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EnglishNarcolepsy with cataplexy is a severe lifelong disorder characterized, among the others, by sudden loss of bilateral face muscle tone triggered by emotions (cataplexy). The current approach followed by neurologists for the classification of such abnormal motor behavior is based on a completely manual analysis of video recordings of patients undergoing emotional stimulation made on-site by medical specialists. With the double aim of supporting neurologists in such a delicate task and facilitating the experience of patients, avoiding them to conduct video recordings at hospitals, in this position paper we advocate the use of automatic video content analysis techniques and mobile multimedia technologies in order to solve the problem. In particular, we propose a medical tool, built on top a general and extensible framework for the effective and efficient management of video collections, that allows patients (i.e., video producers) to record videos through the use of smart devices and neurologists (i.e., video consumers) to automatically identify the presence of the disease by means of a user friendly GUI. Preliminary results achieved on the recognition of one of most recurrent cataplexy motor behaviours pattern (namely, ptosis) and conducted on real data demonstrate the e!effectiveness of the proposed solution and encourage further investigations in this direction.
| Titolo: | Towards Automatic Recognition of Narcolepsy with Cataplexy |
| Autore/i: | ilaria bartolini; andrea di luzio |
| Autore/i Unibo: | |
| Anno: | 2017 |
| Titolo del libro: | Proceedings of the 15th International Conference on Advances in Mobile Computing & Multimedia |
| Pagina iniziale: | 97 |
| Pagina finale: | 101 |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1145/3151848.3151875 |
| Abstract: | Narcolepsy with cataplexy is a severe lifelong disorder characterized, among the others, by sudden loss of bilateral face muscle tone triggered by emotions (cataplexy). The current approach followed by neurologists for the classification of such abnormal motor behavior is based on a completely manual analysis of video recordings of patients undergoing emotional stimulation made on-site by medical specialists. With the double aim of supporting neurologists in such a delicate task and facilitating the experience of patients, avoiding them to conduct video recordings at hospitals, in this position paper we advocate the use of automatic video content analysis techniques and mobile multimedia technologies in order to solve the problem. In particular, we propose a medical tool, built on top a general and extensible framework for the effective and efficient management of video collections, that allows patients (i.e., video producers) to record videos through the use of smart devices and neurologists (i.e., video consumers) to automatically identify the presence of the disease by means of a user friendly GUI. Preliminary results achieved on the recognition of one of most recurrent cataplexy motor behaviours pattern (namely, ptosis) and conducted on real data demonstrate the e!effectiveness of the proposed solution and encourage further investigations in this direction. |
| Data stato definitivo: | 26-feb-2018 |
| Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |
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