Pregled bibliografske jedinice broj: 358516
Applicability of Qualitative ECG Processing to Wearable Computing
Applicability of Qualitative ECG Processing to Wearable Computing // Proceedings of the 5th International Workshop and Symposium on Wearable and Implanzable Body Sensor Networks / Zhang, Yuan-ting (ur.).
Hong Kong: Institute of Electrical and Electronics Engineers (IEEE), 2008. str. 133-136 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 358516 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Applicability of Qualitative ECG Processing to Wearable Computing
Autori
Bogunović, Nikola ; Šmuc, Tomislav
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 5th International Workshop and Symposium on Wearable and Implanzable Body Sensor Networks
/ Zhang, Yuan-ting - Hong Kong : Institute of Electrical and Electronics Engineers (IEEE), 2008, 133-136
Skup
5th International Workshop and Symposium on Wearable and Implantable Body Sensor Networks
Mjesto i datum
Hong Kong, Kina, 01.06.2008. - 03.06.2008
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
ECG processing; data mining; signal classification; wearable computing
Sažetak
Studies of ECG time-series properties and complexities are significant part of the research on the possibilities to automate ECG classification by a wearable body computer. Numerous statistical measures, as well as more recently introduced non-linear and complexity measures provide the basis for signal classification, prediction of events, and discovery of underlying systems and models expressing the observed heart dynamics. This paper presents qualitative signal discretization, based on persistent state trend definition. This transformation results in a compact symbolic sequence representation of the original time series. The information content of the transformed sequence is assessed using some of the classic signal complexity and similarity measures, adapted to the new representation. The presented methodology is applied to ECG time signals classification.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
036-0362980-1921 - Računalne okoline za sveprisutne raspodijeljene sustave (Srbljić, Siniša, MZO ) ( CroRIS)
098-0982560-2563 - Algoritmi strojnog učenja i njihova primjena (Gamberger, Dragan, MZOS ) ( CroRIS)
098-0982560-2565 - Postupci računalne inteligencije u mjernim sustavima (Marić, Ivan, MZOS ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Institut "Ruđer Bošković", Zagreb
