http://www.cnr.it/ontology/cnr/individuo/prodotto/ID282402
Detecting Obstructive Sleep Apnea events in a realtime mobile monitoring system through automatically extracted sets of rules (Contributo in atti di convegno)
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- Detecting Obstructive Sleep Apnea events in a realtime mobile monitoring system through automatically extracted sets of rules (Contributo in atti di convegno) (literal)
- Anno
- 2013-01-01T00:00:00+01:00 (literal)
- Alternative label
Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro (2013)
Detecting Obstructive Sleep Apnea events in a realtime mobile monitoring system through automatically extracted sets of rules
in the 15th IEEE International Conference on e-Health Networking, Application and Services (Healthcom 2013, Lisbon, Portugal, 9 -12 Ottobre 2013
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro (literal)
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- Proceedings of the 15th IEEE International Conference on e-Health Networking, Application and Services (Healthcom 2013), Lisbon, Portugal, pp. 16-20, IEEE, 2013 (literal)
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- ICAR - CNR sede di Npoli (literal)
- Titolo
- Detecting Obstructive Sleep Apnea events in a realtime mobile monitoring system through automatically extracted sets of rules (literal)
- Abstract
- Performing detection and real-time monitoring of Obstructive Sleep Apnea (OSA) is a significant healthcare task. An easy, cheap, and mobile approach to monitor patients with OSA is proposed here. It gathers data from a patient by a single-channel ECG, and offline automatically extracts knowledge about that patient as a set of IF...THEN rules containing Heart Rate Variability (HRV) parameters. These rules are then used in the real-time mobile monitoring system: ECG data is collected by a wearable sensor, sent to a mobile device, and processed online to compute HRV-related parameter values. If a rule is activated by those values, the system produces an alarm. A literature database of OSA patients has been used to test the approach. (literal)
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