| Autor: |
Greene BR; School of Electrical, Electronic & Mechanical Engineering, University College Dublin, Ireland. barry.greene@ee.ucd.ie, de Chazal P, Boylan GB, Connolly S, Reilly RB |
| Jazyk: |
angličtina |
| Zdroj: |
IEEE transactions on bio-medical engineering [IEEE Trans Biomed Eng] 2007 Apr; Vol. 54 (4), pp. 673-82. |
| DOI: |
10.1109/TBME.2006.890137 |
| Abstrakt: |
A method for the detection of seizures in the newborn using the electrocardiogram (ECG) signal is presented. Using a database of eight recordings, a method was developed for automatically annotating each 1-min epoch as "nonseizure" or "seizure". The system uses a linear discriminant classifier to process 41 heartbeat timing interval features. Performance assessment of the method showed that on a patient-specific basis an average accuracy of 70.5% was achieved in detecting seizures with associated sensitivity of 62.2% and specificity of 71.8%. On a patient-independent basis the average accuracy was 68.3% with sensitivity of 54.6% and specificity of 77.3%. Shifting the decision threshold for the patient-independent classifier allowed an increase in sensitivity to 78.4% at the expense of decreased specificity (51.6%), leading to increased false detections. The results of our ECG-based method are comparable with those reported for EEG-based neonatal seizure detection systems and offer the benefit of an easier acquisition methodology for seizure detection. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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