What’s on TV? Detecting age-related neurodegenerative eye disease using eye movement scanpaths
Purpose: We test the hypothesis that age-related neurodegenerative eye disease can be detected by examining patterns of eye movement recorded whilst a person naturally watches a movie. Methods: Thirty-two elderly people with healthy vision (median age: 70, interquartile range [IQR] 64 to 75 yrs) and...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2014-11-01
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| Series: | Frontiers in Aging Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnagi.2014.00312/full |
| _version_ | 1811223680169017344 |
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| author | David Paul Crabb Nicholas David Smith Haogang eZhu |
| author_facet | David Paul Crabb Nicholas David Smith Haogang eZhu |
| author_sort | David Paul Crabb |
| collection | DOAJ |
| description | Purpose: We test the hypothesis that age-related neurodegenerative eye disease can be detected by examining patterns of eye movement recorded whilst a person naturally watches a movie. Methods: Thirty-two elderly people with healthy vision (median age: 70, interquartile range [IQR] 64 to 75 yrs) and 44 patients with a clinical diagnosis of glaucoma (median age: 69, IQR 63 to 77 yrs) had standard vision examinations including automated perimetry. Disease severity was measured using a standard clinical measure (visual field mean deviation; MD). All study participants viewed three unmodified TV and film clips on a computer set up incorporating the Eyelink 1000 eyetracker (SR Research, Ontario, Canada). Eye movement scanpaths were plotted using novel methods that first filtered the data and then generated saccade density maps. Maps were then subjected to a feature extraction analysis using kernel principal component analysis (KPCA). Features from the KPCA were then classified using a standard machine based classifier trained and tested by a 10-fold cross validation which was repeated 100 times to estimate the confidence interval (CI) of classification sensitivity and specificity. Results: Patients had a range of disease severity from early to advanced (median [IQR] right eye and left eye MD was -7 [-13 to -5] dB and -9 [-15 to -4] dB respectively). Average sensitivity for correctly identifying a glaucoma patient at a fixed specificity of 90% was 79% (95% CI: 58 to 86%). The area under the Receiver Operating Characteristic curve was 0.84 (95% CI: 0.82 to 0.87). Conclusions: Huge data from scanpaths of eye movements recorded whilst people freely watch TV type films can be processed into maps that contain a signature of vision loss. In this proof of principle study we have demonstrated that a group of patients with age-related neurodegenerative eye disease can be reasonably well separated from a group of healthy peers by considering these eye movement signatures alone. |
| first_indexed | 2024-04-12T08:36:50Z |
| format | Article |
| id | doaj.art-ee4bfd7efea441a3b5fcc909fdcf5892 |
| institution | Directory Open Access Journal |
| issn | 1663-4365 |
| language | English |
| last_indexed | 2024-04-12T08:36:50Z |
| publishDate | 2014-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Aging Neuroscience |
| spelling | doaj.art-ee4bfd7efea441a3b5fcc909fdcf58922022-12-22T03:40:00ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652014-11-01610.3389/fnagi.2014.00312108109What’s on TV? Detecting age-related neurodegenerative eye disease using eye movement scanpathsDavid Paul Crabb0Nicholas David Smith1Haogang eZhu2City University LondonCity University LondonCity University LondonPurpose: We test the hypothesis that age-related neurodegenerative eye disease can be detected by examining patterns of eye movement recorded whilst a person naturally watches a movie. Methods: Thirty-two elderly people with healthy vision (median age: 70, interquartile range [IQR] 64 to 75 yrs) and 44 patients with a clinical diagnosis of glaucoma (median age: 69, IQR 63 to 77 yrs) had standard vision examinations including automated perimetry. Disease severity was measured using a standard clinical measure (visual field mean deviation; MD). All study participants viewed three unmodified TV and film clips on a computer set up incorporating the Eyelink 1000 eyetracker (SR Research, Ontario, Canada). Eye movement scanpaths were plotted using novel methods that first filtered the data and then generated saccade density maps. Maps were then subjected to a feature extraction analysis using kernel principal component analysis (KPCA). Features from the KPCA were then classified using a standard machine based classifier trained and tested by a 10-fold cross validation which was repeated 100 times to estimate the confidence interval (CI) of classification sensitivity and specificity. Results: Patients had a range of disease severity from early to advanced (median [IQR] right eye and left eye MD was -7 [-13 to -5] dB and -9 [-15 to -4] dB respectively). Average sensitivity for correctly identifying a glaucoma patient at a fixed specificity of 90% was 79% (95% CI: 58 to 86%). The area under the Receiver Operating Characteristic curve was 0.84 (95% CI: 0.82 to 0.87). Conclusions: Huge data from scanpaths of eye movements recorded whilst people freely watch TV type films can be processed into maps that contain a signature of vision loss. In this proof of principle study we have demonstrated that a group of patients with age-related neurodegenerative eye disease can be reasonably well separated from a group of healthy peers by considering these eye movement signatures alone.http://journal.frontiersin.org/Journal/10.3389/fnagi.2014.00312/fullAlzheimer DiseaseEye DiseasesEye MovementsGlaucomaOptic NervePerception |
| spellingShingle | David Paul Crabb Nicholas David Smith Haogang eZhu What’s on TV? Detecting age-related neurodegenerative eye disease using eye movement scanpaths Frontiers in Aging Neuroscience Alzheimer Disease Eye Diseases Eye Movements Glaucoma Optic Nerve Perception |
| title | What’s on TV? Detecting age-related neurodegenerative eye disease using eye movement scanpaths |
| title_full | What’s on TV? Detecting age-related neurodegenerative eye disease using eye movement scanpaths |
| title_fullStr | What’s on TV? Detecting age-related neurodegenerative eye disease using eye movement scanpaths |
| title_full_unstemmed | What’s on TV? Detecting age-related neurodegenerative eye disease using eye movement scanpaths |
| title_short | What’s on TV? Detecting age-related neurodegenerative eye disease using eye movement scanpaths |
| title_sort | what s on tv detecting age related neurodegenerative eye disease using eye movement scanpaths |
| topic | Alzheimer Disease Eye Diseases Eye Movements Glaucoma Optic Nerve Perception |
| url | http://journal.frontiersin.org/Journal/10.3389/fnagi.2014.00312/full |
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