{"title":"ECG artifacts detection in noncardiovascular signals using Slope Sum Function and Teager Kaiser Energy","authors":"Shalini A. Rankawat, M. Rankawat, R. Dubey","doi":"10.1109/ICBAPS.2015.7292208","DOIUrl":"https://doi.org/10.1109/ICBAPS.2015.7292208","url":null,"abstract":"A new method for ECG artifacts detection from noncardiovascular physiological signals namely Electroencephalogram (EEG), Electrooculogram (EOG) and Electromyogram (EMG), without the need of any additional synchronous ECG channel, is being proposed. This ECG artifacts (R peaks) detection method uses Slope Sum Function and Teager Kaiser Energy operator with an adaptive threshold. The performance of algorithm has been evaluated on PhysioNet database of challenge 2014 and MIT BIH polysomnographic database. The algorithm has shown improved ECG artifacts detection results as compared to that of direct application of Teager Kaiser energy operator on noncardiovascular signals. The detection rates of ECG artifacts with the new method is 96.12 percent with FN rate of 3.88 percent and FP rate of 3.16 percent for PhysioNet database challenge 2014. For MIT BIH database the artifacts detection rate is 95.57 percent with FN rate of 4.44 percent and FP rate of 3.57 percent, which shows an excellent performance in ECG artifacts detection.","PeriodicalId":243293,"journal":{"name":"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129354949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Inter-subject variability of respiratory motion from 4D MRI","authors":"Ashrani Aizzuddin Abd Rahni, E. Lewis, K. Wells","doi":"10.1109/ICBAPS.2015.7292225","DOIUrl":"https://doi.org/10.1109/ICBAPS.2015.7292225","url":null,"abstract":"Respiratory motion affects image acquisition and also external beam radiotherapy (EBRT) treatment planning and delivery. Existing approaches for respiratory motion management are often based on a generic view of respiratory motion such as the general movement of organ, tissue or fiducials. This paper aims to present a more in depth analysis of respiratory motion based on 4D MRI, which can then be integrated into motion correction approaches in image acquisition or image based EBRT. In this paper we analyse the respiratory motion of organs for five volunteers on a per-organ basis, separately for each volunteer and together comparatively. We also compare with a separate study of respiratory motion for 20 patients. The motion extracted from 4D MRI on general was found to be consistent with what has been reported in literature and a similar process can be used in future to extract and quantify respiratory motion on a larger dataset.","PeriodicalId":243293,"journal":{"name":"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127208643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}