Respiratory and non-respiratory sinus arrhythmia: implications for heart rate variability

The quantity of blood arriving at the left side of the heart oscillates throughout the breathing cycle due to the mechanics of breathing. Neurally regulated fluctuations in the length of the heart period act to dampen oscillations of the left ventricular stroke volume entering the aorta. We have reported that stroke volume oscillations but not spectral frequency variability stroke volume measures can be used to estimate the breathing frequency. This study investigated with the same recordings whether heart period oscillations or spectral heart rate variability measures could function as estimators of breathing frequency. Continuous 270 s cardiovascular recordings were obtained from 22 healthy adult volunteers in the supine and upright postures. Breathing was recorded simultaneously. Breathing frequency and heart period oscillation frequency were calculated manually, while heart rate variability spectral maximums were obtained using heart rate variability software. These estimates were compared to the breathing frequency using the Bland–Altman agreement procedure. Estimates were required to be \±10% (95% levels of agreement). The 95% levels of agreement measures for the heart period oscillation frequency (supine: -27.7 to 52.0%, upright: -37.8 to 45.9%) and the heart rate variability spectral maximum estimates (supine: -48.7 to 26.5% and -56.4 to 62.7%, upright: -37.8 to 39.3%) exceeded 10%. Multiple heart period oscillations were observed to occur during breathing cycles. Both respiratory and non-respiratory sinus arrhythmia was observed amongst healthy adults. This observation at least partly explains why heart period parameters and heart rate variability parameters are not reliable estimators of breathing frequency. In determining the validity of spectral heart rate variability measurements we suggest that it is the position of the spectral peaks and not the breathing

Low Complexity All-Pass Based Polyphase Decimation Filters for ECG Monitoring

This paper presents a low complexity high efficiency decimation filter which can be employed in EletroCardioGram (ECG) acquisition systems. The decimation filter with a decimation ratio of 128 works along with a third order sigma delta modulator. It is designed in four stages to reduce cost and power consumption. The work reported here provides an efficient approach for the decimation process for high resolution biomedical data conversion applications by employing low complexity two-path all-pass based decimation filters. The performance of the proposed decimation chain was validated by using the MIT-BIH arrhythmia database and comparative simulations were conducted with the state of the art.