Characterization of the autonomic nervous system response in hyperbaric environments
- Autores: Alberto Hernando Sanz
- Directores de la Tesis: María Dolores Peláez Coca (dir. tes.), Eduardo Gil Herrando (dir. tes.)
- Lectura: En la Universidad de Zaragoza ( España ) en 2021
- Idioma: español
- Programa de doctorado: Programa de Doctorado en Ingeniería Biomédica por la Universidad Politécnica de Catalunya y la Universidad de Zaragoza
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- Resumen
This dissertation focuses on the study of the Autonomic Nervous System (ANS) response in hyperbaric environments. Hyperbaric environments are those scenarios in which atmospheric pressure increases and this increase in pressure produces changes in the cardio-respiratory system of the subject to maintain the homeostasis. These changes are reflected in the ANS, whose response can be measured in a non-invasive way with the Heart Rate Variability (HRV), extracted from the electrocardiogram (ECG) or with the Pulse Rate Variability (PRV), extracted from the photoplethysmogram (PPG). The description of the hyperbaric environments, the ANS activity, the relationship between them and how the ANS response can be measured through ECG and PPG signals can be found in Chapter 1.
In Chapter 2, to corroborate if PPG signal provides the same information in terms of ANS response than ECG signal, both signals were recorded for subjects inside a hyperbaric chamber when the atmospheric pressure varied from 1 atm to 3 atm and 5 atm and the coming back to 3 and 1 atm. The correlation and statistical analysis between time and frequency domain parameters extracted from both signals demonstrates that PRV can be considered as a surrogate measurement of HRV inside a hyperbaric chamber. This makes PPG a signal to be considered in hyperbaric environments, since its sensor is cheaper and easier to place than ECG electrodes (especially under the water), and PPG can estimate some parameters, as the oxygen saturation, than ECG cannot. Also a characterization of how the ANS reacts to pressure changes and the time spent in the hyperbaric environment is done with ECG and PPG parameters, increasing those related with the parasympathetic system when the pressure is high and decreasing the heart rate and the parameters related with the sympathetic system when more time is spent inside the chamber.
Respiration plays an important role in hyperbaric environments, so it is important to include respiratory information in the HRV/PRV analysis, since it has been shown that changes in the respiratory pattern could alter the interpretation of the ANS response. Therefore, once that PPG signal has been proved as an interesting signal to consider in hyperbaric environments, in Chapter 3 a study about the respiratory rate estimation from different locations of the PPG sensor is performed. To do that, the respiratory signal together with finger and forehead PPG were recorded from 35 subjects while breathing spontaneously, and during controlled respiration experiments at a constant rate from 0.1 Hz to 0.6 Hz, in 0.1 Hz steps. Four PPG derived respiratory (PDR) signals were extracted from each one of the recorded PPG signals: pulse rate variability (PRV), pulse width variability (PWV), pulse amplitude variability (PAV) and the respiratory-induced intensity variability (RIIV). Respiratory rate was estimated from each one of the 4 PDR signals for both PPG sensor locations. Results suggest that: i) respiratory rate estimation is better at lower rates (0.4 Hz and below); ii) the signals recorded at the finger are better than those at the forehead to estimate respiratory rate; iii) it is better not to include RIIV signal to estimate the respiratory rate.
Following with the PPG signal, not only PRV contains information about the ANS response. Also, PPG morphology can provide a great amount of information about vascular assessment or arterial compliance, since pulse pressure propagation in arteries causes alterations in blood volume and therefore changes in the PPG pulse shape. That is the reason why, in Chapter 4, a new algorithm to decompose the PPG pulse into two waves related with the systolic and the diastolic peaks is presented. The first wave is obtained concatenating the up-slope from the beginning to the first maximum with itself flipped horizontally. The second wave is modelled by a lognormal curve, adjusting its maximum to the diastolic peak. From these two waves, the amplitude, the time instant, the width, the area and some ratios are extracted. This method is applied in a hyperbaric chamber dataset to identify alterations in the morphology of the PPG pulse due to the exposure of the subjects to different pressures. Results of the time and width of the wave related with the systolic peak point out to a vasoconstriction when the pressure increases, probably due to an activation of the sympathetic system on the blood vessels. Results of the time and width of the wave related with the diastolic peak reflect the vasoconstriction but also a dependency with the pulse-to-pulse interval. Therefore this methodology allows to extract a great set of parameters related with the PPG morphology that are affected by the change of pressure in hyperbaric environments.
In Chapters 2 and 4, the ANS response is studied inside a hyperbaric chamber, where the pressure varies. However, there are many variables that could affect the body's cardiovascular response during diving, such as diver body position, physical activity, water temperature, breathing with a scuba mouthpieces and more. This is the reason why in Chapter 5 the ANS response is studied in three different hyperbaric environments: inside a hyperbaric chamber, where only the pressure varied; during a controlled dive in the sea, where the pressure changed but the effects of other factors were minimized; and during an uncontrolled dive in a reservoir, where more factors differed from baseline to immersion stage. A comparison of the HRV features between the two stages (baseline and immersion) in each dataset is carried out to study how these factors related to scuba diving activity affect the ANS response. To do this comparison, instead of the classic frequency methods, the Principal Dynamic Mode (PDM) and the Orthogonal Subspace Projection (OSP) methods are used to account for linear and non-linear interactions and to deal with the respiratory component that could affect the ANS response, respectively. OSP results indicate that most of the variation in the heart rate variability cannot be described by changes in the respiration, so changes in ANS response can be assigned to other factors. Time domain parameters reflect vagal activation in the hyperbaric chamber and in the controlled dive because of the effect of pressure. In the uncontrolled dive, sympathetic activity seems to be dominant, due to the effects of other factors such as physical activity, the challenging environment, and the influence of breathing through the scuba mask during immersion. In summary, a careful description of the changes in all the possible factors that could affect the ANS response between baseline and immersion stages in hyperbaric environments is performed for better explanation of the results.
