| DOI | Trouver le DOI : https://doi.org/10.1109/SAS58821.2023.10253976 |
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| Auteur | Rechercher : Kunz, Manuela1; Rechercher : Syed, Arsalan1; Rechercher : Fraser, Kathleen C.1; Rechercher : Wallace, Bruce; Rechercher : Goubran, Rafik; Rechercher : Knoefel, Frank; Rechercher : Thomas, Neil |
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| Affiliation | - Conseil national de recherches du Canada. Technologies numériques
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| Bailleur de fonds | Rechercher : NSERC; Rechercher : AGE-WELL NCE Inc.; Rechercher : Bruyère Research Institute |
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| Format | Texte, Article |
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| Conférence | 2023 IEEE Sensors Applications Symposium (SAS), July 18-20, 2023, Ottawa, ON, Canada |
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| Sujet | webcam-based eye-tracking; eye gaze; remote monitoring system; facial landmarks; dementia; cognitive assessment |
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| Résumé | The detection and monitoring of cognitive decline has emerged as an important research topic as the global population ages. Here, we present work towards the goal of using a webcam as a low-cost and non-invasive sensor to detect oculomotor changes associated with prodromal or early dementia. Specifically, we implement a method of 3D gaze tracking to account for natural head movement during the data collection. In a user study, we show that this method decreases gaze estimation error in a fixation task by 11 %, when compared with a standard 2D method. Performance improvements are greater in the horizontal direction than vertical direction, indicating the predominance of horizontal head movements in our users. Correcting for naturalistic head movements will be critical in the deployment of this technology, particularly in older user populations. |
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| Date de publication | 2023-07-18 |
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| Maison d’édition | IEEE |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | 703a41b9-e640-4b01-a9fa-37cca7e0c0d7 |
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| Enregistrement créé | 2023-09-26 |
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| Enregistrement modifié | 2023-09-26 |
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