Effects of an eight-day space flight on microvibration and physiological tremor

Cardiorespiratory Interaction and Autonomic Sleep Quality Improve during Sleep in Beds Made from Pinus cembra (Stone Pine) Solid Wood

Cardiorespiratory interactions (CRIs) reflect the mutual tuning of two important organismic oscillators—the heartbeat and respiration. These interactions can be used as a powerful tool to characterize the self-organizational and recreational quality of sleep. In this randomized, blinded and cross-over design study, we investigated CRIs in 15 subjects over a total of 253 nights who slept in beds made from different materials. One type of bed, used as control, was made of melamine faced chipboard with a wood-like appearance, while the other type was made of solid wood from stone pine (Pinus cembra). We observed a significant increase of vagal activity (measured by respiratory sinus arrhythmia), a decrease in the heart rate (as an indicator of energy consumption during sleep) and an improvement in CRIs, especially during the first hours of sleep in the stone pine beds as compared to the chipboard beds. Subjective assessments of study participants’ well-being in the morning and sub-scalar assessments of their intrapsychic stability were significantly better after they slept in the stone pine bed than after they slept in the chipboard bed. Our observations suggest that CRIs are sensitive to detectable differences in indoor settings that are relevant to human health. Our results are in agreement with those of other studies that have reported that exposure to volatile phytochemical ingredients of stone pine (α-pinene, limonene, bornyl acetate) lead to an improvement in vagal activity and studies that show a reduction in stress parameters upon contact with solid wood surfaces.

Heart Rhythm Analyzed via Shapelets Distinguishes Sleep From Awake

Automatically determining when a person falls asleep from easily available vital signals is important, not just for medical applications but also for practical ones, such as traffic safety or smart homes. Heart dynamics and respiration cycle couple differently during sleep and awake. Specifically, respiratory modulation of heart rhythm or respiratory sinus arrhythmia (RSA) is more prominent during sleep, as both sleep and RSA are connected to strong vagal activity. The onset of sleep can be recognized or even predicted as the increase of cardio-respiratory coupling. Here, we employ this empirical fact to design a method for detecting the change of consciousness status (sleep/awake) based only on heart rate variability (HRV) data. Our method relies on quantifying the (self)similarity among shapelets - short chunks of HRV time series - whose "shapes" are related to the respiration cycle. To test our method, we examine the HRV data of 75 healthy individuals recorded with microsecond precision. We find distinctive patterns stable across age and sex, that are not only indicative of sleep and awake, but allow to pinpoint the change from awake to sleep almost immediately. More systematic analysis along these lines could lead to a reliable prediction of sleep.

Dynamical disentanglement in an analysis of oscillatory systems: an application to respiratory sinus arrhythmia

We develop a technique for the multivariate data analysis of perturbed self-sustained oscillators. The approach is based on the reconstruction of the phase dynamics model from observations and on a subsequent exploration of this model. For the system, driven by several inputs, we suggest a dynamical disentanglement procedure, allowing us to reconstruct the variability of the system's output that is due to a particular observed input, or, alternatively, to reconstruct the variability which is caused by all the inputs except for the observed one. We focus on the application of the method to the vagal component of the heart rate variability caused by a respiratory influence. We develop an algorithm that extracts purely respiratory-related variability, using a respiratory trace and times of R-peaks in the electrocardiogram. The algorithm can be applied to other systems where the observed bivariate data can be represented as a point process and a slow continuous signal, e.g. for the analysis of neuronal spiking. This article is part of the theme issue 'Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences'.

Dynamics of Vagal Activity Due to Surgery and Subsequent Rehabilitation

Background

Vagal activity is critical for maintaining key body functions, including the stability of inflammatory control. Its weakening, such as in the aftermatch of a surgery, leaves the body vulnerable to diverse inflammatory conditions, including sepsis.

Methods

Vagal activity can be measured by the cardiorespiratory interaction known as respiratory sinus arrhythmia or high-frequency heart-rate variability (HRV). We examined the vagal dynamics before, during and after an orthopedic surgery. 39 patients had their HRV measured around the period of operation and during subsequent rehabilitation. Measurements were done during 24 h circadian cycles on ten specific days. For each patient, the circadian vagal activity was calculated from HRV data.

Results

Our results confirm the deteriorating effect of surgery on vagal activity. Patients with stronger pre-operative vagal activity suffer greater vagal withdrawal during the peri-operative phase, but benefit from stronger improvements during post-operative period, especially during the night. Rehabilitation seems not only to efficiently restore the vagal activity to pre-operative level, but in some cases to actually improve it.

Discussion

Our findings indicate that orthopedic rehabilitation has the potential to strengthen the vagal activity and hence boost inflammatory control. We conclude that providing a patient with a vagal reinforcement procedure prior to the surgery (“pre-habilitation”) might be a beneficial strategy against post-operative complications. The study also shows the clinical usefulness of quantifying the cardiorespiratory interactions.

Investigation of a Micro-test for Circulatory Autonomic Nervous System Responses

Aims and Objectives: The autonomic nervous system plays an important role in homeostasis and organismic recreation, control of immune function, inflammation, and bone growth. It also regulates blood pressure and orthostasis via vagal and sympathetic pathways. Besides recording of heart rate variability (HRV), which characterizes medium (1–5 min) and long term (circadian) autonomic tone or modulation, no gentle tests of short-term autonomic reactivity and control are available. In 1976 Nogier described a short time cardiovascular response (“Réflexe Auriculo Cardiaque”, RAC) which could be used to investigate short term autonomic reactions without changing system characteristics and thus being repeatable in short intervals. In this paper, we investigated the possible application of the Nogier reaction as a micro-test for the identification of a disturbed sensitivity or reactivity of the autonomic nervous system.

Methods: We statistically analyzed cardiovascular signals derived during the application of small repeated stimuli utilizing methods of signal averaging to characterize the physiological background. Specifically, the Nogier reaction was investigated using simultaneous recordings of ECG, pulse waves, and respiration.

Results: Significant fast (delay 1–5 s) and slower (delay 6–12 s) cardio-autonomic responses to different stimuli which characterize short term were observed. From time characteristics and type of signals where they occur we deduce that fast changes observed in heart rate are vagal reactions to the small stimuli whereas slower changes observed in pulse waves stem from sympathetic nervous system responses.

Conclusions: The investigated autonomic micro-test opens the possibility to differentially investigate both limbs of the autonomic nervous system with minimal stimuli. It can be performed within seconds and does not change the set point of the system in opposition to less subtle tests such as Valsalva maneuver. Therefore, it is well-suited for quick, repeated measurements of autonomic nervous system reactivity.

In vivo cardiac phase response curve elucidates human respiratory heart rate variability

Recovering interaction of endogenous rhythms from observations is challenging, especially if a mathematical model explaining the behaviour of the system is unknown. The decisive information for successful reconstruction of the dynamics is the sensitivity of an oscillator to external influences, which is quantified by its phase response curve. Here we present a technique that allows the extraction of the phase response curve from a non-invasive observation of a system consisting of two interacting oscillators--in this case heartbeat and respiration--in its natural environment and under free-running conditions. We use this method to obtain the phase-coupling functions describing cardiorespiratory interactions and the phase response curve of 17 healthy humans. We show for the first time the phase at which the cardiac beat is susceptible to respiratory drive and extract the respiratory-related component of heart rate variability. This non-invasive method for the determination of phase response curves of coupled oscillators may find application in many scientific disciplines.