Thesis - Instituto de TelecomunicaÃ§Ãµes

More documents

Recommendations

Info

34 CHAPTER 2. STATE OF THE ARTTable 2.2: Comparison between various behavioral biometric techniques.Technique EER Pros Consvoice [193] ∼ 10% easy to collect sensitive to noise andvoice alterationskeystroke [164] ∼ 4% non-intrusive method keystrokes can be replayedgait [78] ∼ 5% uses small device in the low performancebodysignature [253] ∼ 2% difficult to reproduce requires additionalhardwarepointer [83] ∼ 10% low intrusion needs long time interactioneye [128] ∼ 5% hardware commonly low performanceusedheart [219] ∼ 5% physiologic mechanism difficult to acquirebrain [180] ∼ 10% complex source non viable for implementation
Chapter 3Information Sources - HCI andPhysiological SignalsCreating a database with human-computer interaction and physiological signals was oneof the tasks performed in the context of the present research. To study new behavioralbiometric traits, searching for patterns that could be associated with a subject’s identity,we needed a set of behavioral sources.The efforts to undergo a data acquisition task were planned in order to create experimentalscenarios where the collected signals could be used in other research problems.Specifically, we were interested in acquiring data that could be used with the two-foldpurpose of human identification and recognition of cognitive/affective states. This dataacquisition project was coined HiMotion.The focus on human-computer interaction directed the development of a HCI recordingsystem, integrated with the cognitive tests. The physiological signals needed a preparationplan for all the procedures related to the sensors placement and signal quality verification.This research was conduced by Pattern Recognition and Communication Theory Group(TCRP) of Instituto de Telecomunicações, with the collaboration of Escola Superior deTecnologia (EST) and INSTICC.In this chapter we describe the implemented experimental setup, procedures and thestructure of the acquired data. Firstly, we detail the characteristics of the collected signals,in sections 3.2 and 3.3. In section 3.4 we describe the materials and methods used for the35
Page 1:
UNIVERSIDADE TÉCNICA DE LISBOAINST
Page 6 and 7:
iior gave some support to the devel
Page 9: ResumoO comportamento humano tem si
Page 12 and 13: viii2.3.2 Voice . . . . . . . . . .
Page 14 and 15: x6.2.2 Feature Analysis . . . . . .
Page 16 and 17: xii4.2 The x-y representation of th
Page 18 and 19: xiv
Page 20 and 21: xvi
Page 22 and 23: xviiiFCT Fundação para a Ciência
Page 25 and 26: Chapter 1Introduction1.1 The Proble
Page 27 and 28: 1.1. THE PROBLEM 3Figure 1.2: ECG s
Page 29 and 30: 1.2. MOTIVATION 5authentication sit
Page 31 and 32: 1.3. CONTRIBUTIONS 7resource in the
Page 33 and 34: 1.4. THESIS STRUCTURE 9The present
Page 35 and 36: Chapter 2State of the ArtIn this ch
Page 37 and 38: 2.1. BIOMETRICS CONCEPTS 13to class
Page 39 and 40: 2.1. BIOMETRICS CONCEPTS 15by the s
Page 41 and 42: 2.2. BIOMETRICS TECHNOLOGIES 17Figu
Page 43 and 44: 2.3. BEHAVIORAL BIOMETRICS 19Septem
Page 45 and 46: 2.3. BEHAVIORAL BIOMETRICS 21and co
Page 47 and 48: 2.3. BEHAVIORAL BIOMETRICS 232. ove
Page 49 and 50: 2.3. BEHAVIORAL BIOMETRICS 25Figure
Page 51 and 52: 2.3. BEHAVIORAL BIOMETRICS 27situat
Page 53 and 54: 2.3. BEHAVIORAL BIOMETRICS 29of sig
Page 55 and 56: 2.4. MULTIMODAL BIOMETRICS 312.4 Mu
Page 57: 2.6. DISCUSSION AND CONCLUSION 33al
Page 61 and 62: 3.2. HUMAN COMPUTER INTERACTION 37t
Page 63 and 64: 3.2. HUMAN COMPUTER INTERACTION 39I
Page 65 and 66: 3.2. HUMAN COMPUTER INTERACTION 41F
Page 67 and 68: 3.3. PHYSIOLOGICAL SIGNALS 43Histor
Page 69 and 70: 3.3. PHYSIOLOGICAL SIGNALS 45Figure
Page 71 and 72: 3.3. PHYSIOLOGICAL SIGNALS 47Term D
Page 73 and 74: 3.3. PHYSIOLOGICAL SIGNALS 49Figure
Page 75 and 76: 3.4. MATERIALS AND METHODS 51Figure
Page 77 and 78: 3.4. MATERIALS AND METHODS 53had th
Page 83 and 84: 3.6. CONCLUSION 59set of computatio
Page 85 and 86: Chapter 4Signal Processing andFeatu
Page 87 and 88: 4.1. HUMAN-COMPUTER INTERACTION 63I
Page 89 and 90: 4.1. HUMAN-COMPUTER INTERACTION 65T
Page 91 and 92: 4.1. HUMAN-COMPUTER INTERACTION 674
Page 93 and 94: 4.2. ELECTRODERMAL ACTIVITY 69To ex
Page 95 and 96: 4.2. ELECTRODERMAL ACTIVITY 71(eq.
Page 97 and 98: 4.2. ELECTRODERMAL ACTIVITY 73model
Page 99 and 100: 4.2. ELECTRODERMAL ACTIVITY 75the p
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
Page 123 and 124:
5.2. USER TUNED FEATURE SELECTION 9
Page 125 and 126:
5.3. SEQUENTIAL CLASSIFICATION 101p
Page 127 and 128:
5.3. SEQUENTIAL CLASSIFICATION 103s
Page 129 and 130:
5.3. SEQUENTIAL CLASSIFICATION 105n
Page 131 and 132:
5.4. UNCERTAINTY BASED CLASSIFICATI
Page 133 and 134:
Page 135 and 136:
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
Page 143 and 144:
6.1. POINTER DYNAMICS BIOMETRICS 11
Page 145 and 146:
6.2. SYMPATHETIC DYNAMICS BIOMETRIC
Page 147 and 148:
Page 149 and 150:
Page 151 and 152:
Page 153 and 154:
Page 155 and 156:
6.3. HEART DYNAMICS BIOMETRICS 1316
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 189 and 190:
Page 191 and 192:
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
Page 205 and 206:
BIBLIOGRAPHY 181[124] R. M. Kaplan
Page 207 and 208:
BIBLIOGRAPHY 183[145] C. L. Lim, E.
Page 209 and 210:
BIBLIOGRAPHY 185[169] NBSP. Interna
Page 211 and 212:
BIBLIOGRAPHY 187[191] T. Pixley. Do
Page 213 and 214:
BIBLIOGRAPHY 189[214] T. Shen and W
Page 215 and 216:
BIBLIOGRAPHY 191[236] M. Trauring.
show all

Thesis - Instituto de TelecomunicaÃ§Ãµes

Create successful ePaper yourself

Delete template?

Save as template?