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By Maciej Ogorzałek, Grzegorz Surówka, Leszek Nowak, Christian Merkwirth (auth.), Ana Fred, Joaquim Filipe, Hugo Gamboa (eds.)

This publication includes the simplest papers of the second one foreign Joint convention on Biomedical Engineering platforms and applied sciences (BIOSTEC 2009), geared up by means of the Institute for structures and applied sciences of knowledge keep an eye on and Communi- tion (INSTICC), technically co-sponsored by means of the IEEE Engineering in medication and Biology Society (EMB), IEEE Circuits and structures Society (CAS) and the Workflow administration Coalition (WfMC), in cooperation with AAAI and ACM SIGART. the aim of the foreign Joint convention on Biomedical Engineering S- tems and applied sciences is to assemble researchers and practitioners, together with engineers, biologists, overall healthiness execs and informatics/computer scientists, int- ested in either theoretical advances and purposes of knowledge platforms, man made intelligence, sign processing, electronics and different engineering instruments in wisdom parts relating to biology and medication. BIOSTEC consists of 3 co-located meetings; each one makes a speciality of one of many aforementioned major wisdom parts, specifically: • BIODEVICES (International convention on Biomedical Electronics and - vices) makes a speciality of elements with regards to electronics and mechanical engineering, - pecially gear and fabrics encouraged from organic platforms and/or - dressing organic necessities. tracking units, instrumentation sensors and structures, biorobotics, micro-nanotechnologies and biomaterials are a number of the applied sciences addressed at this conference.

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Additional info for Biomedical Engineering Systems and Technologies: International Joint Conference, BIOSTEC 2009 Porto, Portugal, January 14-17, 2009, Revised Selected Papers

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38] Scheirer et al. [39] Nasoz et al. [40] Takahashi [41] Haag et al. [42] Kim et al. [43] Lisetti & Nasoz [44] Wagner et al. [45] Yoo et al. [46] Choi & Woo [47] Healey & Picard [34] Liu et al. [48] Rani et al. [49] Zhai & Barreto [50] Jones & Troen C,E C,E,S,M C,E,M,R C,E C,E,M,R M C,E,R,M C,E C,E,S C,E,B C,E,S,M,R C,E,S C,E,S C,E,R,M C,E E C,E,R,M C,E,M,S C,E,S,M,P C,E,S,P C,E,R signals 8 6 10 72 3 27 1 24 31 12 1 175 29 1 6 1 9 14 15 32 13 PCA Fisher SFS, Fisher SFS, Fisher Viterbi 5 DBI 35 15 20 ANOVA 110 SBS 18 40 5 3 18 13 10 12 32 5 3 22 35 46 11 11 parti- number of selection / cipants features reduction g g LDA LDA HMM k-NN, LDA SVM MLP SVM k-NN, LDA, MLP k-NN, LDA, MLP MLP MLP LDA RT k-NN, SVM, RT, BN SVM ANN 5 valence levels AANN SVM SVM, ANFIS SVM, MLP LDA, DC classifiers / y g g 2 emotions 8 emotions 2 frustrations 6 emotions 6 emotions valence / arousal 3 emotions 6 emotions 4 emotions 4 emotions 4 emotions 3 stress levels 3 anxiety levels 3 emotions 2 stress levels 5 arousal levels 26 / 57% 3 emotions 3 affect states 4 affect states 2 fun levels 4 emotions target 71% 83% 79% 70% 70 / 95% 86% 81% 64% 69% 42% 64 – 97% 78% 84% 92% 80% 75% 97% 70% 86% 90% 31 / 62% classification result Signals: C: cardiovascular activity; E: electrodermal activity; R: respiration; M: electromyogram; B: electroencephalogram; S: skin temperature; P: pupil diameter.

With unsupervised pattern recognition, the distance / similarity measure used and the algorithm applied to generate the clusters are key elements. , the training set). Statistical pattern recognition uses input features, a discriminant function (or network function for ANN) to recognize the features, and an error criterion in its classification process. In the field of ASP, several studies have been conducted, using a broad range of signals, features, and classifiers; see Table 2 for an overview.

Samples of the electromyography (EMG) in µV of the frontalis, the corrugator supercilii, and the zygomaticus major as well as of the electrodermal activity (EDA) in µV , denoted by the skin conductance level (SCL). All these signals were recorded in parallel, with the same person. A TMS International Porti5-16/ASD system was used for the biosignal recordings, which was connected to a PC with TMS Portilab software1 . Three facial EMGs were recorded: the right corrugator supercilii, the left zygomaticus major, and the left frontalis muscle.

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