Thesis - Instituto de TelecomunicaÃ§Ãµes

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130 CHAPTER 6. APPLICATIONS AND RESULTSFigure 6.12: Classification fusion versus uncertainty reject option based fusion. The solidline presents the EER results of the regular fusion rule (± standard deviation indicated bythe error bars). The dashed line represents the uncertainty reject option based fusion rule.The dotted line is the base EER of the synthetic data classifier.Figure 6.13: Fusion results for different bootstrap sample size. The dashed line presentsthe classification results of the uncertainty reject option based fusion rule (the error barspresent ± error standard deviation). The solid line is the synthetic classifier EER.
6.3. HEART DYNAMICS BIOMETRICS 1316.3 Heart Dynamics BiometricsOur approach to the classification of the Electrocardiography (ECG) signal is similar to theone followed on the pointer dynamic biometrics, described in the previous section.6.3.1 Data PreparationWe used ECG data from 27 users, collected while performing the concentration test (the testis described in annex B). For each result we perform 50 runs to obtain mean and standarddeviation values. As described in section 4.3, a sample corresponds to the averaging of 10consecutive heart beats. The entire data set was sampled to create equal sized trainingand testing sets. Each sample corresponds to a feature vector representing a mean waveextracted from 10 beats. The sequential classifier system is evaluated for different sequencesizes. We start with a sequence of 1 to 9 samples. The mean wave examples of 12 users aredepicted in figure 6.14.Figure 6.14: Mean ECG wave for 12 users. The dashed lines represent the mean wave ±its standard deviation.6.3.2 Feature SelectionThe features are selected via the wrapper method of sequential forward search optimizingthe EER for each user. Figure 6.15 presents the typical length of the features sets selectedfor the users, showing that the best results need a small set of features for each user.
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UNIVERSIDADE TÉCNICA DE LISBOAINST
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viii2.3.2 Voice . . . . . . . . . .
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x6.2.2 Feature Analysis . . . . . .
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xviiiFCT Fundação para a Ciência
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Chapter 1Introduction1.1 The Proble
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1.1. THE PROBLEM 3Figure 1.2: ECG s
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1.2. MOTIVATION 5authentication sit
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1.3. CONTRIBUTIONS 7resource in the
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1.4. THESIS STRUCTURE 9The present
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Chapter 2State of the ArtIn this ch
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2.1. BIOMETRICS CONCEPTS 13to class
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2.1. BIOMETRICS CONCEPTS 15by the s
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2.2. BIOMETRICS TECHNOLOGIES 17Figu
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2.3. BEHAVIORAL BIOMETRICS 19Septem
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2.3. BEHAVIORAL BIOMETRICS 21and co
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2.3. BEHAVIORAL BIOMETRICS 232. ove
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2.3. BEHAVIORAL BIOMETRICS 25Figure
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2.3. BEHAVIORAL BIOMETRICS 27situat
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2.3. BEHAVIORAL BIOMETRICS 29of sig
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2.4. MULTIMODAL BIOMETRICS 312.4 Mu
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2.6. DISCUSSION AND CONCLUSION 33al
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Chapter 3Information Sources - HCI
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3.2. HUMAN COMPUTER INTERACTION 37t
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3.2. HUMAN COMPUTER INTERACTION 39I
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3.2. HUMAN COMPUTER INTERACTION 41F
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3.3. PHYSIOLOGICAL SIGNALS 43Histor
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3.3. PHYSIOLOGICAL SIGNALS 45Figure
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3.3. PHYSIOLOGICAL SIGNALS 47Term D
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3.3. PHYSIOLOGICAL SIGNALS 49Figure
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3.4. MATERIALS AND METHODS 51Figure
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3.4. MATERIALS AND METHODS 53had th
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3.6. CONCLUSION 59set of computatio
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Chapter 4Signal Processing andFeatu
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4.1. HUMAN-COMPUTER INTERACTION 63I
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4.1. HUMAN-COMPUTER INTERACTION 65T
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4.1. HUMAN-COMPUTER INTERACTION 674
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4.2. ELECTRODERMAL ACTIVITY 69To ex
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4.2. ELECTRODERMAL ACTIVITY 71(eq.
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4.2. ELECTRODERMAL ACTIVITY 73model
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4.2. ELECTRODERMAL ACTIVITY 75the p
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4.2. ELECTRODERMAL ACTIVITY 77t 3 =
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Page 111 and 112: 4.3. ELECTROCARDIOGRAM 87to the car
Page 113 and 114: 4.3. ELECTROCARDIOGRAM 89analyzing
Page 115 and 116: 4.4. CONCLUSION 918. a T - The ampl
Page 117 and 118: Chapter 5Feature Selection andClass
Page 119 and 120: 5.1. STATISTICAL MODELING 95Weibull
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Page 137 and 138: 5.5. CONCLUSIONS 113of behavioral d
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Page 159 and 160: 6.4. CONCLUSION 135time(s) EDA EER
Page 161 and 162: Chapter 7ConclusionsIn this chapter
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Page 165 and 166: 7.3. FUTURE WORK 141the user clicks
Page 167 and 168: Appendix AToolsThe work underlying
Page 169 and 170: A.2. SCIENTIFIC COMPUTATION 145side
Page 171 and 172: Appendix BTestsThe set of tests dev
Page 173 and 174: B.1. INTELLIGENCE TEST 149Figure B.
Page 175 and 176: B.2. MEMORY TEST 151# 2 3 3# 2 3 3#
Page 177 and 178: B.2. MEMORY TEST 153Level. In this
Page 179 and 180: B.3. ASSOCIATION TEST 155Guide. Ini
Page 181 and 182: B.5. CONCENTRATION TEST 157Descript
Page 183 and 184: B.5. CONCENTRATION TEST 159Test Gen
Page 185 and 186: B.6. TEST’S SEQUENCE 161Orderpage
Page 187 and 188: B.7. RELATED DOCUMENTS 163Figure B.
Page 193 and 194: Bibliography[1] A. Acharya, M. Cutt
Page 195 and 196: BIBLIOGRAPHY 171[18] B. Bimbaum. US
Page 197 and 198: BIBLIOGRAPHY 173[42] H. D. Critchle
Page 199 and 200: BIBLIOGRAPHY 175[63] R. Fernandez a
Page 201 and 202: BIBLIOGRAPHY 177[84] H. Gamboa, A.
Page 203 and 204: BIBLIOGRAPHY 179[102] S. Hocquet, J
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BIBLIOGRAPHY 181[124] R. M. Kaplan
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BIBLIOGRAPHY 183[145] C. L. Lim, E.
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BIBLIOGRAPHY 185[169] NBSP. Interna
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BIBLIOGRAPHY 187[191] T. Pixley. Do
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BIBLIOGRAPHY 189[214] T. Shen and W
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BIBLIOGRAPHY 191[236] M. Trauring.
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Thesis - Instituto de TelecomunicaÃ§Ãµes

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