Abstract
Major complications such as cardiac death and cardiac autonomic neuropathy are caused by diabetic autonomic neuropathy. Heart Rate Variability (HRV) analysis has shown to detect variations in the autonomic balance of heart rate and is useful for early detection of autonomic dysfunction. This study presents the outcome of HRV analysis of short ECG recordings taken from nondiabetic and type 2 diabetes patients, applying Poincaré plot indices represented by short term variation (SD1), long term variation (SD2) and complex correlation (CCM) measure which measures the temporal dynamics, for early detection of cardiac autonomic neuropathy. SD1 and the ratio SD1/SD2 were found to be significantly lower in type 2 diabetes patients than the control group. The highest discriminatory power was observed with CCM, indicating the advantage of using a dynamic measure for HRV rather than the static Poincaré plot indices. SD1 and CCM could be markers for CVD risk in type 2 diabetic patients.
Original language | English |
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Title of host publication | Proceedings of the 2014 Middle East Conference on Biomedical Engineering (MECBME) |
Place of Publication | United States |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 368-370 |
Number of pages | 3 |
ISBN (Print) | 978147994799714 |
DOIs | |
Publication status | Published - 2014 |
Event | 2014 Middle East Conference on Biomedical Engineering (MECBME) - Texas A&M University at Qatar, Doha, Qatar Duration: 17 Feb 2014 → 20 Feb 2014 |
Conference
Conference | 2014 Middle East Conference on Biomedical Engineering (MECBME) |
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Country/Territory | Qatar |
City | Doha |
Period | 17/02/14 → 20/02/14 |