Thesis - Instituto de TelecomunicaÃ§Ãµes

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188 BIBLIOGRAPHY[202] A. Rosenberg and S. Parthasarathy. Speaker background models for connected digitpassword speaker verification. In IEEE International Conference on Acoustics, Speech,and Signal Processing (ICASSP ’96), volume 1, pages 81–84, 1996.[203] A. Ross, A. K. Jain, and J. Z. Qian. Information fusion in biometrics. In Proceedingsof the Third International Conference on Audio- and Video-Based Biometric PersonAuthentication (AVBPA ’01), pages 354–359, London, UK, 2001. Springer-Verlag.[204] A. A. Ross, K. Nandakumar, and A. K. Jain. Handbook of Multibiometrics. Springer,May 2006.[205] T. Ruggles. Comparison of biometric techniques. Technical report, California WelfareFraud Prevention System, 2002.[206] S. Russel and P. Norvig. Artificial Intelligence: a modern approach. Prentice Hall,1995.[207] D. M. Russell, N. A. Streitz, and T. Winograd. Building disappearing computers.Commun. ACM, 48(3):42–48, 2005.[208] H. Said, G. Peake, T. Tan, and K. Baker. Writer identification from non-uniformlyskewed handwriting images. In British Machine Vision Conference, 1998.[209] D. D. Salvucci. Mapping Eye Movements to Cognitive Processes. PhD thesis, Departmentof Computer Science Carnegie Mellon University, May 1999.[210] R. W. Scheifler. The X-Window System Protocol. M.I.T. Laboratory for ComputerScience, 1988.[211] R. Schleicher. Simple EDA/EMG: Matlab tools to analyze EDA/EMG activity. Technicalreport, University of Cologne, 2005.[212] G. Shafer. Mathematical Theory of Evidence. Princeton Univ Pr, Mar. 1976.[213] C. E. Shannon. A mathematical theory of communication. Bell Systems TechnicalJournal, 27(3):379–423, 1948. Continued 27(4):623-656.
BIBLIOGRAPHY 189[214] T. Shen and W. Tompkins. Biometric statistical study of one-lead ECG features andbody mass index (BMI). In Proceedings of 27th Annual International Conference ofthe IEEE Engineering in Medicine and Biology Society, pages 1162–1165, 2005.[215] T. Shen, W. Tompkins, and Y. Hu. One-lead ECG for identity verification. InProceedings of the Second Joint EMBS/BMES Conference, pages 62–63, 2002.[216] S. J. Shepherd. Continuous authentication by analysis of keyboard typing characteristics.In European Convention on Security and Detection (ECOS 95), pages 111–114,1995.[217] W. Siedlencki and J. Sklansky. On automatic feature selection. In C. H. Chen, L. F.Pau, and P. S. P. Wang, editors, Handbook of Pattern Recognition and ComputerVision. World Scientific, 1993.[218] H. Silva. Feature selection in pattern recognition systems. Master’s thesis, UniversidadeTécnica de Lisboa, Instituto Superior Técnico, 2007.[219] H. Silva, H. Gamboa, and A. Fred. Applicability of lead V 2 ECG measurements inbiometrics. In Med-e-Tel Proceedings, 2007.[220] H. Silva, H. Gamboa, and A. Fred. One lead ECG based human identification withfeature subspace ensembles. In 5th International Conference on Machine Learningand Data Mining, 2007.[221] T. Sim, S. Zhang, R. Janakiraman, and S. Kumar. Continuous verification usingmultimodal biometrics. IEEE Transactions on Pattern Analysis and Machine Intelligence,29(4):687–700, 2007.[222] D. X. Song, D. Wagner, and X. Tian. Timing analysis of keystrokes and timing attackson SSH. In 10 th USENIX Security Symposium, 2001.[223] R. Spillane. Keyboard apparatus for personal identification. IBM Technical DisclosureBulletin, 17(3346), 1975.[224] O. Spreen and E. Strauss. A Compendium of Neuropsychological Tests: Administration,Norms, and Commentary. Oxford University Press, USA, second edition,1998.
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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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4.2. ELECTRODERMAL ACTIVITY 75the p
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4.2. ELECTRODERMAL ACTIVITY 77t 3 =
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4.2. ELECTRODERMAL ACTIVITY 79The d
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4.2. ELECTRODERMAL ACTIVITY 81the e
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4.2. ELECTRODERMAL ACTIVITY 831.00.
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4.3. ELECTROCARDIOGRAM 8511.111.010
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4.3. ELECTROCARDIOGRAM 87to the car
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4.3. ELECTROCARDIOGRAM 89analyzing
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4.4. CONCLUSION 918. a T - The ampl
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Chapter 5Feature Selection andClass
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5.1. STATISTICAL MODELING 95Weibull
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5.2. USER TUNED FEATURE SELECTION 9
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5.2. USER TUNED FEATURE SELECTION 9
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5.3. SEQUENTIAL CLASSIFICATION 101p
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5.3. SEQUENTIAL CLASSIFICATION 103s
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5.3. SEQUENTIAL CLASSIFICATION 105n
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5.4. UNCERTAINTY BASED CLASSIFICATI
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5.5. CONCLUSIONS 113of behavioral d
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Chapter 6Applications and ResultsTh
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6.1. POINTER DYNAMICS BIOMETRICS 11
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6.1. POINTER DYNAMICS BIOMETRICS 11
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6.2. SYMPATHETIC DYNAMICS BIOMETRIC
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6.3. HEART DYNAMICS BIOMETRICS 1316
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6.3. HEART DYNAMICS BIOMETRICS 133F
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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
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: BIBLIOGRAPHY 187[191] T. Pixley. Do
Page 215 and 216: BIBLIOGRAPHY 191[236] M. Trauring.
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