Thesis - Instituto de TelecomunicaÃ§Ãµes

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154 APPENDIX B. TESTS...# [moves] 1133884491168# 27Final data.# [total moves] 1133884491171# 126B.3 Association TestFigure B.4: Association test example.Description. The association test requires that the subjects memorize a set of associations.These associations are presented in an initial page where the subject needs to usethe mouse to uncover the associations between abstract objects. A second page shows oneobject and the user has to indicate which is the correct associated object.Goals.The test explores the associative memory capabilities of the user.
B.3. ASSOCIATION TEST 155Guide. Initially a list with associations of pairs of symbols will be shown. Memorizethem.For each problem a symbol is on the top line.Select the corresponding symbol from the list.Two correct answers for each association are needed to complete the test. The elements arehidden so that the system can monitor the mouse movements.Game Generation. A random set of associations between 5 pairs of objects is established.For each question a random object is presented as well as a random creation of thepossible pairs. The progress of the questions is prepared in order to guarantee that everyobject pair is presented a defined number of times.Level.The number of occasions that the question is asked to the user is the test level.Score.A score =correct itemstotal items(B.1)Recorded Data Format.Initial data.# [game] 1133884193288# 3 2 6 6 4 8 2 5 3 1Progress data.# [uncover 1] 1133884194943# 0# [uncover 2] 1133884195886# 6# [uncover 1] 1133884196834# 12# [uncover 2] 1133884198110# 1...# [moves] 1133884225999
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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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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 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: B.2. MEMORY TEST 153Level. In this
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 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.
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Thesis - Instituto de TelecomunicaÃ§Ãµes

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