Eye Tracking A comprehensive guide to methods and measures 1st edition by Kenneth Holmqvist, Marcus Nyström, Richard Andersson, Richard Dewhurst, Halszka Jarodzka, Joost van ISBN 0191625428 9780191625428

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ISBN 10: 0191625428
ISBN 13: 9780191625428
Author: Kenneth Holmqvist, Marcus Nyström, Richard Andersson, Richard Dewhurst, Halszka Jarodzka, Joost van

We make 3-5 eye movements per second, and these movements are crucial in helping us deal with the vast amounts of information we encounter in our everyday lives. In recent years, thanks to the development of eye tracking technology, there has been a growing interest in monitoring and measuring these movements, with a view to understanding how we attend to and process the visual information we encounter Eye tracking as a research tool is now more accessible than ever, and is growing in popularity amongst researchers from a whole host of different disciplines. Usability analysts, sports scientists, cognitive psychologists, reading researchers, psycholinguists, neurophysiologists, electrical engineers, and others, all have a vested interest in eye tracking for different reasons. The ability to record eye-movements has helped advance our science and led to technological innovations. However, the growth of eye tracking in recent years has also presented a variety of challenges – in particular the issue of how to design an eye-tracking experiment, and how to analyse the data. This book is a much needed comprehensive handbook of eye tracking methodology. It describes how to evaluate and acquire an eye-tracker, how to plan and design an eye tracking study, and how to record and analyse eye-movement data. Besides technical details and theory, the heart of this book revolves around practicality – how raw data samples are converted into fixations and saccades using event detection algorithms, how the different representations of eye movement data are calculated using AOIs, heat maps and scanpaths, and how all the measures of eye movements relate to these processes. Part I presents the technology and skills needed to perform high-quality research with eye-trackers. Part II covers the predominant methods applied to the data which eye-trackers record. These include the parsing of raw sample data into oculomotor events, and how to calculate other representations of eye movements such as heat maps and transition matrices. Part III gives a comprehensive outline of the measures which can be calculated using the events and representations described in Part II. This is a taxonomy of the measures available to eye-tracking researchers, sorted by type of movement of the eyes and type of analysis. For anyone in the sciences considering conducting research involving eye-tracking, this book will be an essential reference work.

Eye Tracking A comprehensive guide to methods and measures 1st Table of contents:

1 Introduction

1.1 The structure of this book

1.1.1 Technical and methodological skills

1.1.2 Events and representations

1.1.3 Measures and their operational definitions

1.2 How eye-movement measures are described in this book

1.2.1 The target question and the summary box

1.2.2 The name(s)

1.2.3 The operational definitions

1.2.4 Typical values and histograms

1.2.5 Usage

1.3 Terminology and style

1.4 Material used in the book

Part I Technical and Methodological Skills

2 Eye-tracker Hardware and its Properties

2.1 A brief history of the competences around eye-trackers

2.2 Manufacturers and customers

2.3 Hands-on advice on how to choose infrastructure and hardware

2.4 How to set up an eye-tracking laboratory

2.4.1 Eye-tracking labs as physical spaces

2.4.2 Types of laboratories and their infrastructure

2.5 Measuring the movements of the eye

2.5.1 The eye and its movements

2.5.2 Binocular properties of eye movements

2.5.3 Pupil and corneal reflection eye tracking

2.6 Data quality

2.6.1 Sampling frequency: what speed do you need?

2.6.2 Accuracy and precision

2.6.3 Eye-tracker latencies, temporal precision, and stimulus-synchronization latencies

2.6.4 Filtering and denoising

2.6.5 Active and passive gaze contingency

2.7 Types of eye-trackers and the properties of their set-up

2.7.1 The three types of video-based eye-trackers

2.7.2 Robustness

2.7.3 Tracking range and headboxes

2.7.4 Mono- versus binocular eye tracking

2.7.5 The parallax error

2.7.6 Data samples and the frames of reference

2.8 Summary

3 From Vague Idea to Experimental Design

3.1 The initial stage—explorative pilots, fishing trips, operationalizations, and highway research

3.1.1 The explorative pilot

3.1.2 The fishing trip

3.1.3 Theory-driven operationalizations

3.1.4 Operationalization through traditions and paradigms

3.2 What caused the effect? The need to understand what you are studying

3.2.1 Correlation and causality: a matter of control

3.2.2 What measures to select as dependent variables

3.2.3 The task

3.2.4 Stimulus scene, and the areas of interest

3.2.5 Trials and their durations

3.2.6 How to deal with participant variation

3.2.7 Participant sample size

3.3 Planning for statistical success

3.3.1 Data exploration

3.3.2 Data description

3.3.3 Data analysis

3.3.4 Data modelling

3.3.5 Further statistical considerations

3.4 Auxiliary data: planning

3.4.1 Methodological triangulation of eye movement and auxiliary data

3.4.2 Questionnaires and Likert scales

3.4.3 Reaction time measures

3.4.4 Galvanic skin response (GSR)

3.4.5 Motion tracking

3.4.6 Electroencephalography (EEG)

3.4.7 Functional magnetic resonance imaging (fMRI)

3.4.8 Verbal data

3.5 Summary

4 Data Recording

4.1 Hands-on advice for data recording

4.2 Building the experiment

4.2.1 Stimulus preparation

4.2.2 Physically building the recording environment

4.2.3 Pilot testing the experiment

4.3 Participant recruitment and ethics

4.3.1 Ethics toward participants

4.4 Eye camera set-up

4.4.1 Mascara

4.4.2 Droopy eyelids and downward eyelashes

4.4.3 Shadows and infrared reflections in glasses

4.4.4 Bi-focal glasses

4.4.5 Contact lenses

4.4.6 Direct sunlight and other infrared sources

4.4.7 The fourth Purkinje reflection

4.4.8 Wet eyes due to tears or allergic reactions

4.4.9 The retinal reflection (bright-pupil condition)

4.4.10 Mirror orientation and dirty mirrors

4.5 Calibration

4.5.1 Points

4.5.2 Geometry

4.5.3 The calibration procedure

4.5.4 Corner point difficulties and solutions

4.5.5 Calibration validation

4.5.6 Binocular and head-tracking calibration

4.5.7 Calibration tricks with head-mounted systems

4.6 Instructions and start of recording

4.7 Auxiliary data: recording

4.7.1 Non-interfering set-ups

4.7.2 Interfering set-ups

4.7.3 Verbal data

4.8 Debriefing

4.9 Preparations for data analysis

4.9.1 Data quality

4.9.2 Analysis software for eye-tracking data

4.10 Summary

Part II Detecting Events and Building Representations

5 Estimating Oculomotor Events from Raw Data Samples

5.1 The setting dialogues and the output

5.2 Principles and algorithms for event detection

5.3 Hands-on advice for event detection

5.4 Challenging issues in event detection

5.4.1 Choosing parameter settings

5.4.2 Noise, artefacts, and data quality

5.4.3 Glissades

5.4.4 Sampling frequency

5.4.5 Smooth pursuit

5.4.6 Binocularity

5.5 Algorithmic definitions

5.5.1 Dispersion-based algorithms

5.5.2 Velocity and acceleration algorithms

5.6 Manual coding of events

5.7 Blink detection

5.8 Smooth pursuit detection

5.9 Detection of noise and artefacts

5.10 Detection of other events

5.11 Summary: oculomotor events in eye-movement data

6 Areas of Interest

6.1 The AOI editor and your hypothesis

6.2 Hands-on advice for using AOIs

6.3 The basic AOI events

6.3.1 The AOI hit

6.3.2 The dwell

6.3.3 The transition

6.3.4 The return

6.3.5 The AOI first skip

6.3.6 The AOI total skip

6.4 AOI-based representations of data

6.4.1 Dwell maps

6.4.2 The AOI strings

6.4.3 Transition matrices

6.4.4 Markov models

6.4.5 AOIs over time

6.4.6 Time and order

6.5 Types of AOIs

6.5.1 Whitespace

6.5.2 Planes

6.5.3 Dynamic AOIs

6.5.4 Distributed AOIs

6.5.5 Gridded AOIs

6.5.6 Fuzzy AOIs

6.5.7 Stimulus-inherent AOI orders

6.5.8 Participant-specific AOI identities

6.5.9 AOI identities across stimuli

6.5.10 AOIs in the feature domain

6.6 Challenging issues with AOIs

6.6.1 Choosing and positioning AOIs

6.6.2 Overlapping AOIs

6.6.3 Deciding the size of an AOI

6.6.4 Data samples or fixations and saccades?

6.6.5 Dealing with inaccurate data

6.6.6 Normalizing AOI measures to size, position, and content

6.6.7 AOIs in gaze-overlaid videos

6.7 Summary: events and representations from AOIs

7 Attention Maps—Scientific Tools or Fancy Visualizations? 231

7.1 Heat map settings dialogues

7.2 Principles and terminology

7.3 Hands-on advice for using attention maps

7.4 Challenging issues: interpreting and building attention maps

7.4.1 Interpreting attention map visualizations

7.4.2 How many fixations/participants?

7.4.3 How attention maps are built

7.5 Usage of attention maps other than for visualization

7.5.1 Using attention maps to define AOIs

7.5.2 Attention maps as image and data processing tools

7.5.3 Using attention maps in measures

7.6 Summary: attention map representations

8 Scanpaths—Theoretical Principles and Practical Application

8.1 What is a scanpath?

8.2 Hands-on advice for using scanpaths

8.3 Usages of scanpath visualization

8.3.1 Data quality checks

8.3.2 Data analysis by visual inspection

8.3.3 Exhibiting scanpaths in publications

8.4 Scanpath events

8.4.1 The backtrack

8.4.2 The regression family of events

8.4.3 The look-back and inhibition of return

8.4.4 The look-ahead

8.4.5 The local and global subscans

8.4.6 Ambient versus focal fixations

8.4.7 The sweep

8.4.8 The reading and scanning events

8.5 Scanpath representations

8.5.1 Symbol sequences

8.5.2 Vector sequences

8.5.3 Attention map sequences

8.6 Principles for scanpath comparison

8.6.1 Representation

8.6.2 Simplification

8.6.3 Sequence alignment

8.6.4 Calculation

8.6.5 Pairwise versus groupwise comparison

8.7 Unresolved issues concerning scanpaths

8.7.1 Relationships between scanpaths and cognitive processes

8.7.2 Scanpath Theory

8.7.3 Scanpath planning

8.7.4 The average scanpath

8.7.5 Comparing scanpaths

8.8 Summary: scanpath events and representations

9 Auxiliary Data: Events and Representations

9.1 Event-based coalignment

9.1.1 Alignment of eye-tracking events with auxiliary data

9.1.2 Latencies between events in eye-tracking and auxiliary data

9.2 Triangulating eye-movement data with verbal data

9.2.1 Detecting events in verbal data: transcribing verbalizations and segmenting them into idea units

9.2.2 Coding of verbal data units

9.2.3 Representations, measures, and statistical considerations for verbal data

9.2.4 Open issues: how to co-analyse eye-movement and verbal data

9.3 Summary: events and representations with auxiliary data

Part III Measures

10 Movement Measures

10.1 Movement direction measures

10.1.1 Saccadic direction

10.1.2 Glissadic direction

10.1.3 Microsaccadic direction

10.1.4 Smooth pursuit direction

10.1.5 Scanpath direction

10.2 Movement amplitude measures

10.2.1 Saccadic amplitude

10.2.2 Glissadic amplitude

10.2.3 Microsaccadic amplitude

10.2.4 Smooth pursuit length

10.2.5 Scanpath length

10.2.6 Blink amplitude

10.3 Movement duration measures

10.3.1 Saccadic duration

10.3.2 Scanpath duration

10.3.3 Blink duration

10.4 Movement velocity measures

10.4.1 Saccadic velocity

10.4.2 Smooth pursuit velocity

10.4.3 Scanpath velocity and reading speed

10.4.4 Pupil constriction and dilation velocity

10.5 Movement acceleration measures

10.5.1 Saccadic acceleration/deceleration

10.5.2 Skewness of the saccadic velocity profile

10.5.3 Smooth pursuit acceleration

10.5.4 Saccadic jerk

10.6 Movement shape measures

10.6.1 Saccadic curvature

10.6.2 Glissadic curvature

10.6.3 Smooth pursuit: degree of smoothness

10.6.4 Global to local scanpath ratio

10.7 AOI order and transition measures

10.7.1 Order of first AOI entries

10.7.2 Transition matrix density

10.7.3 Transition matrix entropy

10.7.4 Number and proportion of specific subscans

10.7.5 Unique AOIs

10.7.6 Statistical analysis of a transition matrix

10.8 Scanpath comparison measures

10.8.1 Correlation between sequences

10.8.2 Attention map sequence similarity

10.8.3 The string edit distance

10.8.4 Refined AOI sequence alignment measures

10.8.5 Vector sequence alignment

11 Position Measures

11.1 Basic position measures

11.1.1 Position

11.1.2 Landing position in AOI

11.2 Position dispersion measures

11.2.1 Comparison of dispersion measures

11.2.2 Standard deviation, variance, and RMS

11.2.3 Range

11.2.4 Nearest neighbour index

11.2.5 The convex hull area

11.2.6 Bivariate contour ellipse area (BCEA)

11.2.7 Skewness of the Voronoi cell distribution

11.2.8 Coverage, and volume under an attention map

11.2.9 Relative entropy and the Kullback-Leibler Distance (KLD)

11.2.10 Average landing altitude

11.3 Position similarity measures

11.3.1 Euclidean distance

11.3.2 Mannan similarity index

11.3.3 The earth mover distance

11.3.4 The attention map difference

11.3.5 Average landing altitude

11.3.6 The angle between dwell map vectors

11.3.7 The correlation coefficient between two attention maps

11.3.8 The Kullback-Leibler distance

11.4 Position duration measures

11.4.1 The inter-microsaccadic interval (IMSI)

11.4.2 Fixation duration

11.4.3 The skewness of the frequency distribution of fixation durations

11.4.4 First fixation duration after onset of stimulus

11.4.5 First fixation duration in an AOI, and also the second

11.4.6 Dwell time

11.4.7 Total dwell time

11.4.8 First and second pass (dwell) times in an AOI

11.4.9 Diversion duration

11.5 Pupil diameter

11.6 Position data and confounding factors

11.6.1 Participant brainware and substances

11.6.2 Participant cultural background

11.6.3 Participant experience and anticipation

11.6.4 Communication, imagination, and problem solving

11.6.5 Central bias

11.6.6 The stimulus

12 Numerosity Measures

12.1 Saccades: number, proportion, and rate

12.1.1 Number of saccades

12.1.2 Proportion of saccades

12.1.3 Saccadic rate

12.2 Glissadic proportion

12.3 Microsaccadic rate

12.4 Square-wave jerk rate

12.5 Smooth pursuit rate

12.6 Blink rate

12.7 Fixations: number, proportion, and rate

12.7.1 Number of fixations

12.7.2 Proportion of fixations

12.7.3 Fixation rate

12.8 Dwells: number, proportion, and rate

12.8.1 Number of dwells (entries) in an area of interest

12.8.2 Proportion of dwells to an area of interest

12.8.3 Dwell rate

12.9 Participant, area of interest, and trial proportion

12.9.1 Participant looking and skipping proportions

12.9.2 Proportion of areas of interest looked at

12.9.3 Proportion of trials

12.10 Transition number, proportion, and rate

12.10.1 Number of transitions

12.10.2 Number of returns to an area of interest

12.10.3 Transition rate

12.11 Number and rate of regressions, backtracks, look-backs, and look-aheads

12.11.1 Number of regressions in and between areas of interest

12.11.2 Number of regressions out of and into an area of interest

12.11.3 Regression rate

12.11.4 Number of backtracks

12.11.5 Number of look-aheads

13 Latency and Distance Measures

13.1 Latency measures

13.1.1 Saccadic latency

13.1.2 Smooth pursuit latency

13.1.3 Latency of the reflex blink

13.1.4 Pupil dilation latency

13.1.5 EFRPs—eye fixation related potentials

13.1.6 Entry time in AOI

13.1.7 Thresholded entry time

13.1.8 Latency of the proportion of participants over time

13.1.9 Return time

13.1.10 Eye–voice latencies

13.1.11 Eye–hand span

13.1.12 The eye–eye span (cross-recurrence analysis)

13.2 Distances

13.2.1 Eye–mouse distance

13.2.2 Disparities

13.2.3 Smooth pursuit gain

13.2.4 Smooth pursuit phase

13.2.5 Saccadic gain

14 What are Eye-Movement Measures and How can they be Harnessed?

14.1 Eye-movement measures: plentiful but poorly accessible

14.2 Measure concepts and operationalizing them

14.3 Proposed model of eye-tracking measures

14.4 Classification of eye-movement measures

14.5 How to construct even more measures

14.6 Summary

References

Index

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