Get Started. It's Free
or sign up with your email address
Review by Mind Map: Review

1. Introduction

1.1. a summary and evolution of research approaches that use eye tracking technology and computational analysis to measure and compare eye movements under different tasks and experiments

1.2. An opportune early diagnosis of Alzheimer’s disease (AD) would help to overcome symptoms and improve the quality of life for AD patients.

2. Data Collection

2.1. Eye trackers

2.1.1. static

2.1.1.1. screen based tracker

2.1.1.2. head mounted

2.1.2. Mobility

2.1.2.1. Tobbi

2.1.2.2. SMI

2.2. Concerns

2.2.1. Uncontrolled participants

2.2.2. participants take a non optimal pose

2.3. Participants

2.3.1. young controls

2.3.2. elder control

2.3.3. PwAD

2.3.4. MCI

3. Eye Movements and AD

3.1. Eye Movements Analysis in Controlled Scenarios.

3.1.1. 12

3.1.1.1. Method: Subjects responded to targets presented on a hemispherical screen with diverse eccentricity. The

3.1.1.2. PwAD were significate less accurate than elderly controls. Elder were less accurate than young controls.

3.1.1.3. Participants: AD: 17 mild AD. CG elderly: 23 CG young: 24. Apparatus:

3.1.1.4. Tool: Apparatus: Eye tracker (Senso-Motoric Instruments)

3.1.2. 11

3.1.2.1. Eye movements from subjects were examined during reading regular and high predictable sentences. Subjects

3.1.2.2. PwAD gaze was longer than CG gaze. CG decreased gaze duration with high predictable sentences suggesting reading enhancement using stored information.

3.1.2.3. Participants: AD: 35 CG: 35

3.1.2.4. Tools: Apparatus: EyeLink 1000. Chinrest to control

3.1.3. 25

3.1.3.1. Method: Subjects responded to targets presented on a hemispherical screen with diverse eccentricity.

3.1.3.2. Results: PwAD recognized less targets in the center. No difference was found with CG on the peripheral targets.

3.1.3.3. Participants: AD: 18 CG: 20

3.1.3.4. Tools: Hemispherical screen Octupus 900 with camera used for eye tracking.

3.1.4. 19

3.1.4.1. Method: Longitudinal study with Gap and overlap paradigms.

3.1.4.2. Results: PwAD had slower reaction times than CG. Prosaccades did not deteriorate after the 12-month longitudinal study in AD.

3.1.4.3. Participants: AD: 11 CG elderly: 25

3.1.4.4. Tool: ExpressEye

3.1.5. 23

3.1.5.1. Method: Eye movements from subjects were examined while read proverbs.

3.1.5.2. Results: PwAD has less word predictability than CG.

3.1.5.3. Participants: AD: 20 CG: 40.

3.1.5.4. Tools: EyeLink 1000. Chinrest to control eye movements.

3.1.6. 26

3.1.6.1. Method: The King-Devick test (with saccadic and other movements) was applied to subjects.

3.1.6.2. Result: The King-Devick test may a tool to detect cognitive impairment associated with AD.

3.1.6.3. Participants: AD:32 CG: 135 MCI:39

3.1.6.4. Tool: N/A

3.1.7. 27

3.1.7.1. Method: Subjects looked a series of slides containing four images of different emotional themes.

3.1.7.2. Result: PwAD with apathy had diminished attentional bias toward social-themed stimuli.

3.1.7.3. Participants: AD: 36 (Apathy: 17 Not apathy: 19).

3.1.7.4. Tool: Binocular eye tracking system developed by EL-MAR Inc.

3.1.8. 29

3.1.8.1. Method: Eye movements from subjects were examined while read sentences.

3.1.8.2. Result: PwAD had more fixations on regular and high predictable sentences. PwAD spend more time reading the sentence. CG had less frequent second pass fixation over sentences.

3.1.8.3. Participants: AD: 35 CG-elderly: 35.

3.1.8.4. Tool: Apparatus: EyeLink 1000. Chinrest to control eye movements.

3.1.9. 30

3.1.9.1. Method: Subjects made saccadic movement to photographs to target instructed scenes (natural vs urban, indoor vs outdoor).

3.1.9.2. Result: Were found differences between controls and PwAD on accuracy but not saccadic latency.

3.1.9.3. Participants: AD:24 CG age-matched:28 CG young: 26.

3.1.9.4. Tool: Eye tracker (Red-M, Senso-Motoric Instruments).

3.1.10. 31

3.1.10.1. Method: Eye movements from subjects were examined while read low and high predictable sentences.

3.1.10.2. Result: CG have shorter gaze duration on high predictable sentences. PwAD have similar gaze duration on both low and high predictable sentences. PwAD gaze duration is longer than CG.

3.1.10.3. Participants: AD: 20 CG age-matched: 40.

3.1.10.4. Tool: EyeLink1000. Chinrest to control eye movements..

3.1.11. 32

3.1.11.1. Method: Eye movements from subjects were examined while read sentences.

3.1.11.2. Result: PwAD have altered visual exploration and absence on contextual predictability.

3.1.11.3. Participants: AD:18 HC age-matched: 40.

3.1.11.4. Tool: EyeLink 2K. Chinrest to control eye movements.

3.1.12. 33

3.1.12.1. Method: Eye movements from subjects were examined while read sentences.

3.1.12.2. Result: PwAD evidences marked alterations in eye movement behavior during reading.

3.1.12.3. Participants: AD: 20 CG age-matched: 25.

3.1.12.4. Tool: EyeLink1000. Chinrest to control eye movements.

3.1.13. 34

3.1.13.1. Method: Subjects were required to look to a small fixation cross for 20 seconds on the center of a screen.

3.1.13.2. Result: CG and PwAD showed significantly differences of microsaccade direction.

3.1.13.3. Participants: AD: 18 MCI: 15 CG age-matched: 21.

3.1.13.4. Tool: EyeSee Cam.

3.1.14. 35

3.1.14.1. Method: Visual targets were presented to subjects in a dim room. Prosaccade and anti saccade trails.

3.1.14.2. Result: The antisaccade taks performance serves as a measure of executive function on PwAD.

3.1.14.3. Participants: AD: 28 MCI: 36 CG elderly: 118.

3.1.14.4. Tool: Dual Purkinje Image Tracker.

3.1.15. 36

3.1.15.1. Method: Pro-saccade and anti-saccade tasks. Gap and overlap paradigms.

3.1.15.2. Result: PwAD have an excessive proportion of uncorrected errors in the antisaccade test.

3.1.15.3. Participants: AD: 18 Parkinson disease: 25 CG-young: 17 CG elderly: 18.

3.1.15.4. Tool: Apparatus: Head mounted device ExpressEye eyetracker.

3.1.16. 37

3.1.16.1. Method: Horizontal and vertical saccades. Gap and overlap paradigms on a black computer screen.

3.1.16.2. Result: A link between MMSE and saccade latency.

3.1.16.3. Participants: AD: 25 Amnestic MCI: 18 CG elderly: 30.

3.1.16.4. Tool: Head mounted Eyeseecam.

3.2. Eye Movements Analysis in Naturalistic Tasks

3.2.1. 28

3.2.1.1. Method: Subjects performed a variety of tasks: walking, through stairs, through a room with and without obstacles.

3.2.1.2. Result: The Posterior Cortical Atrophy (PCA) patient had longer mean fixation durations than PwAD and CG. Mean fixation duration between PwAD and CG was similar.

3.2.1.3. Participants: AD: 1 CG:1 PCA: 1.

3.2.1.4. Tool: SMI mobile eye tracker.

3.2.2. 73

3.2.2.1. Method: understand the relation between activity execution and eye movements by investigating the eye patterns and eye-hand coordination on actions.

3.2.2.2. Results indicate that subjects rarely fixate on objects irrelevant to a performed action

3.2.3. 76

3.2.3.1. Method: the eye movements in an ADL task are analyzed from a patient with action disorganization syndrome (ADS), from a PwAD, and from control subjects.

3.2.3.2. Result:s show difference in the visual behavior from the participants while they were preparing a cup of tea.

3.2.4. 76

3.2.4.1. Method: Subjects looked a series of slides containing four images of different emotional themes.

3.2.4.2. Result: PwAD with apathy had diminished attentional bias toward social-themed stimuli.

3.2.4.3. Participants: AD: 36 (Apathy: 17 Not apathy: 19).

3.2.4.4. Tool: Binocular eye tracking system developed by EL-MAR Inc.

4. Towards Early Detection Leveraging on Computational Attention Modelling

4.1. Recommended devices

4.1.1. Egocentric camera

4.1.1.1. it could be worked mobile eye trackers (Tobbi or SMI)

4.1.1.2. For example, GoPro, Samsung Glass and Microsoft Sense Cam

4.2. 118

4.2.1. Method: analyzes the visual search task performance from AD patients by conducting experiments using salient and not salient search conditions.

4.2.2. Result:The PwAD show longer reaction times than control participants. However, the gap between both groups is bigger when searching for nonsalient target items. This suggests that salient elements attract PwAD.

5. Conclusion and future works

5.1. visual features can be used for early diagnosis and progression measurement.

5.2. computer vision techniques, such as visual saliency and object detections in ADL performance settings, could be a good means to measure visual attention of PwAD to diagnose

5.3. Limitation 1: estimating gaze on top-down driven mechanisms and relating bottom- up mechanisms with the activities.

5.4. Limitation 2: conduct experiments with persons with different cognitive problems

6. Article information

6.1. Date

6.1.1. 2018

6.2. Authors

6.2.1. Beltrán, Jessica García-Vázquez, Mireya S. Benois-Pineau, Jenny Gutierrez-Robledo, Luis Miguel Dartigues, Jean François