Thesis - Instituto de TelecomunicaÃ§Ãµes

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126 CHAPTER 6. APPLICATIONS AND RESULTSFigure 6.8: Confusion matrix for an 1 sample EDA classifier.Uncertainty Based Reject OptionThe uncertainty based reject option (see section 5.4.2) was tested with the EDA data tounderstand the possible use of the EDA signal as a stand-alone mode, even if a relevantpercentage of the samples would need to be rejected.The identification error probability - probability of rejection trade-off is depicted in figure6.10 for the standard rejection option classifier (solid line) and the proposed uncertaintybased reject option classifier (dashed line). The example is from a sequential classifier with5 sequential samples (the training vector had 5 sequential samples per user). The bootstrapestimates were computed from 100 bootstrap samples.We see that the uncertainty based rejection classifier presents lower error probability forthe same rejection level. If we select a fixed error probability, the uncertainty based rejectoption also has lower rejection levels when compared to the standard reject option.
6.2. SYMPATHETIC DYNAMICS BIOMETRICS 127Figure 6.9: .Confusion matrix for a 10 sample EDA sequential classifier.Figure 6.10: Error probability versus rejection probability. The solid line refers to thenormal reject option classifier and the dashed line refers to the proposed uncertainty basedreject option classifier.
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UNIVERSIDADE TÉCNICA DE LISBOAINST
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iior gave some support to the devel
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ResumoO comportamento humano tem si
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viii2.3.2 Voice . . . . . . . . . .
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x6.2.2 Feature Analysis . . . . . .
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xii4.2 The x-y representation of th
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xiv
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xvi
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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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Page 101 and 102: 4.2. ELECTRODERMAL ACTIVITY 77t 3 =
Page 103 and 104: 4.2. ELECTRODERMAL ACTIVITY 79The d
Page 105 and 106: 4.2. ELECTRODERMAL ACTIVITY 81the e
Page 107 and 108: 4.2. ELECTRODERMAL ACTIVITY 831.00.
Page 109 and 110: 4.3. ELECTROCARDIOGRAM 8511.111.010
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
Page 121 and 122: 5.2. USER TUNED FEATURE SELECTION 9
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Page 137 and 138: 5.5. CONCLUSIONS 113of behavioral d
Page 139 and 140: Chapter 6Applications and ResultsTh
Page 141 and 142: 6.1. POINTER DYNAMICS BIOMETRICS 11
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Page 157 and 158: 6.3. HEART DYNAMICS BIOMETRICS 133F
Page 159 and 160: 6.4. CONCLUSION 135time(s) EDA EER
Page 161 and 162: Chapter 7ConclusionsIn this chapter
Page 163 and 164: 7.2. APPLICATION SCENARIOS 139adequ
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
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BIBLIOGRAPHY 177[84] H. Gamboa, A.
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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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