{"id":{"repo_id":"aston","oai_identifier":"oai:publications.aston.ac.uk:10681"},"canonical_url":"https://search.dev.ndltd.org/etd/aston/oai:publications.aston.ac.uk:10681","repository":{"repo_id":"aston","name":"Aston University","base_url":"https://publications.aston.ac.uk/cgi/oai2"},"display":{"title":"A novel entropy measure for analysis of the electrocardiogram","abstract":"There has been much recent research into extracting useful diagnostic features from the electrocardiogram with numerous studies claiming impressive results. However, the robustness and consistency of the methods employed in these studies is rarely, if ever, mentioned. Hence, we propose two new methods; a biologically motivated time series derived from consecutive P-wave durations, and a mathematically motivated regularity measure. We investigate the robustness of these two methods when compared with current corresponding methods. We find that the new time series performs admirably as a compliment to the current method and the new regularity measure consistently outperforms the current measure in numerous tests on real and synthetic data.","abstract_html":"There has been much recent research into extracting useful diagnostic features from the electrocardiogram with numerous studies claiming impressive results. However, the robustness and consistency of the methods employed in these studies is rarely, if ever, mentioned. Hence, we propose two new methods; a biologically motivated time series derived from consecutive P-wave durations, and a mathematically motivated regularity measure. We investigate the robustness of these two methods when compared with current corresponding methods. We find that the new time series performs admirably as a compliment to the current method and the new regularity measure consistently outperforms the current measure in numerous tests on real and synthetic data.","abstract_has_math":false,"creators":["Woodcock, Dan"],"institution":"Aston University","degree_name":"Ph.D.","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Nabney, Ian"],"committee_chairs":[],"committee_members":[],"year":2007,"date_issued":"2007-02","date_published":"2007-02","updated_at":"2026-07-24T01:01:19Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Nabney, Ian"]},{"key":"dc:creator","label":"Author","values":["Woodcock, Dan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2007-02"]},{"key":"dc:date.issued","label":"Date","values":["2007-02"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Aston University"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://publications.aston.ac.uk/id/eprint/10681/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Ph.D."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://publications.aston.ac.uk/id/eprint/10681/1/woodc2007_739513.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["There has been much recent research into extracting useful diagnostic features from the electrocardiogram with numerous studies claiming impressive results. However, the robustness and consistency of the methods employed in these studies is rarely, if ever, mentioned. Hence, we propose two new methods; a biologically motivated time series derived from consecutive P-wave durations, and a mathematically motivated regularity measure. We investigate the robustness of these two methods when compared with current corresponding methods. We find that the new time series performs admirably as a compliment to the current method and the new regularity measure consistently outperforms the current measure in numerous tests on real and synthetic data."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["A novel entropy measure for analysis of the electrocardiogram"]}]}],"canonical_facts":{"dc:contributor.advisor":["Nabney, Ian"],"dc:creator":["Woodcock, Dan"],"dc:date":["2007-02"],"dc:date.issued":["2007-02"],"dc:description.abstract":["There has been much recent research into extracting useful diagnostic features from the electrocardiogram with numerous studies claiming impressive results. However, the robustness and consistency of the methods employed in these studies is rarely, if ever, mentioned. Hence, we propose two new methods; a biologically motivated time series derived from consecutive P-wave durations, and a mathematically motivated regularity measure. We investigate the robustness of these two methods when compared with current corresponding methods. We find that the new time series performs admirably as a compliment to the current method and the new regularity measure consistently outperforms the current measure in numerous tests on real and synthetic data."],"dc:format":["application/pdf"],"dc:identifier.uri":["https://publications.aston.ac.uk/id/eprint/10681/1/woodc2007_739513.pdf"],"dc:publisher.institution":["Aston University"],"dc:relation.isreferencedby":["https://publications.aston.ac.uk/id/eprint/10681/"],"dc:title":["A novel entropy measure for analysis of the electrocardiogram"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["Ph.D."]},"updated_at":"2026-07-24T01:01:19Z"}