Amplitude Modulation Approach for Real-Time Algorithms of ECG-Derived Respiration

Abstract

This work presents the development of an ECG-Derived Respiration (EDR) methodology based on the amplitude modulation approach. It allows to redefine actual methodologies in order to obtain a continuous EDR signal with high correlations and the small delay between EDR and respiration activity. Two algorithms are implemented: one of them using the amplitude modulation of the R-peak (EDRAM) and another one applying a band-pass filter in the bandwidth of respiration. Unlike other techniques in literature, conventional low order filters are applied without sacrifice of correlation factor (0.76 and 0.67) and a minimum delay of 0.27s (with EDRAM) in a $sim$6s cycle. A robustness test was performed, and it shows a noise tolerance of up to 20% of the maximum value before its correlation factor drops considerably. The application into a wearable sensor was successfully implemented. The two methodologies proposed show advantages like real-time processing and robustness under certain noises. The proposed AM perspective supports the use of both algorithms for typical applications with high efficiency, low computational cost and ease of implementation. These characteristics result in a technique that facilitates the development of wearable systems, and to increase the information of actual databases.