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Article: Dynamic Bayesian Adjustment of Dwell Time for Faster Eye Typing

TitleDynamic Bayesian Adjustment of Dwell Time for Faster Eye Typing
Authors
KeywordsEye tracking
human computer interaction
eye typing
dwell time
motor disability
Issue Date2020
PublisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7333
Citation
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020, v. 28 n. 10, p. 2315-2324 How to Cite?
AbstractEye typing is a hands-free method of human computer interaction, which is especially useful for people with upper limb disabilities. Users select a desired key by gazing at it in an image of a keyboard for a fixed dwell time. There is a tradeoff in selecting the dwell time; shorter dwell times lead to errors due to unintentional selections, while longer dwell times lead to a slow input speed. We propose to speed up eye typing while maintaining low error by dynamically adjusting the dwell time for each letter based on the past input history. More likely letters are assigned shorter dwell times. Our method is based on a probabilistic generative model of gaze, which enables us to assign dwell times using a principled model that requires only a few free parameters. We evaluate our model on both able-bodied subjects and subjects with a spinal cord injury (SCI). Compared to the standard dwell time method, we find consistent increases in typing speed in both cases. e.g., 41.8% faster typing for able-bodied subjects on a transcription task and 49.5% faster typing for SCI subjects in a chatbot task. We observed more inter-subject variability for SCI subjects.
Persistent Identifierhttp://hdl.handle.net/10722/305867
ISSN
2021 Impact Factor: 4.528
2020 SCImago Journal Rankings: 1.093
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorPI, J-
dc.contributor.authorKoljonen, PA-
dc.contributor.authorHu, Y-
dc.contributor.authorSHI, BE-
dc.date.accessioned2021-10-20T10:15:28Z-
dc.date.available2021-10-20T10:15:28Z-
dc.date.issued2020-
dc.identifier.citationIEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020, v. 28 n. 10, p. 2315-2324-
dc.identifier.issn1534-4320-
dc.identifier.urihttp://hdl.handle.net/10722/305867-
dc.description.abstractEye typing is a hands-free method of human computer interaction, which is especially useful for people with upper limb disabilities. Users select a desired key by gazing at it in an image of a keyboard for a fixed dwell time. There is a tradeoff in selecting the dwell time; shorter dwell times lead to errors due to unintentional selections, while longer dwell times lead to a slow input speed. We propose to speed up eye typing while maintaining low error by dynamically adjusting the dwell time for each letter based on the past input history. More likely letters are assigned shorter dwell times. Our method is based on a probabilistic generative model of gaze, which enables us to assign dwell times using a principled model that requires only a few free parameters. We evaluate our model on both able-bodied subjects and subjects with a spinal cord injury (SCI). Compared to the standard dwell time method, we find consistent increases in typing speed in both cases. e.g., 41.8% faster typing for able-bodied subjects on a transcription task and 49.5% faster typing for SCI subjects in a chatbot task. We observed more inter-subject variability for SCI subjects.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7333-
dc.relation.ispartofIEEE Transactions on Neural Systems and Rehabilitation Engineering-
dc.rightsIEEE Transactions on Neural Systems and Rehabilitation Engineering. Copyright © Institute of Electrical and Electronics Engineers.-
dc.rights©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectEye tracking-
dc.subjecthuman computer interaction-
dc.subjecteye typing-
dc.subjectdwell time-
dc.subjectmotor disability-
dc.titleDynamic Bayesian Adjustment of Dwell Time for Faster Eye Typing-
dc.typeArticle-
dc.identifier.emailKoljonen, PA: kpa229@hku.hk-
dc.identifier.emailHu, Y: yhud@hku.hk-
dc.identifier.authorityHu, Y=rp00432-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TNSRE.2020.3016747-
dc.identifier.pmid32795970-
dc.identifier.scopuseid_2-s2.0-85092507365-
dc.identifier.hkuros328183-
dc.identifier.volume28-
dc.identifier.issue10-
dc.identifier.spage2315-
dc.identifier.epage2324-
dc.identifier.isiWOS:000578017200022-
dc.publisher.placeUnited States-

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