Abstract
Congestive Heart Failure (CHF) is a disease caused by the inability of the heart to supply the needs of the body in terms of oxygen and perfusion. Detection and diagnosis of CHF is difficult and requires a battery of tests, which include the electrocardiogram (ECG). Automated processing of the ECG signal and in particular heart rate variability (HRV) analysis holds great promise for diagnosis of CHF and more generally in assessing cardiac health, especially for personalized mobile health. However, recording the full 12-lead ECG is a relatively invasive procedure and for that reason it is of interest to determine what can be deduced from the much less intensive measurement of heart rate (RR interval) alone. In addition to calculating SDNN and, RMSSD, which when combined gave an accuracy of 78.8% with the Nearest Neighbour classifier. The best Renyi entropy result was an accuracy of 66.7% using Nearest Neighbour. Combining the best Renyi entropy results with SDNN and RMSSD led to an overall accuracy of 87.9% with sensitivity of 80% and specificity of 94.4%. In this work we have shown that applying Renyi entropy in addition to standard time domain measures identified CHF with higher accuracy than using time domain measures only. In addition, Renyi entropy exponents provide further information about the time signal characteristics that may be important in clinical decision making.
| Original language | English |
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| Title of host publication | Computing in cardiology 2016 |
| Place of Publication | United States |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 669-672 |
| Number of pages | 4 |
| Volume | 43 |
| ISBN (Electronic) | 9781509008957 |
| ISBN (Print) | 9781509008964 (Print of demand) |
| DOIs | |
| Publication status | Published - 01 Mar 2016 |
| Event | 43rd Computing in Cardiology Conference, CinC 2016 - Marriot Hotel and Simon Fraser University, Vancouver, Canada Duration: 11 Sept 2016 → 14 Sept 2016 https://web.archive.org/web/20160908015049/http://www.cinc2016.org/ (Conference website) http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7861973 (Conference proceedings - IEEE) |
Conference
| Conference | 43rd Computing in Cardiology Conference, CinC 2016 |
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| Country/Territory | Canada |
| City | Vancouver |
| Period | 11/09/16 → 14/09/16 |
| Other | Computing in Cardiology (formerly Computers in Cardiology) is an international scientific conference that has been held annually since 1974. CinC provides a forum for scientists and professionals from the fields of medicine, physics, engineering and computer science to discuss their current research in topics pertaining to computing in clinical cardiology and cardiovascular physiology. Attendees present and learn about leading-edge work at the interface of clinical practice, engineering, and basic research during three days of plenary, parallel, and poster sessions. |
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