Publications

  1. Chen M, Holobar A, Zhang X, Zhou P 2016 Progressive fastICA peel-off and convolution kernel compensation demonstrate high agreement for high density surface EMG decomposition. Neural Plasticity, vol. 2016, pp. 1-5,

  2. Cescon., Raimondi E., Začesta V. Drusany-Starič K., Martsidis K., Merletti R., Characterization of the motor units of the external anal sphincter in pregnant women with multichannel surface EMG, Int. Urogynecol J. DOI 10.1007/s00192-014-2356-3 2014a,

  3. Cescon C., Riva D., Začesta V., Drusany-Starič K., Martsidis K., Protsepko O., Baessler K. , Merletti R., Effect of vaginal delivery on the external anal sphincter muscle innervation pattern evaluated by multichannel surface EMG: results of the multicentre study TASI-2, Int Urogynecol J DOI 10.1007/s00192-014-2375-0 2014b (in press),

  4. Dideriksen J L, Gallego J A, Holobar A, Rocon E, Pons J L, Farina D 2015 One central oscillatory drive is compatible with experimental motor unit behaviour in essential and Parkinsonian tremor Journal of neural engineering vol. 12, no. 4, pp. 1-17,

  5. Dideriksen J L, Holobar A, Falla D 2016 Preferential distribution of nociceptive input to motoneurons with muscle units in the cranial portion of the upper trapezius muscle. Journal of neurophysiology, vol. 116, no. 2, pp. 611-618,

  6. Farina D and Merletti R 2001 Effect of electrode shape on spectral features of surface detected motor unit action potentials Acta. Physiol. Pharmacol. Bulg. 26 63–66,

  7. Farina D, Cescon C, Merletti R 2002 Influence of anatomical, physical, and detection-system parameters on surface EMG Biol. Cybern. 86 445–456,

  8. Farina D, Mesin L, Martina S, Merletti R 2004c A surface EMG generation model with multilayer cylindrical description of the volume conductor IEEE Trans. Biomed. Eng. 51 415–426,

  9. Farina D, Negro F, Gazzoni M, Enoka RM (2008). Detecting the unique representation of motor-unit action potentials in the surface electromyogram. J. Neurophysiol. 100: 1223–1233,

  10. Farina D, Holobar A 2015 Human-machine interfacing by decoding surface electromyogram. IEEE signal processing magazine, vol. 32, no. 1, pp. 115-120,

  11. Farina D, Holobar A 2016 Characterization of human motor units from surface EMG decomposition. Proceedings of the IEEE, vol. 104, no. 2, pp. 353-373,

  12. Farina D, Holobar A, Merletti R, Enoka R M 2010 Decoding the neural drive to muscles from the surface electromyogram Clin. Neurophysiol. 121 1616–1623,

  13. Farina D, Negro F 2012 Accessing the neural drive to muscle and translation to neurorehabilitation technologies. IEEE Rev Biomed Eng. 5 3-14,

  14. Gallego J A, Holobar A, Glaser V, et al. 2015 The phase difference between neural drives to antagonist muscles in essential tremor is associated with the relative strength of supraspinal and afferent input. The Journal of neuroscience, vol. 35, no. 23, pp. 8925-8937,

  15. Holobar A and Zazula D 2004 Correlation-based decomposition of surface electromyograms at low contraction forces Med. Biol. Eng. Comput. 42 487–495,

  16. Holobar A and Zazula D 2007a Multichannel Blind Source Separation Using Convolution Kernel Compensation IEEE Transactions on Signal Processing 55 4487 –4496,

  17. Holobar A and Zazula D 2007b Gradient convolution kernel compensation applied to surface electromyograms. Lect. notes comput. sci. 4666 617-624,

  18. Holobar A, Farina D, Gazzoni M, Merletti R, Zazula D 2009 Estimating motor unit discharge patterns from high-density surface electromyogram Clin. Neurophysiol 120 551–562,

  19. Holobar A, Farina D, Zazula D 2016 Surface EMG decomposition, Surface electromyography : physiology, engineering and applications, IEEE Press,

  20. Holobar A, Minetto M A, Botter A, Negro F, Farina D 2010 Experimental analysis of accuracy in the identification of motor unit spike trains from high-density surface EMG IEEE Trans. Neural. Syst. Rehabil. Eng. 18 221–229,

  21. Holobar A, Glaser V, Gallego J A, Dideriksen J L, Farina D 2012 Non-invasive characterization of motor unit behaviour in pathological tremor J. Neural. Eng. 9 056011,

  22. Holobar A, Minetto M A, Farina D 2014 Accurate identification of motor unit discharge patterns from high-density surface EMG and validation with a novel signal-based performance metric J. Neural Eng. 11 016008,

  23. Holobar A and Farina D 2014 Blind source identification from the multichannel surface electromyogram, Physiol. Meas. 35 R143-R165,

  24. Li X, Holobar A, Gazzoni M, Merletti R, Rymer W Z, Zhou P 2015 Examination of poststroke alteration in motor unit firing behavior using high-density surface EMG decomposition. IEEE transactions on bio-medical engineering, vol. 62, no. 5, pp. 1242-1252,

  25. Kapelner T, Jiang N, Holobar A, Vujaklija I, Roche A D, Farina D, Aszmann O 2016 Motor unit characteristics after targeted muscle reinnervation. PloS one, vol. 11, iss. 2, pp. 1-7, e149772,

  26. Marateb H R, McGill K C, Holobar A, Lateva Z C, Mansourian M, Merletti R 2011 Accuracy assessment of CKC high-density surface EMG decomposition in biceps femoris muscle J. Neural. Eng. 8 066002,

  27. Merletti R, Holobar A, Farina D. Analysis of motor units with high-density surface electromyography. J. Electromyogr. Kinesiol. 2008;18:879-890,

  28. Merletti R, Aventaggiato M, Botter A, Holobar A, Marateb H, Vieira T M M 2010 Advances in surface EMG: recent progress in detection and processing techniques Crit. Rev. Biomed. Eng. 38 305–345,

  29. Merletti R and Parker P J 2004 Electromyography: Physiology, Engineering, and Non-Invasive Applications (IEEE Press, Piscataway New Jersey),

  30. Negro F, Muceli S, Castronovo A M, Holobar A, Farina D. 2016 Multi-channel intramuscular and surface EMG decomposition by convolutive blind source separation. Journal of neural engineering, vol. 13, no. 2, pp. 1-17,

  31. Potočnik B, Holobar A 2009 A new optical flow model for motor unit conduction velocity estimation in multichannel surface EMG. Computers in Biology and Medicine, April 2017, vol. 83, pp. 59-68,

  32. Negro, F., Holobar, A., and Farina, D. (2009). Fluctuations in isometric muscle force can be described by one linear projection of low-frequency components of motor unit discharge rates. J. Physiol. (Lond.) 587, 5925–5938,

  33. Radeke J, van Dijk J P, Holobar A, Lapatki B G 2013 Electrophysiological method for examining the muscle fiber architecture of the upper lip in cleft-lip subjects, Journal of Orofacial Orthopedics (in Press),

  34. Watanabe K, Gazzoni M, Holobar A, Miyamoto T, Fukuda K, Merletti R, Moritani T 2013 Motor unit firing pattern of vastus lateralis muscle in type 2 diabetes mellitus patients Muscle Nerve 48 806-813,

  35. Watanabe K, Holobar A, Kouzaki M, Ogawa M, Akima H, Moritani T 2016 Age-related changes in motor unit firing pattern of vastus lateralis muscle during low-moderate contraction. Age, vol. 38, iss. 3, pp. 1-14,

  36. Yavuz U Ş, Sebik O, Negro F, Holobar A, Frömmel C, Türker K S, Farina D 2015 Estimating reflex responses in large populations of motor units by decomposition of the high-density surface electromyogram. Journal of physiology, vol. 593, iss. 19, pp. 4305-4318.