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Typical waveforms used for the simulation of pressure and volume-controlled ventilation in medical ventilators have been extensively studied in the literature. The majority of simulation studies reported employ the step pattern or ramp pattern to model the pressure and flow variations in pressure/volume-controlled ventilation. It was observed that the above waveforms tend to add to the discomfort level of patients due to the presence of jerks in derivatives of pressure/flow variations; the pressure/flow variation of air and oxygen mixture should be smooth so that the patient discomfort is kept at a minimal level. To overcome the above-mentioned drawback, a careful study of the flow/pressure simulation using a cycloidal pattern during the inhalation and exhalation phases of the breath cycle was proposed and investigated in this work. Based on transient analysis of the pressure variation simulation, it was observed that the air and oxygen mixture delivered to the patient was relatively jerk-free due to the finite values of first and second-order derivatives of pressure/flow curves. Mathematical models of the proposed simulation study of the cycloidal pattern of flow variation in both pressure/volume-controlled ventilation, are formulated and presented for use by ventilator designers. A comparative study of the simulation of step, ramp and cycloidal profiles applied to the breath cycle in a typical pressure-controlled ventilation is carried out and a marginal decrease in tidal volumes was observed in the case of cycloidal profiles for a given set of ventilator settings and the results are discussed. A typical natural breath pattern of a healthy adult was experimentally measured using a CITRIX breath analyser and the above mathematical model for the volume-controlled ventilation was found to closely describe the natural breathing process, using statistical parameters. Thus, the proposed cycloidal profile of pressure/flow variations in medical ventilators will be a better alternative, when compared to the step/ramp profiles investigated in this work; further, the proposed cycloidal profile matches closely with the natural breath pattern, based on typical experimental studies. [ABSTRACT FROM AUTHOR]

Abstract Seismocardiographic (SCG) signals are chest wall vibrations induced by cardiac activity and are potentially useful for cardiac monitoring and diagnosis. SCG waveform is observed to vary with respiration, but the mechanism of these changes is poorly understood as alterations in autonomic tone, lung volume, heart location and intrathoracic pressure are all varying during the respiratory cycle. Understanding SCG variability and its sources may help reduce variability and increase SCG clinical utility. This study investigated SCG variability during breath holding (BH) at two different lung volumes (i.e., end inspiration and end expiration) and five airway pressures (i.e., 0, ± 2–4, and ± 15–20 cm H2O). Variability during normal breathing was also studied with and without grouping SCG beats into two clusters of similar waveform morphologies (performed using the K-medoid algorithm in an unsupervised machine learning fashion). The study included 15 healthy subjects (11 Females and 4 males, Age: 21 ± 2 y) where SCG, ECG, and spirometry were simultaneously acquired. SCG waveform variability was calculated at each experimental state (i.e., lung volume and airway pressure). Results showed that breath holding was more effective in reducing the intra-state variability of SCG than clustering normal breathing data. For the BH states, the intra-state variability increased as the airway pressure deviated from zero. The subaudible-to-audible energy ratio of the BH states increased as the airway pressure decreased below zero which may be related to the effect of the intrathoracic pressure on cardiac afterload and blood ejection. When combining the BH waveforms at end inspiration and end expiration states (at the same airway pressures) into one group, the intra-state variability increased, which suggests that the lung volume and associated change in heart location were a significant source of variability. The linear trend between airway pressure and waveform changes was found to be statistically significant for BH at end expiration. To confirm these findings, more studies are needed with a larger number of airway pressure levels and larger number of subjects.

Seismocardiographic (SCG) signals are chest wall vibrations induced by cardiac activity and are potentially useful for cardiac monitoring and diagnosis. SCG waveform is observed to vary with respiration, but the mechanism of these changes is poorly understood as alterations in autonomic tone, lung volume, heart location and intrathoracic pressure are all varying during the respiratory cycle. Understanding SCG variability and its sources may help reduce variability and increase SCG clinical utility. This study investigated SCG variability during breath holding (BH) at two different lung volumes (i.e., end inspiration and end expiration) and five airway pressures (i.e., 0, ± 2–4, and ± 15–20 cm H2O). Variability during normal breathing was also studied with and without grouping SCG beats into two clusters of similar waveform morphologies (performed using the K-medoid algorithm in an unsupervised machine learning fashion). The study included 15 healthy subjects (11 Females and 4 males, Age: 21 ± 2 y) where SCG, ECG, and spirometry were simultaneously acquired. SCG waveform variability was calculated at each experimental state (i.e., lung volume and airway pressure). Results showed that breath holding was more effective in reducing the intra-state variability of SCG than clustering normal breathing data. For the BH states, the intra-state variability increased as the airway pressure deviated from zero. The subaudible-to-audible energy ratio of the BH states increased as the airway pressure decreased below zero which may be related to the effect of the intrathoracic pressure on cardiac afterload and blood ejection. When combining the BH waveforms at end inspiration and end expiration states (at the same airway pressures) into one group, the intra-state variability increased, which suggests that the lung volume and associated change in heart location were a significant source of variability. The linear trend between airway pressure and waveform changes was found to be statistically significant for BH at end expiration. To confirm these findings, more studies are needed with a larger number of airway pressure levels and larger number of subjects. [ABSTRACT FROM AUTHOR]

Goal: To evaluate suitability of respiratory signals derived from clinical 12-lead electrocardiograms (ECGs) and wearable 1-lead ECG to identify different respiration types. Methods: ECGs were simultaneously acquired through the M12R ECG Holter by Global Instrumentation and the chest strap BioHarness 3.0 by Zephyr from 42 healthy subjects alternating normal breathing, breath holding, and deep breathing. Respiration signals were derived from the ECGs through the Segmented-Beat Modulation Method (SBMM)-based algorithm and the algorithms by Van Gent, Charlton, Soni and Sarkar, and characterized in terms of breathing rate and amplitude. Respiration classification was performed through a linear support vector machine and evaluated by F1 score. Results: Best F1 scores were 86.59%(lead V2) and 80.57%, when considering 12-lead and 1-lead ECGs, respectively, and using SBMM-based algorithm. Conclusion: ECG-derived respiratory signals allow reliable identification of different respiration types even when acquired through wearable sensors, if associated to appropriate processing algorithms, such as the SBMM-based algorithm.

Mechanical ventilation is required for many patients who cannot breathe normally as a result of lung disease and other factors that result in reduced lung function. In this study, we investigated the effects of mechanical ventilation and normal breathing on whole lung geometry as well as isolated bifurcations through computational fluid dynamic (CFD) simulations. Results of flow characteristics (airflow velocity, wall pressure, and wall shear stress) obtained from the CFD simulations are presented. Similar flow patterns and pressure drops were obtained between the whole lung geometry and isolated bifurcations under both normal breathing and mechanical ventilation, respectively. Results obtained from simulations suggest that analyzing specific local bifurcations may be a more feasible alternative as it may reduce the computational time and numerical errors resulting from computations as compared to simulating a complex whole lung geometry. The approach presented in this study also demonstrated that analyses of isolated bifurcations gave similar flow characteristics to that of whole lung geometry. Therefore, this approach may be useful for quickly obtaining results that will assist in making clinical predictions and other applications. [ABSTRACT FROM AUTHOR]

Objectives: Nasal peak inspiratory flow (NPIF) is a practical and affordable tool that measures maximum inspiratory flow rate through both nostrils. Although NPIF values for healthy controls and patients appear to differ considerably, a generally expected value for populations with and without nasal obstruction has yet to be established. The aim of this systematic review and meta-analysis was to determine the mean NPIF value in populations with and without nasal obstruction.Methods: Medline (1946-) and Embase (1947-) were searched until July 1, 2017. A search strategy was used to identify studies that reported NPIF values for defined healthy or disease states. All studies providing original data were included. The study population was defined as having either normal nasal breathing or nasal obstruction. A meta-analysis of the mean data was presented in forest plots, and data were presented as mean (95% confidence interval [CI]).Results: The search yielded 1,526 studies, of which 29 were included. The included studies involved 1,634 subjects with normal nasal breathing and 817 subjects with nasal obstruction. The mean NPIF value for populations with normal nasal breathing was 138.4 (95% CI: 127.9-148.8) L/min. The mean value for populations with nasal obstruction was 97.5 (95% CI: 86.1-108.8) L/min.Conclusions: Current evidence confirms a difference between mean NPIF values of populations with and without nasal obstruction. The mean value of subjects with no nasal obstruction is 138.4 L/min, and the mean value of nasally obstructed populations is 97.5 L/min. Prospective studies adopting a standardized procedure are required to further assess normative NPIF values. Laryngoscope, 131:260-267, 2021. [ABSTRACT FROM AUTHOR]

Mechanical ventilation is required for many patients who cannot breathe normally as a result of lung disease and other factors that result in reduced lung function. In this study, we investigated the effects of mechanical ventilation and normal breathing on whole lung geometry as well as isolated bifurcations through computational fluid dynamic (CFD) simulations. Results of flow characteristics (airflow velocity, wall pressure, and wall shear stress) obtained from the CFD simulations are presented. Similar flow patterns and pressure drops were obtained between the whole lung geometry and isolated bifurcations under both normal breathing and mechanical ventilation, respectively. Results obtained from simulations suggest that analyzing specific local bifurcations may be a more feasible alternative as it may reduce the computational time and numerical errors resulting from computations as compared to simulating a complex whole lung geometry. The approach presented in this study also demonstrated that analyses of isolated bifurcations gave similar flow characteristics to that of whole lung geometry. Therefore, this approach may be useful for quickly obtaining results that will assist in making clinical predictions and other applications.

Abstract In this work, we investigate the regional characteristics of the dynamic interactions between arterial CO 2 and BOLD (dynamic cerebrovascular reactivity - dCVR) during normal breathing and hypercapnic, externally induced step CO 2 challenges. To obtain dCVR curves at each voxel, we use a custom set of basis functions based on the Laguerre and gamma basis sets. This allows us to obtain robust dCVR estimates both in larger regions of interest (ROIs), as well as in individual voxels. We also implement classification schemes to identify brain regions with similar dCVR characteristics. Our results reveal considerable variability of dCVR across different brain regions, as well as during different experimental conditions (normal breathing and hypercapnic challenges), suggesting a differential response of cerebral vasculature to spontaneous CO 2 fluctuations and larger, externally induced CO 2 changes that are possibly associated with the underlying differences in mean arterial CO 2 levels. The clustering results suggest that anatomically distinct brain regions are characterized by different dCVR curves that in some cases do not exhibit the standard, positive valued curves that have been previously reported. They also reveal a consistent set of dCVR cluster shapes for resting and forcing conditions, which exhibit different distribution patterns across brain voxels. [ABSTRACT FROM AUTHOR]

Applied pressure on human lung wall has great importance on setting up protective ventilatory strategies, therefore, estimating pressure relationships in terms of specific parameters would provide invaluable information specifically during mechanical ventilation (MV). A three-dimensional model from a healthy human lung MRI is analyzed by computational fluid dynamic (CFD), and results for pressure are curve fitted to estimate relationships that associate pressure to breathing time, cross section and generation numbers of intended locations. Among all possible functions, it is observed that exponential and polynomial pressure functions present most accurate results for normal breathing (NB) and MV, respectively. For validation, pressure-location curves from CFD and results from this study are compared and good correlations are found. Also, estimated pressure values are used to calculate pressure drop and airway resistance to the induced air into the lung bifurcations. It is concluded that maximum pressure drop appeared in generation number 2 and medium sized airways show higher resistance to air flow and that resistance decreased as cross sectional area increased through the model. Results from this study are in good agreement with previous studies and provide potentials for further studies on influence of air pressure on human lung tissue and reducing lung injuries during MV. [ABSTRACT FROM AUTHOR]

We have studied the rate of evaporation of sweat for the body of human of two different surface areas at different temperatures. We have also studied the rate of evaporation of sweat at different values of heat produced by chemical metabolism. It is found that a thin man perspires at lower temperature than a fat man when they both produce the same heat by chemical metabolism. Keywords: Chemical metabolism; Evaporation of sweat; Normal breathing DOI: 10.3126/bibechana.v7i0.4037 BIBECHANA 7 (2011) 14-17

We investigated the function of the m. hyohyoideus superior (MHS) and inferior (MHI) in the head of three carp (Cyprinus carpio L., 29.7 ± 2.1 cm FL ) during three movements (normal breathing, stressed movements and food uptake). Both muscle parts are located ventrally at the inner side of the operculum and branchiostegal rays and consist of red (mainly in MHI) and white (mainly in MHS) fibres. Contrasting views exist about the functional role of these muscles during ventilation and food uptake. Therefore, we analysed muscle activities of the MHS and MHI using electromyography (EMG) and measured the strain pattern of the MHS using sonomicrometry. Carp were also filmed from a ventral viewpoint using high-speed video at 250 frames s[sup -1]. EMG and sonomicrometry data showed an increase in muscle strain amplitudes, cycle frequency and (relative) stimulus duration while stimulus on- and off-times occurred earlier in the strain cycle from normal breathing to stressed movements to food uptake. The MHS and MHI were always simultaneously active. We concluded that: 1) the MHI is not responsible for high frequency movements (i.e. stressed movements and food uptake); 2) both muscle parts assist in the onset of opercular closing, and 3) the MHS and MHI do not act as antagonists in carp. [ABSTRACT FROM AUTHOR]