Marul A: SEMG based Facial Expression Recognition in Bipolar configuration. J Comp Sci 2011, 7(9):1407415. 17. Sawarkar KG: Analysis and Inference of EMG Applying FFT. Mumbai, India: Proceeding of SPIT-IEEE Colloquium and International Conference; 2007:1. 18. Subasi A, Kiymik MK: Muscle fatigue detection in EMG utilizing time-frequency strategies, ICA and neural networks. J Med Syst 2010, 34(four):77585. 19. Tkach D, Huang H, Kuiken TA: Study study of stability of time-domain features for electromyographic pattern recognition. J Neuroeng Rehabil 2010, 7:21. 20. Ang LBP, Belen EF, Bernardo RA, Boongaling ER, Briones GH, Coronel JB: Facial expression recognition through pattern analysis of facial muscle movements utilizing electromyogram sensors. In Proceedings on the TENCON 2004 IEEE Area 10 Conference: 214 Nov. 2004. 3rd edition. Chiang Mai, Thailand: IEEE; 2004:60003. 21. Van den Broek EL, Lis’y V, Janssen JH, Westerink JHDM, Schut MH, Tuinenbreijer K: Affective Man achine Interface: Unveiling human feelings by way of biosignals. Biomedical Engineering Systems and Technologies: Communications in Laptop or computer and Information Science. Berlin, Germany: Springer Verlag; 2010:217. 52(Portion 1). 22. Hamedi M, Rezazadeh IM, Firoozabadi SMP: Facial gesture recognition applying two-channel biosensors configuration and fuzzy classifier: a pilot study. In Proceeding on the International Conference on Electrical, Handle and Laptop or computer Engineering: 212 June 2011. Pahang, Malaysia: IEEE; 2011:33843. 23. Hamedi M, Salleh SH, Tan TS, Ismail K, Ali J, Dee-Uam C, Pavaganun C, Yupapin PP: Human facial neural activities and gesture recognition for machine interfacing applications.Clotrimazole Int J Nanomedicine 2011, six:3461472. 24. Mohammad Rezazadeh I, Firoozabadi SM, Hu H, Hashemi Golpayegani SMR: A novel human-machine interface based on recognition of multi-channel facial bioelectric signals. Australas Phys Eng Sci Med 2011, 34(4):49713. 25. Mohammad Rezazadeh I, Firoozabadi M, Hu H, Hashemi Golpayegani MR: Figuring out the surface electrodes areas to capture facial bioelectric signals. Iran J Med Phys 2010, 7:659. 26. Englehart K, Hudgins B: A robust, real-time control scheme for multifunction myoelectric handle. IEEE Trans Biomed Eng 2003, 50(7):84854. 27. Battiti R: Applying mutual info for selecting capabilities in supervised neural net learning.Decitabine Neural Networks, IEEE Trans on 1994, 5(4):53750.PMID:24406011 28. Cover TM, Thomas JA: Entropy, relative entropy and mutual information and facts. In Components of Inform Theory. New York: John Wiley Sons; 1991:129. 29. Rechy-Ramirez EJ, Hu H: Stages for Establishing Control Systems utilizing EMG and EEG signals: A survey. Technical Report: CES-513 in College of Personal computer Science and Electronic Engineering. United kingdom: University of Essex; 2011.Hamedi et al. BioMedical Engineering On-line 2013, 12:73 http://www.biomedical-engineering-online/content/12/1/Page 22 of30. Peng HC, Lengthy F, Ding C: Function selection determined by mutual data: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans Pattern Anal Mach Intell 2005, 27(eight):1226238. 31. Asghari Oskoei M, Hu H: Myoelectric control systems–A survey. Biomed Signal Proces 2007, two(four):27594. 32. Saichon J, Chidchanok L, Suphakant P: A very quick neural mastering for classification making use of only new incoming datum. IEEE Trans Neural Netw 2010, 21(3):38192. 33. Andris F: Biomechanics of your Upper Limbs Mechanics, Modelling and Musculoskeletal Injuries. 1st edition. London, England: CRC Press; 2004.do.
