Abstract
This study presents the first successful preliminary attempt to directly investigate the interactions of power spectra of electrocardiography (ECG) and respiration signals of patients with type II diabetes by coherence analysis. Also the interactions comparing angiotensin converting enzyme (ACE) genotyping groups. ECG and Respiration signals were collected from 43 non-diabetic healthy subjects and 55 patients with type II diabetes in the United Arab Emirates. Coherence between two signals over different frequency bands (0-0.4 Hz) were calculated for very low frequency (VLF: 0.003-0.04 Hz), low frequency (LF: 0.04-0.15Hz) and high frequency (HF: 0.15-0.4 Hz). Overall coherence of ECG and Respiration in HF band is higher in control group than that in the diabetic patients group. A significant (p=0.0162 and p=0.001 after age correction) difference of coherence in the range of 0.15-4 Hz was found between the two groups. Significant HF results for genotyping ACE groups with (p=0.002) were reported after correction for age. The results could be useful in detecting cardiovascular complications to characterize why diabetes population has a high incidence of heart disease. The genotyping analysis could be used for personalizing the diagnosis.
| Original language | British English |
|---|---|
| Title of host publication | 2014 Middle East Conference on Biomedical Engineering, MECBME 2014 |
| Publisher | IEEE Computer Society |
| Pages | 346-348 |
| Number of pages | 3 |
| ISBN (Print) | 9781479947997 |
| DOIs | |
| State | Published - 2014 |
| Event | 2014 2nd Middle East Conference on Biomedical Engineering, MECBME 2014 - Doha, Qatar Duration: 17 Feb 2014 → 20 Feb 2014 |
Publication series
| Name | Middle East Conference on Biomedical Engineering, MECBME |
|---|---|
| ISSN (Print) | 2165-4247 |
| ISSN (Electronic) | 2165-4255 |
Conference
| Conference | 2014 2nd Middle East Conference on Biomedical Engineering, MECBME 2014 |
|---|---|
| Country/Territory | Qatar |
| City | Doha |
| Period | 17/02/14 → 20/02/14 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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