Validation of a novel software‐based platform to extract oculometric measures
Purpose: Eye‐tracking systems are a valuable tool in the assessment of disorders by detecting eye movement abnormalities. However, current systems require lab settings, extraction of oculometric measures entails dedicated long sessions, and operation requires qualified personnel. Recently, a novel s...
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| Veröffentlicht in: | Acta ophthalmologica (Oxford, England) England), 2022-12, Vol.100 (S275), p.n/a |
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| container_title | Acta ophthalmologica (Oxford, England) |
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| creator | Rosset, Israel Raveh, Eitan Shimon, Assaf Ben Anisimov, Vova Ben‐Ami, Edmund Kreitman, Rivka Breakstone, Micha |
| description | Purpose: Eye‐tracking systems are a valuable tool in the assessment of disorders by detecting eye movement abnormalities. However, current systems require lab settings, extraction of oculometric measures entails dedicated long sessions, and operation requires qualified personnel. Recently, a novel software‐based platform was developed, using a webcam, enabling the extraction of oculometric measures in a short test with seamless operation. The aim of this study was to validate this platform as compared with a validated eye‐tracker.
Methods: 82 participants (51 females, age range 21–88) were evaluated with a software‐based platform (NeuraLight, Israel) in a 15‐minute eye‐tracking test. Participants were presented with different stimuli for various tasks. During the test, data from a validated eye‐tracker (Tobii Pro, Sweden) were captured. Correlations between oculometric measures captured by both methods were calculated using Pearson correlation. Observable information on demographic data was measured using Fisher information matrix.
Results: Eye and gaze positions captured by the NeuraLight platform were highly correlated with eye‐tracker (r = 0.9–0.99, p 0.9, p |
| doi_str_mv | 10.1111/j.1755-3768.2022.0359 |
| format | Article |
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Methods: 82 participants (51 females, age range 21–88) were evaluated with a software‐based platform (NeuraLight, Israel) in a 15‐minute eye‐tracking test. Participants were presented with different stimuli for various tasks. During the test, data from a validated eye‐tracker (Tobii Pro, Sweden) were captured. Correlations between oculometric measures captured by both methods were calculated using Pearson correlation. Observable information on demographic data was measured using Fisher information matrix.
Results: Eye and gaze positions captured by the NeuraLight platform were highly correlated with eye‐tracker (r = 0.9–0.99, p < 0.01). Saccade and anti‐saccade latency, pro‐saccade and anti‐saccade error rates, position and velocity gain for all tasks were all highly correlated (r > 0.9, p < 0.01). Relative root mean square error of all measures in both methods was <0.1. Saccadic latency and fixation time were found to be in relation with participants' age.
Conclusions: NeuraLight platform was significantly correlated with a validated eye‐tracker, providing high accuracy for eye and gaze positions and oculometric measures. Relation between oculometric measures and age was established. The platform can be implemented for assessment of eye movements in practice. Future studies are needed to use the platform in various conditions.</description><identifier>ISSN: 1755-375X</identifier><identifier>EISSN: 1755-3768</identifier><identifier>DOI: 10.1111/j.1755-3768.2022.0359</identifier><language>eng</language><publisher>Malden: Wiley Subscription Services, Inc</publisher><subject>Age ; Eye movements ; Latency ; Saccadic eye movements ; Software</subject><ispartof>Acta ophthalmologica (Oxford, England), 2022-12, Vol.100 (S275), p.n/a</ispartof><rights>2022 The Authors Acta Ophthalmologica © 2022 Acta Ophthalmologica Scandinavica Foundation</rights><rights>Copyright © 2022 Acta Ophthalmologica Scandinavica Foundation</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c1779-6eba609b7845920b6c89fdca465f7182526b9b570e8865ddc1379640f234961a3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fj.1755-3768.2022.0359$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,1433,27924,27925,45575,46833</link.rule.ids></links><search><creatorcontrib>Rosset, Israel</creatorcontrib><creatorcontrib>Raveh, Eitan</creatorcontrib><creatorcontrib>Shimon, Assaf Ben</creatorcontrib><creatorcontrib>Anisimov, Vova</creatorcontrib><creatorcontrib>Ben‐Ami, Edmund</creatorcontrib><creatorcontrib>Kreitman, Rivka</creatorcontrib><creatorcontrib>Breakstone, Micha</creatorcontrib><title>Validation of a novel software‐based platform to extract oculometric measures</title><title>Acta ophthalmologica (Oxford, England)</title><description>Purpose: Eye‐tracking systems are a valuable tool in the assessment of disorders by detecting eye movement abnormalities. However, current systems require lab settings, extraction of oculometric measures entails dedicated long sessions, and operation requires qualified personnel. Recently, a novel software‐based platform was developed, using a webcam, enabling the extraction of oculometric measures in a short test with seamless operation. The aim of this study was to validate this platform as compared with a validated eye‐tracker.
Methods: 82 participants (51 females, age range 21–88) were evaluated with a software‐based platform (NeuraLight, Israel) in a 15‐minute eye‐tracking test. Participants were presented with different stimuli for various tasks. During the test, data from a validated eye‐tracker (Tobii Pro, Sweden) were captured. Correlations between oculometric measures captured by both methods were calculated using Pearson correlation. Observable information on demographic data was measured using Fisher information matrix.
Results: Eye and gaze positions captured by the NeuraLight platform were highly correlated with eye‐tracker (r = 0.9–0.99, p < 0.01). Saccade and anti‐saccade latency, pro‐saccade and anti‐saccade error rates, position and velocity gain for all tasks were all highly correlated (r > 0.9, p < 0.01). Relative root mean square error of all measures in both methods was <0.1. Saccadic latency and fixation time were found to be in relation with participants' age.
Conclusions: NeuraLight platform was significantly correlated with a validated eye‐tracker, providing high accuracy for eye and gaze positions and oculometric measures. Relation between oculometric measures and age was established. The platform can be implemented for assessment of eye movements in practice. Future studies are needed to use the platform in various conditions.</description><subject>Age</subject><subject>Eye movements</subject><subject>Latency</subject><subject>Saccadic eye movements</subject><subject>Software</subject><issn>1755-375X</issn><issn>1755-3768</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNqNkM9KxDAQh4MouK4-ghDw3JqkTdJ4WxZdhYU9-AdvIU0TaGk3a5K67s1H8Bl9EltX9uxcZhh-3wx8AFxilOKhrpsUc0qTjLMiJYiQFGVUHIHJYXt8mOnrKTgLoUGIYcbyCVi9qLauVKzdGjoLFVy7d9PC4GzcKm--P79KFUwFN62K1vkORgfNR_RKR-h037rORF9r2BkVem_COTixqg3m4q9PwfPd7dP8PlmuFg_z2TLRmHORMFMqhkTJi5wKgkqmC2ErrXJGLccFoYSVoqQcmaJgtKo0zrhgObIkywXDKpuCq_3djXdvvQlRNq736-GlJJzniGBSsCFF9yntXQjeWLnxdaf8TmIkR3eykaMZOVqSozs5uhu4mz23rVuz-x8kZ6vHX_gHMzxz3w</recordid><startdate>202212</startdate><enddate>202212</enddate><creator>Rosset, Israel</creator><creator>Raveh, Eitan</creator><creator>Shimon, Assaf Ben</creator><creator>Anisimov, Vova</creator><creator>Ben‐Ami, Edmund</creator><creator>Kreitman, Rivka</creator><creator>Breakstone, Micha</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope></search><sort><creationdate>202212</creationdate><title>Validation of a novel software‐based platform to extract oculometric measures</title><author>Rosset, Israel ; Raveh, Eitan ; Shimon, Assaf Ben ; Anisimov, Vova ; Ben‐Ami, Edmund ; Kreitman, Rivka ; Breakstone, Micha</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1779-6eba609b7845920b6c89fdca465f7182526b9b570e8865ddc1379640f234961a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Age</topic><topic>Eye movements</topic><topic>Latency</topic><topic>Saccadic eye movements</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rosset, Israel</creatorcontrib><creatorcontrib>Raveh, Eitan</creatorcontrib><creatorcontrib>Shimon, Assaf Ben</creatorcontrib><creatorcontrib>Anisimov, Vova</creatorcontrib><creatorcontrib>Ben‐Ami, Edmund</creatorcontrib><creatorcontrib>Kreitman, Rivka</creatorcontrib><creatorcontrib>Breakstone, Micha</creatorcontrib><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><jtitle>Acta ophthalmologica (Oxford, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rosset, Israel</au><au>Raveh, Eitan</au><au>Shimon, Assaf Ben</au><au>Anisimov, Vova</au><au>Ben‐Ami, Edmund</au><au>Kreitman, Rivka</au><au>Breakstone, Micha</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validation of a novel software‐based platform to extract oculometric measures</atitle><jtitle>Acta ophthalmologica (Oxford, England)</jtitle><date>2022-12</date><risdate>2022</risdate><volume>100</volume><issue>S275</issue><epage>n/a</epage><issn>1755-375X</issn><eissn>1755-3768</eissn><abstract>Purpose: Eye‐tracking systems are a valuable tool in the assessment of disorders by detecting eye movement abnormalities. However, current systems require lab settings, extraction of oculometric measures entails dedicated long sessions, and operation requires qualified personnel. Recently, a novel software‐based platform was developed, using a webcam, enabling the extraction of oculometric measures in a short test with seamless operation. The aim of this study was to validate this platform as compared with a validated eye‐tracker.
Methods: 82 participants (51 females, age range 21–88) were evaluated with a software‐based platform (NeuraLight, Israel) in a 15‐minute eye‐tracking test. Participants were presented with different stimuli for various tasks. During the test, data from a validated eye‐tracker (Tobii Pro, Sweden) were captured. Correlations between oculometric measures captured by both methods were calculated using Pearson correlation. Observable information on demographic data was measured using Fisher information matrix.
Results: Eye and gaze positions captured by the NeuraLight platform were highly correlated with eye‐tracker (r = 0.9–0.99, p < 0.01). Saccade and anti‐saccade latency, pro‐saccade and anti‐saccade error rates, position and velocity gain for all tasks were all highly correlated (r > 0.9, p < 0.01). Relative root mean square error of all measures in both methods was <0.1. Saccadic latency and fixation time were found to be in relation with participants' age.
Conclusions: NeuraLight platform was significantly correlated with a validated eye‐tracker, providing high accuracy for eye and gaze positions and oculometric measures. Relation between oculometric measures and age was established. The platform can be implemented for assessment of eye movements in practice. Future studies are needed to use the platform in various conditions.</abstract><cop>Malden</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/j.1755-3768.2022.0359</doi><tpages>1</tpages></addata></record> |
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| subjects | Age Eye movements Latency Saccadic eye movements Software |
| title | Validation of a novel software‐based platform to extract oculometric measures |
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