| | Category | EBED | P04 | Real Time Heart Rate Variability Analysis |
| | Abstract | Electrocardiogram(ECG) is commonly used for diagnosis of cardiac |
| | rhythm. Variation in the heart rate and beat to beat interval is indicated |
| | by Heart Rate Variability (HRV) analysis, which plays an important role |
| | in the diagnosis of cardiac status. Patients in intensive care require |
| | continuous monitoring; however, it is impractical for a human to analyze |
| | such a large quantity of data for the diagnosis. An embedded system |
| | for real-time HRV analysis is desired for a more efficient and accurate |
| | diagnosis. This study used a Shimmer wireless body sensor platform to |
| | detect ECG signals from the human body. A nonlinear energy method |
| | was used to detect the R peak of QRS, and HRV analysis was |
| | performed based on statistical measures. A MATLAB program was |
| | developed to compute R peak and HRV indexes. The proposed |
| | embedded system can be used for real time HRV analysis. |
| | Bibliography | https://www.hindawi.com/journals/cmmm/2012/219080/http://ieeexplore.i |
| | eee.org/document/6645866/ |