



@book {2890,
	title = {Minimum error entropy classification},
	series = {Studies in Computational Intelligence},
	volume = {420},
	year = {2013},
	note = {Export Date: 12 December 2013Source: Scopus},
	month = {2013///},
	pages = {1 - 278},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84867489006\&partnerID=40\&md5=45e5679e51ca7e192b098b2320ec561a},
	author = {Marques De S{\'a}, J.P. and Silva, L.M.A. and Santos, J.M.F. and Alexandre, L.A.}
}
@article {2386,
	title = {A novel dry active electrode for EEG recording},
	journal = {IEEE Transactions on Biomedical EngineeringIEEE Trans. Biomed. Eng.},
	volume = {54},
	year = {2007},
	note = {Cited By (since 1996): 24Export Date: 21 November 2012Source: ScopusArt. No.: 23CODEN: IEBEAdoi: 10.1109/TBME.2006.884649PubMed ID: 17260869Language of Original Document: EnglishCorrespondence Address: Fonseca, C.; INEB Instituto de Engenharia Biom{\'e}dica, Laborat{\'o}rio de Biomateriais, Universidade Do Porto, Rua do Campo Alegre, 823, 4150-180 Porto, Portugal; email: cfonseca@ibmc.up.ptChemicals/CAS: Biocompatible Materials; Titanium, 7440-32-6; titanium dioxide, 13463-67-7References: Portnoy, W., David, R., Akers, L., Insulated ECG electrodes (1974) Biomedical Electrode Technology, , H. A. Miller and D. C. Harrison, Eds. New York: Academic;Nishimura, S., Tomita, Y., Horiuchi, T., Clinical application of an active electrode using an operational amplifier (1992) IEEE Trans. Biomed. Eng, 39 (10), pp. 1090-1099. , Oct; 
Taheri, A., Knight, R., Smith, R., A dry electrode for EEG recording (1994) Electroencephalogr. Clin. Neurophysiol, 90, pp. 376-383; 
Searle, A., Kirkup, L., A direct comparison of wet, dry and insulating bioelectric recording electrodes (2000) Physiol. Meas, 22, pp. 71-83; 
Fonseca, C., Vaz, F., Barbosa, M.A., Electrochemical behaviour of titanium coated stainless steel by R.F. sputtering in synthetic sweat solutions for electrode applications (2004) Corrosion Sci, 46 (12), pp. 3005-3018; 
Matsuo, T., IInuma, K., Esashi, M., Barium titanate ceramics capacitive type EEG elecrode (1973) IEEE Trans. Biomed. Eng, BME-20, pp. 299-300; 
Perez, J., Vilarinho, P., Kholkin, A., High-quality Pbzr0.52Ti0. 48O3 films prepared by modified sol-gel route at low temperature (2004) Thin Solid Films, 449 (1-2), pp. 20-24; 
Rosell, J., Colominas, J., Riu, P., Pallas-Areny, R., Webster, J., Skin impedance from 1 Hz to 1 MHz (1988) IEEE Trans. Biomed. Eng, 35 (8), pp. 649-651. , Aug; 
Ferree, T., Luu, P., Russell, G., Tucker, D., Scalp electrode impedance, infection risk and EEG data quality (2001) Clin. Neurophysiol, 112 (3), pp. 536-544
},
	month = {2007///},
	pages = {162 - 165},
	abstract = {The design and testing of a "dry" active electrode for electroencephalographic recording is described. A comparative study between the EEG signals recorded in human volunteers simultaneously with the classical Ag-AgCl and "dry" active electrodes was carried out and the reported preliminary results are consistent with a better performance of these devices over the conventional Ag-AgCl electrodes. {\textcopyright} 2007 IEEE.},
	keywords = {article, Biocompatible Materials, Bioelectric phenomena, Bioelectric signal recording, bioenergy, biomedical electrodes, Biomedical engineering, Data recording, Dry electrodes, Electric Impedance, Electrochemical electrodes, electrode, Electrodes, electroencephalogram, Electroencephalographic recording, electroencephalography, Equipment Design, Equipment Failure Analysis, Feasibility Studies, Pilot Projects, signal transduction, Silver compounds, Titanium},
	isbn = {00189294 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-33846389173\&partnerID=40\&md5=0273ef7699807f6e20f95dd6bacb3c9b},
	author = {Fonseca, C. and Silva Cunha, J.P. and Martins, R.E. and Ferreira, V.M. and Marques De S{\'a}, J.P. and Barbosa, M.A. and Martins Da Silva, A.}
}
@conference {2388,
	title = {Characterization of fetal heart rate irregularity using approximate entropy and wavelet filtering},
	booktitle = {Computers in CardiologyComput Cardiol},
	series = {2006 Computers in Cardiology, CIC},
	volume = {33},
	year = {2006},
	note = {Conference code: 73228Cited By (since 1996): 3Export Date: 21 November 2012Source: ScopusArt. No.: 4512006CODEN: COCADLanguage of Original Document: EnglishCorrespondence Address: Marques De S{\'a}, J. P.; Faculdade de Engenharia, DEEC, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal; email: jmsa@fe.up.ptReferences: Pincus, S., Approximate entropy as a measure of system complexity (1991) Proc. Natl. Acad. Sci. U.S.A, 88, pp. 2297-2301;Pincus, S., Randomness and degrees of irregularity (1996) Proc. Natl. Acad. Sci. U.S.A, 93, pp. 2083-2088; 
Pincus, S.M., Viscarello, R.R., Approximate entropy: A regularity measure for fetal heart rate (1992) Obstet. Gynecol, 2, pp. 249-255; 
Fleisher, L.A., Dipietro, J.A., Johnson, T.R., Pincus, S., Complementary and non-coincident increases in heart rate variability and irregularity during fetal development (1997) Clin. Sci, 4, pp. 345-349; 
van Leeuwen, P., Lange, S., Betterman, H., Gronemeyer, D., Hatzmann, W., Fetal heart rate variability and complexity in the course of pregnancy (1999) Early Human Develop, 54, pp. 259-269; 
Pincus, S., Assessing Serial Irregularity and its Implications for Health (2001) Ann N Y Acad Sci, 954, pp. 245-267; 
Cysarz, D., Betterman, H., van Leeuwen, P., Entropies of short binary sequences in heart period dynamics (2000) Am J Physiol Heart Circ Physiol, 6, pp. 2163-2172; 
Signorini, M.G., Magenes, G., Cerutti, S., Arduini, D., Linear and Nonlinear Parameters for the Analysis of Fetal Heart Rate Signal from Cardiotocographic Recordings (2003) IEEE Tr. BME, 50, pp. 365-373; 
Ayres-de-Campos, D., Bernardes, J., Garrido, A., Marques-de-S{\'a}, J., Pereira-Leite, L., SisPorto 2.0 - A Program for Automated Analysis of Cardiotocograms (2000) J Matern Fetal Med, 9, pp. 311-318; 
S{\'a} Couto, P.M., van Meurs, W.L., Bernardes, J.F., Marques de, S.J., Goodwin, J.A., Combined Model-Driven and Rule-Based Approach for Educational Simulation of Fetal Heart Rate (2002) Proc. 16th Biennial Int. Conf. Europ. Assoc. for Speech, Signal and Image Processing, pp. 400-402. , EURASIP, Brno, Czech Rep, pp; 
Marques de S{\'a}, J.P., Characterization of fetal heart rate using approximate entropy (2005) Proc. IEEE Comp. in Cardiology 2005, 32, pp. 671-673
},
	month = {2006///},
	pages = {933 - 936},
	address = {Valencia},
	abstract = {Approximate Entropy (ApEn) has been used by several researchers as a means to characterize the irregularity of fetal heart rate (FHR), a major contributor to fetal risk assessment. The present work starts by analyzing the influence of accelerative and decelerative (AD) components of the FHR signal in the computation of ApEn. Having shown that the AD components may completely distort the ApEn evaluation we proceed to present two methods of eliminating the influence of the AD components: wavelet filtering; AD detection using specific algorithms based on well-established physiological criteria. We obtained good results with the first method when applied to simulated signals; however it proved unreliable in the practical application of discriminating normal from pathological fetal FHR. With the second method we were able to achieve this discrimination with high statistical significance.},
	keywords = {Approximate entropy, Cardiology, Fetal heart rate, Neonatal monitoring, Occupational risks, Physiological models, risk assessment, Risk management, Safety engineering, Simulated signals, Statistical significance, Wavelet filtering},
	isbn = {02766574 (ISSN); 1424425328 (ISBN); 9781424425327 (ISBN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-50149100681\&partnerID=40\&md5=51e2dd8109d66e30498d7c2f8689c820},
	author = {Magalh{\~a}es, F. and Marques De S{\'a}, J.P. and Bernardes, J. and Ayres-de-Campos, D.}
}
@book {2395,
	title = {Error entropy minimization for LSTM training},
	series = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci.},
	volume = {4131 LNCS - I},
	year = {2006},
	note = {Conference code: 68317Cited By (since 1996): 3Export Date: 21 November 2012Source: ScopusLanguage of Original Document: EnglishCorrespondence Address: Alexandre, L.A.; Department of Informatics, IT-Networks and Multimedia Group, University of Beira Interior, Covilh{\~a}, Portugal; email: lfbaa@di.ubi.ptReferences: Hochreiter, S., Schmidhuber, J., Long short-term memory (1997) Neural Computation, 9 (8), pp. 1735-1780;Gers, F., Schmidhuber, J., Cummins, F., Learning to forget: Continual prediction with LSTM (2000) Neural Computation, 12 (10), pp. 2451-2471; 
Gers, F., Schmidhuber, J., Recurrent nets that time and count (2000) Proc. IJCNN{\textquoteright}2000, Int. Joint Conf. on Neural Networks, , Como, Italy; 
P{\'e}rez-Ortiz, J., Gers, F., Eck, D., Schmidhuber, J., Kalman filters improve LSTM network performance in problems unsolvable by traditional recurrent nets (2003) Neural Networks, 16 (2), pp. 241-250; 
Haykin, S., (1999) Neural Networks: A Comprehensive Foundation, 2nd Edition, , Prentice Hall; 
Erdogmus, D., Principe, J., An error-entropy minimization algorithm for supervised training of nonlinear adaptive systems (2002) IEEE Trans. Signal Processing, 50 (7), pp. 1780-1786; 
Santos, J., Alexandre, L., Sereno, F., Marques De S{\'a}, J., Optimization of the error entropy minimization algorithm for neural network classification (2004) ANNIE 2004, Intelligent Engineering Systems Through Artificial Neural Networks, 14, pp. 81-86. , St.Louis, USA, ASME Press Series; 
Santos, J., Alexandre, L., Marques De S{\'a}, J., The error entropy minimization algorithm for neural network classification (2004) Proceedings of the 5th International Conference on Recent Advances in Soft Computing, pp. 92-97. , Lofti, A., ed.: Nottingham, United Kingdom; 
Silva, L., Marques De S{\'a}, J., Alexandre, L., Neural network classification using Shannon{\textquoteright}s entropy (2005) 13th European Symposium on Artificial Neural Networks - ESANN 2005, pp. 217-222. , Bruges, Belgium
},
	month = {2006///},
	pages = {244 - 253},
	address = {Athens},
	abstract = {In this paper we present a new training algorithm for the Long Short-Term Memory (LSTM) recurrent neural network. This algorithm uses entropy instead of the usual mean squared error as the cost function for the weight update. More precisely we use the Error Entropy Minimization approach, were the entropy of the error is minimized after each symbol is present to the network. Our experiments show that this approach enables the convergence of the LSTM more frequently than with the traditional learning algorithm. This in turn relaxes the burden of parameter tuning since learning is achieved for a wider range of parameter values. The use of EEM also reduces, in some cases, the number of epochs needed for convergence. {\textcopyright} Springer-Verlag Berlin Heidelberg 2006.},
	keywords = {Algorithms, Convergence of numerical methods, Cost function, entropy, Error Entropy Minimization, Errors, Long Short-Term Memory (LSTM), Neural networks, Optimization},
	isbn = {03029743 (ISSN); 3540386254 (ISBN); 9783540386254 (ISBN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-33749837658\&partnerID=40\&md5=5f40159a3f1faf4760405dd581e79bf7},
	author = {Alexandre, L.A. and Marques De S{\'a}, J.P.}
}
@conference {2435,
	title = {Characterization of fetal heart rate using approximate entropy},
	booktitle = {Computers in CardiologyComput Cardiol},
	series = {Computers in Cardiology, 2005},
	volume = {32},
	year = {2005},
	note = {Conference code: 69149Cited By (since 1996): 2Export Date: 21 November 2012Source: ScopusArt. No.: 1588190CODEN: COCADdoi: 10.1109/CIC.2005.1588190Language of Original Document: EnglishCorrespondence Address: Marques de S{\'a}, J.P.; Faculdade de Engenharia, DEEC, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal; email: jmsa@fe.up.ptReferences: Felgueiras, C., Marques de, S.J., Bernardes, J., Gama, S., Classification of Foetal Heart Rate Sequences Based on Fractal Features (1998) Medical \& Biological Engineering \& Computing, 2, pp. 197-201;Pincus, S., Approximate entropy as a measure of system complexity (1991) Proc. Natl. Acad. Sci. U.S.A, 88, pp. 2297-2301; 
Pincus, S.M., Viscarello, R.R., Approximate entropy: A regularity measure for fetal heart rate (1992) Obstet. Gynecol, 2, pp. 249-255; 
Pincus, S., Approximate Entropy (ApEn) as a Complexity Measure (1995) Chaos, 5, pp. 110-117; 
Pincus, S., Randomness and degrees of irregularity (1996) Proc. Natl. Acad. Sci. U.S.A, 93, pp. 2083-2088; 
Pincus, S., Kalman, R.E., Not all (possibly) "random" sequences are created equal (1997) Proc. Natl. Acad. Sci. U.S.A, 94, pp. 3513-3518; 
Fleisher, L.A., Dipietro, J.A., Johnson, T.R., Pincus, S., Complementary and non-coincident increases in heart rate variability and irregularity during fetal development (1997) Clin. Sci, 4, pp. 345-349; 
van Leeuwen, P., Lange, S., Betterman, H., Gronemeyer, D., Hatzmann, W., Fetal heart rate variability and complexity in the course of pregnancy (1999) Early Human Develop, 54, pp. 259-269; 
Pincus, S., Assessing Serial Irregularity and its Implications for Health (2001) Ann N Y Acad Sci, 954, pp. 245-267; 
Cysarz, D., Betterman, H., van Leeuwen, P., Entropies of short binary sequences in heart period dynamics (2000) Am J Physiol Heart Circ Physiol, 6, pp. 2163-2172; 
Ayres-de-Campos, D., Bernardes, J., Garrido, A., Marques-de-S{\'a}, J., Pereira-Leite, L., SisPorto 2.0 - A Program for Automated Analysis of Cardiotocograms (2000) J Matern Fetal Med, 9, pp. 311-318
},
	month = {2005///},
	pages = {671 - 673},
	address = {Lyon},
	abstract = {Approximate entropy (ApEn) is an interesting measure for assessing the irregularity of time series and in particular for characterizing heart rate variability. In the present paper we apply ApEn to the characterization of three patterns of fetal heart rate (FHR): calm sleep; calm vigilance; pathological flat-sinusoidal condition. We conclude that ApEn can perfectly discriminate the pathological FS pattern from the normal A and C patterns and is far better for FHR pattern discrimination than classic time-domain variability indexes used in clinical practice. {\textcopyright} 2005 IEEE.},
	keywords = {Approximate entropy (ApEn), Cardiology, Fetal heart rate, Fetal monitoring, Heart rate variability, Pathology, Sleep research, Time domain analysis},
	isbn = {02766574 (ISSN); 0780393376 (ISBN); 9780780393370 (ISBN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-33847143708\&partnerID=40\&md5=9c0b28217d5f8a40e2e1741bba8c4561},
	author = {Marques De S{\'a}, J.P.}
}
@article {2534,
	title = {Mathematical model for educational simulation of the oxygen delivery to the fetus},
	journal = {Control Engineering PracticeControl Eng. Pract.},
	volume = {10},
	year = {2002},
	note = {Cited By (since 1996): 3Export Date: 21 November 2012Source: ScopusCODEN: COEPEdoi: 10.1016/S0967-0661(01)00133-2Language of Original Document: EnglishCorrespondence Address: Marques de S{\'a}, J.P.; Instituto de Engenharia Biomedica, Faculdade de Engenharia, Universidade do Porto, Rua Roberto Frias, Porto 4200-465, Portugal; email: jmsa@fe.up.ptReferences: Beneken, J.E.W., Rideout, V.C., The use of multiple models in cardiovascular system studies: Transport and perturbation methods (1968) IEEE Transactions on Bio-Medical Engineering, 15 (4), pp. 281-289;Cunningham, G., (1997) Williams Obstretrics, , (20th ed.). London: Prentice-Hall; 
Delivoria-Papadopoulos, M., McGowan, J.E., Oxygen transport and delivery (1998) Fetal and Neonatal Physiology, pp. 1105-1117. , R. A. Polin and W. W. Fox (Eds.), (2nd ed.) London: W.B. Saunders Company; 
Euliano, T.Y., Caton, D., van Meurs, W.L., Good, M.L., Modeling obstetric cardiovascular physiology on a full-scale patient simulator (1997) Journal Clinical Monitoring, 13 (5), pp. 293-297; 
Fukui, Y., Smith, N.T., Interactions among ventilation, the circulation, and the uptake and distribution of halothane-use of a hybrid computer multiple model: I the basic model (1981) Anesthesiology, 54, pp. 107-118; 
Fukui, Y., Smith, N.T., Interactions among ventilation, the circulation, and the uptake and distribution of halothane-use of a hybrid computer multiple model: II spontaneous vs. controlled ventilation, and the effects of CO 2 (1981) Anesthesiology, 54, pp. 119-124; 
Gaba, D.M., De Anda, A., A comprehensive anesthesia simulation environment: Recreating the operating room for research and training (1988) Anesthesiology, 69, pp. 387-394; 
Good, M.L., Gravenstein, J.S., Anesthesia simulators and training devices (1989) International Anesthesiololy Clinics, 27 (3), pp. 161-168; 
Guyton, A.C., (1991) Medical Physiolology, , (8th ed.). London: W.B. Saunders Company; 
Henson, L., Lee, A., (1998) Simulators in Anesthesiology Education, , New York: Plenum; 
Huikeshoven, F.J., Hope, I.D., Power, G.G., Gilbert, R.D., Longo, L.D., Mathematical model of fetal circulation and oxygen delivery (1985) American Journal of Physiology, 249, pp. R192-R202; 
Itskovitz, J., LaGamma, E., Rudolph, A.M., The effect of reducing umbilical blood flow on fetal oxygenation (1983) American Journal of Obstetric and Gynecology, 145 (7), pp. 813-818; 
Polin, R.A., Fox, W.W., (1998) Fetal and Neonatal Physiology, , (2nd ed.). London: W.B. Saunders Company; 
Schwid, H.A., Flight simulator for general anesthesia training (1987) Computers and Biomedical Research, 20, pp. 64-75; 
Schwid, H.A., O{\textquoteright}Donnell, D., The anesthesia simulator- recorder: A device to train and evaluate anesthesiologists{\textquoteright} responses to critical incidents (1990) Anesthesiology, 72, pp. 191-197; 
Severinghaus, J.W., Simple, accurate equations for human blood O 2 dissociation computations (1979) Journal of Applied Physiology, 46 (3), pp. 599-602; 
Skillman, C.A., Plemessinger, M.A., Woods, J.R., Clark, K.E., The effect of graded reductions in uteroplacental blood flow on fetal lamb (1985) American Journal of Physiology, 249 (18), pp. H1098-H1105; 
Sukumar, N., Morin III, F.C., Response of the fetal circulation to stress (1998) Fetal and Neonatal Physiology, pp. 1014-1023. , (2nd ed.) London: WB Saunders Company; 
van Meurs, W.L., Good, M., Lampotang, S., Functional anatomy of full-scale patient simulators (1997) Journal of Clinical Monitoring, 13 (5), pp. 317-324; 
Zwart, A., Smith, N.T., Beneken, J.E.W., Multiple model approach to uptake and distribution of halothane: The use of an analog computer (1972) Computers and Biomedical Research, 5, pp. 228-238
},
	month = {2002///},
	pages = {59 - 66},
	abstract = {Critical situations in obstetrics and anesthesia of the pregnant woman are rare and associated with a high risk to the woman and fetus involved. Therefore, simulation is a valuable tool in teaching the diagnostic and therapeutic skills in this context. We derive a mathematical model for the oxygen supply to the fetus that was specifically designed for educational simulations. The model reflects the hemodynamics and the oxygen transport. Parameter values for human patients are derived from the literature data. We validate the response of the model, with parameters reflecting the fetal lamb, to various reductions of the uterine and umbilical blood flow. {\textcopyright} 2002 Elsevier Science Ltd. All rights reserved.},
	keywords = {Anesthesiology, Blood, Computer simulation, control, Diagnosis, education, Fetal monitoring, fetus, hemodynamics, mathematical model, Mathematical models, medical application, Obstetrics, oxygen, Oxygen supply, simulator, Therapeutic skills},
	isbn = {09670661 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0036141420\&partnerID=40\&md5=5b294e0689357e03c548b7ccf608b476},
	author = {S{\'a} Couto, P.M. and van Meurs, W.L. and Bernardes, J.F. and Marques De S{\'a}, J.P. and Goodwin, J.A.}
}
@article {2563,
	title = {Classification of breast tissue by electrical impedance spectroscopy},
	journal = {Medical and Biological Engineering and ComputingMed. Biol. Eng. Comput.},
	volume = {38},
	year = {2000},
	note = {Cited By (since 1996): 42Export Date: 21 November 2012Source: ScopusCODEN: MBECDPubMed ID: 10829386Language of Original Document: EnglishCorrespondence Address: Marques de Sa, J.P.; INEB, Facul. Engenharia Universidade Porto, Porto, Portugal; email: jmsa@fe.op.ptReferences: Brown, B.H., Barber, D.C., Morice, A.H., Leathard, A.D., Cardiac and respiratory related electrical impedance changes in the human thorax (1994) IEEE Trans. Biomed. Eng., BME-41, pp. 729-734;Campbell, A.M., Land, D.V., Dielectric properties of female breast tissue measured in vitro at 3.2 GHz (1992) Phys. Med. Biol., 37, pp. 193-210; 
Duda, R., Hart, P., (1973) Pattern Classification and Scene Analysis, , Wiley, New York; 
Foley, D.H., Considerations of sample and feature size (1972) IEEE Trans. Inform. Theory, IT-18, pp. 618-626; 
Foster, K.R., Schwan, H.P., Dielectric properties of tissues and biological materials: A critical review (1989) CRC Crit. Reviews Biomed. Eng., 17, pp. 25-104; 
Fukunaga, K., (1972) Introduction to Statistical Pattern Recognition, , Academic Press, New York and London; 
Gersing, E., Sch{\"a}fer, M., Osypka, M., The appearance of positive phase angles in impedance measurements on extended biological subjects (1995) Innov. Techn. Biol. Med., 16 (SPEC. ISSUE 2), pp. 72-76. , Proc. {\textquoteright}CAIT Workshop on Electrode-Skin Interface in EIT{\textquoteright}; 
Heinitz, J., Minet, O., Dielectric properties of female breast tumors (1995) Proc. {\textquoteright}9th Int. Conf. Electrical Bioimpedance{\textquoteright}, pp. 356-359. , University of Heidelberg Press; 
Henderson, R.P., Webster, J.G., An impedance camera for spatially specific measurements of the thorax (1978) IEEE Trans. Biomed. Eng., BME-27, pp. 250-254; 
Jossinet, J., Variability of impedivity in normal and pathological breast tissue (1996) Med. Biol. Eng. Comput., 34, pp. 346-350; 
Jossinet, J., The impedivity of freshly excised human breast tissue (1998) Physiol. Meas., 19, pp. 61-75; 
Jossinet, J., Lavandier, B., The discrimination of excised cancerous breast tissue samples using impedance spectroscopy (1998) Bioelectrochem. Bioenerg., 45, pp. 161-167; 
Kubicek, W.G., Patterson, R.P., Witsoe, D.A., Impedance cardiography as a noninvasive method of monitoring cardiac function and other parameters of the cardiovascular system (1970) Ann. N.Y. Acad. Sciences, 170, pp. 24-732; 
Morimoto, T., Kinouchi, Y., Iritani, T., Kimura, S., Konishi, Y., Mitsuyama, N., Komaki, K., Monden, Y., Measurement of the electrical bio-impedance of breast tumors (1990) Eur. Surg. Res., 22, pp. 86-92; 
Raudys, S., Pikelis, V., On dimensionality, sample size, classification error and complexity of classification algorithm in pattern recognition (1980) IEEE Trans. Patt. Anal. Mach. Intel., PAMI-2, pp. 242-252; 
Shapiro, S.S., Wilk, S.S., Chen, S.W., A comparative study of various tests for normality (1968) J. Am. Stat. Ass., 63, pp. 1343-1372; 
Swain, P.H., The decision tree classifier: Design and potential (1977) IEEE Trans. Geosci. Electronics, GE-15, pp. 142-147; 
Schwan, H.P., Alternating current spectroscopy of biological substances (1959) Proc. IRE, 47, pp. 1841-1855; 
Surowiec, A.J., Stuchly, S.S., Barr, J.R., Swarup, A., Dielectric properties of breast carcinoma and the surrounding tissues (1988) IEEE Trans. Biomed. Eng., BME-35, pp. 257-263; 
Tachibana, S., Aguilar, J.A., Birzis, L., Scanning the interior of living brain by impedography (1970) J. of App. Physiol., 28, pp. 534-539
},
	month = {2000///},
	pages = {26 - 30},
	publisher = {Peter Peregrinus Ltd},
	abstract = {Electrical impedance spectroscopy is a minimally invasive technique that has clear advantages for living tissue characterisation owing to its low cost and ease of use. The present paper describes how this technique can be applied to breast tissue classification and breast cancer detection. Statistical analysis is used to derive a set of rules based on features extracted from the graphical representation of electrical impedance spectra. These rules are used hierarchically to discriminate several classes of breast tissue. Results of statistical classification obtained from a data set of 106 cases representing six classes of excised breast tissue show an overall classification efficiency of ~92\% with carcinoma discrimination > 86\%.Electrical impedance spectroscopy is a minimally invasive technique that has clear advantages for living tissue characterization owing to its low cost and ease of use. The present paper describes how this technique can be applied to breast tissue classification and breast cancer detection. Statistical analysis is used to derive a set of rules based on features extracted from the graphical representation of electrical impedance spectra. These rules are used hierarchically to discriminate several classes of breast tissue. Results of statistical classification obtained from a data set of 106 cases representing six classes of excised breast tissue show an overall classification efficiency of approximately 92\% with carcinoma discrimination >86\%.
},
	keywords = {article, Breast, breast cancer, Breast Neoplasms, cancer classification, Data classification, Discriminant Analysis, Electric Impedance, Electrical impedance spectroscopy, Electrodiagnosis, Feature extraction, Female, human, Humans, impedance, Impedance spectroscopy, major clinical study, Medical imaging, Signal Processing, Computer-Assisted, Spectroscopy, Statistical analysis, Statistical methods, Tissue, Tissue characterisation},
	isbn = {01400118 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0033962139\&partnerID=40\&md5=1510d493688d338d985aad2a31d1caeb},
	author = {Estrela Da Silva, J. and Marques De S{\'a}, J.P. and Jossinet, J.}
}
@conference {2566,
	title = {ECG noise filtering using wavelets with soft-thresholding methods},
	booktitle = {Computers in CardiologyComput Cardiol},
	series = {The 26th Annual Meeting: Computers in Cardiology 1999},
	year = {1999},
	note = {Conference code: 56519Cited By (since 1996): 29Export Date: 21 November 2012Source: ScopusCODEN: COCADLanguage of Original Document: EnglishCorrespondence Address: Agante, P.M.; Inst Nacional de Engenharia, Biomedica, Oporto, PortugalReferences: Graps, A., An introduction to wavelets (1995) IEEE Computational Science and Engineering, 2 (2);Donoho, D.L., De-noising by soft-thresholding (1992) Symposium on Wavelet Theory, , Vanderbilt; 
Daubechies, I., The wavelet transform, time-frequency localization and signal analysis (1990) IEEE Transactions on Information Theory, 36 (5), pp. 961-1005; 
Chui, C.K., (1992) An Introduction to Wavelets, , Academic Press; 
Willems, J.L., CSE multilead atlas (1988) Common Standards for Quantitative Electrocardiography (European Concerted Action Project II.2.2), Div. Medical Informatics, , CSE Project Leader, Univ. Hosp. Gasthuisberg, Leuven; 
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},
	month = {1999///},
	pages = {535 - 538},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Hannover, Ger},
	abstract = {In this paper we analyze algorithms for filtering white gaussian noise and 50 Hz power line noise from ECG signals. We used several wavelets to study their effect and efficiency in the filtering process. To deal with these different kinds of noises we used two distinct soft-thresholding techniques: the Donoho{\textquoteright}s statistical threshold estimator and a method developed by us. This last method exploits one of the wavelet processing main features: time-frequency relation. The de-noising methods led to good filtering results: noise reduction with only minor change of the ECG waveforms as confirmed by the high correlation values between the processed signal and the original one. These good results are due to a wavelet advantage over classical filtering - time-frequency relation - enabling the possibility of filtering noise in the same frequency band of the ECG signal with minimal interference.},
	keywords = {Algorithms, Electrocardiography, Signal filtering and prediction, Signal interference, Wavelet denoising, White noise},
	isbn = {02766574 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0342854378\&partnerID=40\&md5=11e3b634e77d95bc3486d33a9f2a4b2d},
	author = {Agante Da Silva, P.M.G. and Marques De S{\'a}, J.P.}
}
