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dc.contributor.authorSiswoyo, Agus
dc.contributor.authorArief, Zainal
dc.contributor.authorSulistijono, Adji
dc.date.accessioned2015-03-27T02:49:56Z
dc.date.available2015-03-27T02:49:56Z
dc.date.issued2014-12
dc.identifier.citationBashashati, A., Fatourechi, M., Ward, R.K., Birch, G.E.: A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals. J. Neural Eng. 4(2), R32–R57 (2007) Boyu Wang, Feng Wan, Peng Un Mak, Pui In Mak, and Mang I Vai, Member IEEE, EEG Signals Classification for Brain Computer Interfaces Based on Gaussian Process Classifier, May, 2009 Calvo, R.A., Brown, I., Scheding, S.: Effect of experimental factors on the recognition of affective mental states through physiological measures. In: Nicholson, A., Li, X. (eds.) AI 2009. LNCS (LNAI), vol. 5866, pp. 61–70. Springer, Heidelberg (2009) Chanel, G., Kronegg, J., Grandjean, D., Pun, T.: Emotion assessment: Arousal evaluation using eeg‟s and peripheral physiological signals. In: Gunsel, B., Jain, A.K., Tekalp, A.M., Sankur, B. (eds.) MRCS 2006. LNCS, vol. 4105, pp. 530–537. Springer, Heidelberg (2006) Heijden, F., Duin, R., de Ridder, D., Tax, D.: Classification, parameter estimation and state estimation. John Wiley & Sons, Chichester (2004) Jose Principe, “Brain Machine Interfaces: Mind over Matter”, 2005. ttp://www.ece.ufl.edu/publications/ Archives/inthenews/2005/brainmachine.html Jorge Baztarrica Ochoa, EEG Signal Classification for Brain Computer Interface Applications, March 28th, 2002. Ki-Hong Kim, Hong Kee Kim, Jong-Sung Kim, Wookho Son, and Soo-Young Lee, A Biosignal-Based Human Interface Controlling a Power-Wheelchair for People with Motor Disabilities, ETRI Journal, Volume 28, Number 1, February 2006. Mustafa Ahmned Yousef dan Mustafa Ezz EL-din Mohamed, Brain Computer Interface System, Graduation Project Report, Helwan University, 2011. Olofsson, J.K., Nordin, S., Sequeira, H., Polich, J.: Affective picture processing: an integrative review of erp findings. Biol. Psychol. 77(3), 247–265 (2008) Picard, R.W., Vyzas, E., Healey, J.: Toward machine emotional intelligence: analysis of affective physiological state. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(10), 1175–1191 (2001) Rajesh Kannan. Megalingam, Athul. Asokan Thulasi, Rithun. Raj Krishna, Manoj. Katta Venkata, Ajithesh. Gupta B V, Tatikonda. Uday Dutt, Thought Controlled Wheelchair Using EEG Acquisition Device, 3rd International Conference on Advancements in Electronics and Power Engineering (ICAEPE'2013) January 8-9, 2013 Kuala Lumpur (Malaysia). Savran, A., Ciftci, K., Chanel, G., Mota, J., Viet, L., Sankur, B., Akarun, L , Caplier, A., Rombaut, M.: Emotion detection in the loop from brain signals andfacial images (2006) Shenoy, P., Krauledat, M., Blankertz, B., Rao, R., M¨uller, K.: Towards adaptive classification for bci. Journal of Neural Engineering 3(1) (2006) Tom Carlson and Jos´e del R. Mill´an, Brain–Controlled Wheelchairs: A Robotic Architecture, IEEE Robotics and Automation Magazine, 20(1): 65 – 73,, March Vijay khare, Jayashree Santhosh and Sneh Anand Manvir Bhatia,“Controlling wheelchair using Electroencephalogram (EEG)”, International Journal of Computer Science and Information Security, Vol. 8, No.2, 2010.in_ID
dc.identifier.issn1412-9612
dc.identifier.urihttp://hdl.handle.net/11617/5455
dc.description.abstractAntara otak dan bagian tubuh terhubung oleh saraf saraf dimana saraf memuat informasi untuk memerintahkan bagian tubuh. Informasi ini yang akan diklasifikasikan untuk mengetahui informasi sinyal apa yang terdapat pada otak manusia. Salah satu tujuan aplikasi yang saat ini berkembang adalah Brain Computer Interface (BCI), dimana sistem digital digunakan untuk menerjemahkan sinyal EEG untuk melakukan pengontrolan suatu perangkat. Metodologi penelitian menggunakan Fuzzy Logic Controller ini Fuzzy yang digunakan dengan metode mamdani. Untuk mengambil data sinyal otak ini menggunakan Neurosky Mindset. Hasil klasifikasi sinyal otak ini berupa sinyal yang berbeda antara lain Alfa/α, Beta/β, Tetha/θ, Gamma/δ, Attention, meditasi.in_ID
dc.language.isoidin_ID
dc.publisherUniversitas Muhammadiyah Surakartain_ID
dc.subjectKlasifikasi sinyalin_ID
dc.subjectLogika fuzzyin_ID
dc.subjectNeurosky Mindset`in_ID
dc.titleKlasifikasi Sinyal Otak Menggunakan Metode Logika Fuzzy dengan Neurosky Mindsetin_ID
dc.typeArticlein_ID


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