Signal Quality-Aware Frequency Demodulation-Based ECG-Derived Respiration Rate Estimation Method With Reduced False Alarms

Abstract

In this letter, we present an automated signal quality-aware frequency demodulation (FD)-based electrocardiogram (ECG)-derived respiration rate (FD-ECG-derived RR) estimation method with reduced false alarms under noisy ECG signals, which are unavoidable in resting and ambulatory health monitoring applications. The proposed FD-ECG-derived RR estimation method includes three major steps of signal quality checking to discard noisy ECG signals, respiratory-induced frequency variation (RIFV) waveform extraction using a frequency demodulation envelope detector by determining peaks of the derivative ECG waveform using a simple R-peak detector, and respiration rate estimation using the Fourier magnitude spectrum of the extracted RIFV waveform. On the standard Capnobase and BIDMC databases, the proposed FD-ECG-derived RR estimation method provides promising results with mean absolute error values of 5.01 and 5.37 breaths/min, respectively. The signal quality-aware RR estimation method used can reduce false alarm rate of 84.85 ${\%}$ by discarding noisy ECG signals with quality assessment accuracy of 85.25 ${\%}$ . The proposed simplistic method having lightweight signal processing approaches makes it suitable for real-time health monitoring applications.