Preserved parasympathetic cardiac innervation after atrioventricular node modification: evidence from circle maps of respiratory sinus arrhythmia

Respiratory modulation of the heart rate: A potential biomarker of cardiorespiratory function in human

In recent decade, wearable digital devices have shown potentials for the discovery of novel biomarkers of humans' physiology and behavior. Heart rate (HR) and respiration rate (RR) are most crucial bio-signals in humans' digital phenotyping research. HR is a continuous and non-invasive proxy to autonomic nervous system and ample evidence pinpoints the critical role of respiratory modulation of cardiac function. In the present study, we recorded longitudinal (7 days, 4.63 ± 1.52) HR and RR of 89 freely behaving human subjects (Female: 39, age 57.28 ± 5.67, Male: 50, age 58.48 ± 6.32) and analyzed their dynamics using linear models and information theoretic measures. While HR's linear and nonlinear characteristics were expressed within the plane of the HR-RR directed flow of information (HR→RR - RR→HR), their dynamics were determined by its RR→HR axis. More importantly, RR→HR quantified the effect of alcohol consumption on individuals' cardiorespiratory function independent of their consumed amount of alcohol, thereby signifying the presence of this habit in their daily life activities. The present findings provided evidence for the critical role of the respiratory modulation of HR, which was previously only studied in non-human animals. These results can contribute to humans' phenotyping research by presenting RR→HR as a digital diagnosis/prognosis marker of humans' cardiorespiratory pathology.

Spinal genesis of Mayer waves

Variability in cardiovascular spectra was first described by Stephan Hales in 1733. Traube and Hering initially noted respirophasic variation of the arterial pressure waveform in 1865 and Sigmund Mayer noted a lower frequency oscillation of the same in anesthetized rabbits in 1876. Very low frequency oscillations were noted by Barcroft and Nisimaru in 1932, likely representing vasogenic autorhythmicity. While the origins of Traube Hering and very low frequency oscillatory variability in cardiovascular spectra are well described, genesis mechanisms and functional significance of Mayer waves remain in controversy. Various theories have posited baroreflex and central supraspinal mechanisms for genesis of Mayer waves. Several studies have demonstrated the persistence of Mayer waves following high cervical transection, indicating a spinal capacity for genesis of these oscillations. We suggest a general tendency for central sympathetic neurons to oscillate at the Mayer wave frequency, the presence of multiple Mayer wave oscillators throughout the brainstem and spinal cord, and possible contemporaneous genesis by baroreflex and vasomotor mechanisms.

Poincaré plot analysis for pulse interval extracted from non-contact photoplethysmography

An analysis of pulse-to-pulse interval (PPI) derived from non-contact photoplethysmography (PPG) is performed using the Poincaré plot technique. Eleven healthy volunteers participated in a protocol utilising both spontaneous and paced breathing methodologies with a customised non-contact PPG system to obtain adequate quality signals for a distance of 80mm between source and detector. An adaptive trough-searching algorithm (ATSA) is developed to extract the PPI which is effective in the presence of artefact during non-contact PPG measurement. A Poincaré plot for each 5 minute period of the protocol shows significant pattern differences between spontaneous and paced breathing measurements. Geometric parameters extracted from the Poincaré plot are shown to be sensitive to breathing interval changes and are a useful indicator for the variation of pulse rate variability measured using non-contact PPG.

Online cardiac arrhythmia classification by means of circle maps analysis implemented on an intelligent miniaturized sensor

The intermittent occurrence of cardiac arrhythmias like e.g. atrial fibrillation hampers their diagnosis and hence the treatment. Since persons suffering from atrial fibrillation are known to have a remarkable increased risk of stroke the diagnosis of atrial fibrillation is a matter of great importance. Easy and comfortable to use long term ECG recording systems capable of online arrhythmia classification might help to solve this problem. We developed an intelligent, miniaturized, and wireless networking sensor which allows lossless local data recordings up to 4 GB. With its outer dimensions of 20mm per rim and less than 15g of weight including the Lithium-Ion battery our modular designed sensor node is thoroughly capable of up to eight channel recordings with 8 kHz sample rate each and provides sufficient computational power for online digital signal processing. For online arrhythmia classification we will record one ECG channel and 3-axis accelerometer data with 512 Hz each, the later being used for activity classification based artifact identification. We adapted our recently developed circle maps analysis of short term heart rate variation to run on this miniaturized intelligent sensor powered by the Texas Instruments MSP430 microcontroller derivate F1611. With this configuration we started to evaluate the cardiac arrhythmia classification in long term ECG recordings.