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Rehouma, Haythem; Noumeir, Rita; Jouvet, Philippe; Bouachir, Wassim et Essouri, Sandrine (2017). A computer vision method for respiratory monitoring in intensive care environment using RGB-D cameras. Dans Proceedings of the Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA 2017). Montréal, Canada : IEEE Xplore Digital Library.
Fichier(s) associé(s) à ce document :| PDF - IPTA-VERSION-WASSIM_ (003).pdf |
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| Catégorie de document : | Communications dans des actes de congrès/colloques |
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| Évaluation par un comité de lecture : | Oui |
| Étape de publication : | Publié |
| Résumé : | This paper presents a novel computer vision method to measure the breathing pattern in intensive care environment. The proposed system uses depth information captured by two RGB-D cameras in order to reconstruct a 3D surface of a patient's torso with a high spatial coverage. The optimal positioning for the sensors is a key step to perform an accurate 3D reconstruction without interfering with patient care. In this context, our hardware setup meets the clinical requirements while allowing accurate estimation of respiratory parameters including respiratory rate, tidal volume and inspiratory time. Our system provides the motion information not only for the top of the torso surface but also for its both lateral sides. Our method was tested in an environment designed for critically ill children, where it was compared to the gold standard method currently used in intensive care units. The performed experiments yielded high accuracy and showed significant agreement with gold standard method. |
| Adresse de la version officielle : | https://ieeexplore.ieee.org/document/8310155 |
| Déposant: | Bouachir, Wassim |
| Responsable : | Wassim Bouachir |
| Dépôt : | 11 oct. 2017 18:28 |
| Dernière modification : | 13 janv. 2020 16:19 |
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