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One algorithm to ru...
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Andersson, RichardLund University,Lunds universitet,Kognitionsvetenskap,Filosofiska institutionen,Institutioner,Humanistiska och teologiska fakulteterna,Cognitive Science,Department of Philosophy,Departments,Joint Faculties of Humanities and Theology
(author)
One algorithm to rule them all? : An evaluation and discussion of ten eye movement event-detection algorithms
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2016-05-18
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Springer Science and Business Media LLC,2017
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LIBRIS-ID:oai:lup.lub.lu.se:784a92cf-a4aa-452f-9acd-faafd94366cd
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https://lup.lub.lu.se/record/784a92cf-a4aa-452f-9acd-faafd94366cdURI
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https://doi.org/10.3758/s13428-016-0738-9DOI
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Language:English
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Summary in:English
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Subject category:art swepub-publicationtype
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Subject category:ref swepub-contenttype
Notes
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Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eye-movement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from previous evaluations by considering a relatively large set of algorithms, multiple events, and data from both static and dynamic stimuli. The main conclusion is that current detectors of only fixations and saccades work reasonably well for static stimuli, but barely better than chance for dynamic stimuli. Differing results across evaluation methods make it difficult to select one winner for fixation detection. For saccade detection, however, the algorithm by Larsson, Nyström and Stridh (IEEE Transaction on Biomedical Engineering, 60(9):2484–2493,2013) outperforms all algorithms in data from both static and dynamic stimuli. The data also show how improperly selected algorithms applied to dynamic data misestimate fixation and saccade properties.
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Larsson, LinnéaLund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH(Swepub:lu)eit-lla
(author)
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Holmqvist, KennethLund University,Lunds universitet,Humanistlaboratoriet,Fakultetsgemensamma verksamheter,Humanistiska och teologiska fakulteterna,Lund University Humanities Lab,Units,Joint Faculties of Humanities and Theology(Swepub:lu)lucs-kho
(author)
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Stridh, MartinLund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH(Swepub:lu)tde-mst
(author)
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Nyström, MarcusLund University,Lunds universitet,Humanistlaboratoriet,Fakultetsgemensamma verksamheter,Humanistiska och teologiska fakulteterna,Lund University Humanities Lab,Units,Joint Faculties of Humanities and Theology(Swepub:lu)it-mny
(author)
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KognitionsvetenskapFilosofiska institutionen
(creator_code:org_t)
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In:Behavior Research Methods: Springer Science and Business Media LLC49:2, s. 616-6371554-3528
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