Abstract
It is challenging to understand the inter-muscular interactions from electromyogram (EMG) signals in the research of human movements. Based on ordinal pattern analysis, this paper proposes a mutual information (MI) measure to describe correlations of EMG recordings during hand open and hand close states. Linear discriminant analysis (LDA) is utilized to evaluate the performance of the MI measure for identifying different hand states from various subjects. Experimental results show that the MI measure is effective to extract correlations among EMG recordings, with which the different human hand open and close states have been successfully distinguished, and thus the MI measure is able to reveal the characteristics of intermuscular interactions from EMG signals.
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References
McGill, K.C., Marateb, H.R.: Rigorous a Posteriori Assessment of Accuracy in EMG Decomposition. IEEE Trans. Neural. Syst. Rehabil. Eng. 19, 54–63 (2011)
Farfan, F.D., Politti, J.C., Felice, C.J.: Evaluation of EMG processing techniques using Information Theory. BioMedical Engineering OnLine 9, 72 (2010)
Artemiadis, P.K., Kyriakopoulos, K.J.: An EMG-based robot control scheme robust to time-varying EMG signal features. IEEE Trans. Inf. Technol. Biomed. 14, 582–588 (2010)
Alonso, J.F., Mananas, M.A., Hoyer, D., Topor, Z.L., Bruce, E.N.: Evaluation of respiratory muscles activity by means of cross mutual information function at different levels of ventilatory effort. IEEE Trans. Biomed. Eng. 54, 1573–1582 (2007)
Mananas, M.A., Fiz, J.A., Morera, J., Caminal, P.: Analyzing dynamic EMG and VMG signals of respiratory muscles. IEEE Eng. Med. Biol. Mag. 20, 125–132 (2001)
Bruce, E.N., Akerson, L.M.: High-frequency oscillations in human electromyograms during voluntary contractions. J. Neurophysiol. 56, 542–553 (1986)
Semmler, J.G., Nordstrom, M.A.: A comparison of cross-correlation and surface EMG techniques used to quantify motor unit synchronization in humans. J. Neurosci. Methods 90, 47–55 (1999)
Hlavackova-Schindler, K., Palus, M., Vejmelka, M., Bhattacharya, J.: Causality detection based on information-theoretic approaches in time series analysis. Physics Reports 441, 1–46 (2007)
Bandt, C., Pompe, B.: Permutation entropy: a natural complexity measure for time series. Phys. Rev. Lett. 88, 174102 (2002)
Li, X., Ouyang, G.: Estimating coupling direction between neuronal populations with permutation conditional mutual information. Neuroimage 52, 497–507 (2010)
Webb, A.R.: Statistical pattern recognition, 2nd edn. Wiley, Chichester (2006)
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Ouyang, G., Ju, Z., Liu, H. (2012). Mutual Information Analysis with Ordinal Pattern for EMG Based Hand Motion Recognition. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33509-9_50
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DOI: https://doi.org/10.1007/978-3-642-33509-9_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33508-2
Online ISBN: 978-3-642-33509-9
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