2026-09-19T19:48:09Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/287262022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Richard Cohen.
Dosani, Adnan, 1982-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2005-09-27T18:00:18Z
2005-09-27T18:00:18Z
2004
2004
http://hdl.handle.net/1721.1/28726
59554446
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (leaves 93-96).
The goal of our thesis was to investigate if P-wave and PQ segment alternans can be used to detect and predict Paroxysmal Atrial Fibrillation (PAF) from an Electrocardiogram (ECG). The work involved implementing an algorithm for computing alternans information for a region of ECG, applying the algorithm to derive P-wave and PQ segment alternans information, and analyzing data generated for normal and PAF ECGs for evidence of any distinguishable predictive characteristics. Based on analysis of total 80 patient records (35 normal and 45 PAF) with validation on 30 records randomly selected from those (achieving c-indexes between 0.66 and 0.70), we concluded that alternans can potentially be a useful predictor for PAF.
by Adnan Dosani.
S.M.
96 leaves
3876089 bytes
3887201 bytes
application/pdf
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en_US
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Exploring alternans characteristics of electrocardiogram for prediction of Paroxysmal Atrial Fibrillation
Thesis
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<Abstract>The goal of our thesis was to investigate if P-wave and PQ segment alternans can be used to detect and predict Paroxysmal Atrial Fibrillation (PAF) from an Electrocardiogram (ECG). The work involved implementing an algorithm for computing alternans information for a region of ECG, applying the algorithm to derive P-wave and PQ segment alternans information, and analyzing data generated for normal and PAF ECGs for evidence of any distinguishable predictive characteristics. Based on analysis of total 80 patient records (35 normal and 45 PAF) with validation on 30 records randomly selected from those (achieving c-indexes between 0.66 and 0.70), we concluded that alternans can potentially be a useful predictor for PAF.</Abstract>
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