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.

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