , 1971 .

[33]  Jun Yu,et al.  Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study , 2000, IEEE Transactions on Biomedical Engineering.

[34]  Dario Farina,et al.  Time–frequency analysis and estimation of muscle fiber conduction velocity from surface EMG signals during explosive dynamic contractions , 2005, Journal of Neuroscience Methods.

[35]  M. Akay,et al.  Analyzing surface myoelectric signals recorded during isokinetic contractions , 2001, IEEE Engineering in Medicine and Biology Magazine.

[36]  L.H. Lindstrom,et al.  Interpretation of myoelectric power spectra: A model and its applications , 1977, Proceedings of the IEEE.

[37]  G. Keppel,et al.  Design and Analysis: A Researcher's Handbook , 1976 .

[38]  T J Housh,et al.  Mean power frequency and amplitude of the mechanomyographic and electromyographic signals during incremental cycle ergometry. , 2001, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.