LEADER 05999nam 2200541 450 001 996466409403316 005 20231110230525.0 010 $a981-16-1722-8 035 $a(CKB)4100000011912203 035 $a(MiAaPQ)EBC6578009 035 $a(Au-PeEL)EBL6578009 035 $a(OCoLC)1249473110 035 $a(PPN)255293372 035 $a(EXLCZ)994100000011912203 100 $a20211211d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aPupil reactions in response to human mental activity /$fMinoru Nakayama, Yasutaka Shimizu, editors 210 1$aSingapore :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (110 pages) 225 0 $aBehaviormetrics: Quantitative Approaches to Human Behavior ;$vVolume 6,$x2524-4027 311 $a981-16-1721-X 320 $aIncludes bibliographical references and index. 327 $aIntro -- Preface -- Contents -- Controlling the Effects of Brightness on the Measurement of Pupil Size as a Means of Evaluating Mental Activity -- 1 Introduction -- 2 Pupillary Change Due to Picture Brightness -- 2.1 Picture Brightness Control -- 2.2 Experimental Method of Observing the Influence of Brightness -- 2.3 Pupillary Change With Levels of Picture Brightness -- 3 Pupillary Change in Response to Brightness Levels -- 3.1 Experimental Procedure for Pupillary Change Due to Brightness -- 3.2 Results of Observation of Pupillary Change According to Brightness Level -- 3.3 Procedure for Correcting Pupil Size -- 4 Pupillary Changes in Response to Picture Content -- 4.1 Assessment Procedure -- 4.2 Results of Assessment -- 5 Summary -- References -- Pupil Reaction Model Using a Neural Network for Brightness Change -- 1 Introduction -- 2 Experimental Method -- 2.1 Visual Stimuli -- 2.2 Observed Records -- 3 Pupil Reaction Model -- 3.1 Linear Model -- 3.2 Neural Network Model -- 4 Evaluation of Performance Models -- 4.1 Temporal Changes in Pupil Size -- 4.2 Mean Square Errors -- 5 Characteristics of the Model Developed -- 5.1 Optimization of the Number of Units -- 5.2 Weight Distribution of Input Layer -- 5.3 Representation of Hidden Units -- 6 Evaluation of Brightness Compensation Performance -- 6.1 Compensation Due to Random Changes in Brightness During a Video -- 6.2 Compensation Performance During a Video -- 7 Summary -- References -- A Neural-Network-Based Eye Pupil Reaction Model for Use with Television Programs -- 1 Introduction -- 2 Pupil Reaction Model -- 2.1 Modeling Procedure -- 2.2 Training Data Preparation -- 2.3 Evaluation of the model trained for changes in brightness -- 2.4 Internal Representation of the Trained Model -- 3 Evaluation of Extracted Mental Activity Using the Trained Model -- 3.1 Video Materials. 327 $a3.2 Compensation Procedures for the Influences of Brightness -- 3.3 Determination of Sampling Duration -- 3.4 Brightness Change Compensation Performance -- 3.5 Video Clip Compensation Performance -- 3.6 Temporal Pupil Responses During Clip Viewing -- 4 Summary -- References -- The Relationship Between Pupillary Changes and Subjective Indices to the Content of Television Programs -- 1 Introduction -- 2 Experimental Method -- 2.1 Pupil Size -- 2.2 Blinks -- 2.3 Subjective Impression -- 2.4 Emotional Impressions of Movie Clips -- 2.5 Presented Video and Experimental Procedure -- 3 Results -- 3.1 Temporal Changes Caused by Clips Viewed -- 3.2 Scene Splitting -- 4 Relationship Between Measured Metrics and Overall Impressions of Video Clips -- 4.1 Overall Impression -- 4.2 Relationship Between Measured Metrics and Overall Impressions -- 4.3 Factors Contributing to Observed Metrics -- 5 Summary -- References -- An Estimation Model for Pupil Size of Blink Artifacts While Viewing TV Programs -- 1 Introduction -- 2 Estimation of Pupil Size -- 2.1 Estimation Using MLP -- 2.2 Training of Pupil Size -- 2.3 Results of Training -- 3 Pupil Estimation During Blinks -- 3.1 Training Using Blink Patterns -- 3.2 Training Results -- 3.3 Internal Representation of the Network -- 4 Applying the Model to TV Program Viewing -- 4.1 Video Clips Presented -- 4.2 Compensation Performance for the Influence of Brightness -- 4.3 Processing Effectiveness Using the Model -- 5 Summary -- References -- Estimation of Eye-Pupil Size During Blink by Support Vector Regression -- 1 Introduction -- 2 Method -- 2.1 Periodic Pupillary Response -- 2.2 Training Data -- 2.3 Pupil Size Estimation by Use of SVR -- 3 Result -- 3.1 Reproducing Performance -- 3.2 Estimation Results -- 3.3 Estimation Performance -- 3.4 Application to Another Data Set -- 4 Summary -- References. 327 $aFrequency Analysis of Task Evoked Pupillary Response and Eye Movement -- 1 Introduction -- 2 Experimental Method -- 2.1 Experimental Tasks -- 2.2 Pupil Size Estimation During the Eye Blink -- 2.3 Eye Movement During Blink -- 3 Results of Pupillary Response -- 3.1 Estimation Performance -- 3.2 Average Pupil Size -- 3.3 Frequency Analysis of Pupillography -- 4 Results of Eye Movement -- 4.1 Saccadic Eye Movement -- 4.2 Frequency Analysis of Eye Movement Data -- 5 Discussion -- 5.1 Pupillary Response -- 5.2 Eye Movement -- 6 Conclusions -- References -- Appendix Epilogue: Last But Not Least -- References. 410 0$aBehaviormetrics: Quantitative Approaches to Human Behavior 606 $aPsychometrics$xData processing 606 $aPsicometria$2thub 606 $aProcessament de dades$2thub 608 $aLlibres electrònics$2thub 615 0$aPsychometrics$xData processing. 615 7$aPsicometria 615 7$aProcessament de dades 676 $a150.28553 702 $aNakayama$b Minoru 702 $aShimizu$b Yasutaka 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466409403316 996 $aPupil reactions in response to human mental activity$92557643 997 $aUNISA