Title
Automated identification of ERP peaks through Dynamic Time Warping : an application to developmental dyslexia Automated identification of ERP peaks through Dynamic Time Warping : an application to developmental dyslexia
Author
Faculty/Department
Faculty of Medicine and Health Sciences
Publication type
article
Publication
Amsterdam ,
Subject
Biology
Human medicine
Source (journal)
Clinical neurophysiology. - Amsterdam
Volume/pages
120(2009) :10 , p. 1819-1827
ISSN
1388-2457
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Abstract
Objective This article proposes a method to automatically identify and label event-related potential (ERP) components with high accuracy and precision. Methods We present a framework, referred to as peak-picking Dynamic Time Warping (ppDTW), where a priori knowledge about the ERPs under investigation is used to define a reference signal. We developed a combination of peak-picking and Dynamic Time Warping (DTW) that makes the temporal intervals for peak-picking adaptive on the basis of the morphology of the data. We tested the procedure on experimental data recorded from a control group and from children diagnosed with developmental dyslexia. Results We compared our results with the traditional peak-picking. We demonstrated that our method achieves better performance than peak-picking, with an overall precision, recall and F-score of 93%, 86% and 89%, respectively, versus 93%, 80% and 85% achieved by peak-picking. Conclusion We showed that our hybrid method outperforms peak-picking, when dealing with data involving several peaks of interest. Significance The proposed method can reliably identify and label ERP components in challenging event-related recordings, thus assisting the clinician in an objective assessment of amplitudes and latencies of peaks of clinical interest.
E-info
https://repository.uantwerpen.be/docman/iruaauth/5a3154/bf5f615ddfb.pdf