Academic literature on the topic 'Ventilation Waveform Data'
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Journal articles on the topic "Ventilation Waveform Data"
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Rehm, Gregory, Jinyoung Han, Brooks Kuhn, Jean-Pierre Delplanque, Nicholas Anderson, Jason Adams, and Chen-Nee Chuah. "Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony." Methods of Information in Medicine 57, no. 04 (September 2018): 208–19. http://dx.doi.org/10.3414/me17-02-0012.
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Summary Background: As healthcare increasingly digitizes, streaming waveform data is being made available from an variety of sources, but there still remains a paucity of performant clinical decision support systems. For example, in the intensive care unit (ICU) existing automated alarm systems typically rely on simple thresholding that result in frequent false positives. Recurrent false positive alerts create distrust of alarm mechanisms that can be directly detrimental to patient health. To improve patient care in the ICU, we need alert systems that are both pervasive, and accurate so as to be informative and trusted by providers. Objective: We aimed to develop a machine learning-based classifier to detect abnormal waveform events using the use case of mechanical ventilation waveform analysis, and the detection of harmful forms of ventilation delivery to patients. We specifically focused on detecting injurious subtypes of patient-ventilator asynchrony (PVA). Methods: Using a dataset of breaths recorded from 35 different patients, we used machine learning to create computational models to automatically detect, and classify two types of injurious PVA, double trigger asynchrony (DTA), breath stacking asynchrony (BSA). We examined the use of synthetic minority over-sampling technique (SMOTE) to overcome class imbalance problems, varied methods for feature selection, and use of ensemble methods to optimize the performance of our model. Results: We created an ensemble classifier that is able to accurately detect DTA at a sensitivity/specificity of 0.960/0.975, BSA at sensitivity/specificity of 0.944/0.987, and non-PVA events at sensitivity/specificity of .967/.980. Conclusions: Our results suggest that it is possible to create a high-performing machine learning-based model for detecting PVA in mechanical ventilator waveform data in spite of both intra-patient, and inter-patient variability in waveform patterns, and the presence of clinical artifacts like cough and suction procedures. Our work highlights the importance of addressing class imbalance in clinical data sets, and the combined use of statistical methods and expert knowledge in feature selection.
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Lutchen, K. R., K. Yang, D. W. Kaczka, and B. Suki. "Optimal ventilation waveforms for estimating low-frequency respiratory impedance." Journal of Applied Physiology 75, no. 1 (July 1, 1993): 478–88. http://dx.doi.org/10.1152/jappl.1993.75.1.478.
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We present a broad-band optimal ventilator waveform (OVW), the concept of which was to create a computer-driven ventilator waveform containing increased energy at specific frequencies (f). Values of f were chosen such that nonlinear harmonic distortion and intermodulation were minimized. The phases at each f were then optimized such that the resulting flow waveform delivered sufficient volume to maintain gas exchange while minimizing peak-to-peak airway opening pressure. Simulations with a linear anatomically consistent branching airway model and a nonlinear viscoelastic model showed that respiratory resistance (Rrs) and elastance (Ers) estimates at 0.1–2 Hz from the OVW are far superior to those from a standard step ventilator waveform (SVW) during healthy and obstructed conditions and that the OVW reduces the influences of harmonic interactions. Using a servo-controlled oscillator, we applied individual sine waves, an OVW containing energy at 0.15625–2.4 Hz, and an SVW to healthy humans and one symptomatic asthmatic subject before and after bronchodilation. The OVW was markedly superior to the SVW and always provided smooth estimates of Rrs and Ers. Before bronchodilation in the asthmatic subject Rrs was highly elevated and Ers was markedly increased with f; after bronchodilation the level of Rrs and the f dependence of Ers decreased. Although based on results from only one asthmatic subject, these data suggest a dominant influence of airway constriction and lung inhomogeneities during asthmatic bronchoconstriction that is alleviated by bronchodilators. These and other results indicate that the OVW approach has high potential for simultaneously probing f and amplitude dependence in the mechanical properties of clinical subjects during physiological breathing conditions and perhaps during dynamic bronchoconstriction.
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Luijendijk, S. C., and J. Milic-Emili. "Breathing patterns in anesthetized cats and the concept of minimum respiratory effort." Journal of Applied Physiology 64, no. 1 (January 1, 1988): 31–41. http://dx.doi.org/10.1152/jappl.1988.64.1.31.
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Theoretical studies dealing with the principle of minimal respiratory effort usually make use of sinusoidal or saw-tooth-like breathing patterns. Recent observations in anesthetized cats have shown that the driving pressure waveform for inspiration can be described by a power function of time and that most of expiration is passive. This driving pressure waveform, however, results in breathing patterns that differ from those described above. For this reason, we have reevaluated in anesthetized cats the principle of minimal respiratory effort by computing optimal duration of inspiration (TI) and optimal tidal volume (VT) for different ventilatory conditions using actual driving pressure waveforms. The results are in qualitative agreement with the experimental observations; i.e., optimal TI decreases and optimal VT increases with increasing minute ventilation. On the average, a good agreement is found between measured and computed values of TI. In some cats, however, there are substantial differences between observed and predicted values of TI, which can probably be ascribed to inaccuracies in the data used in our computations. Despite its limitations, the present model analysis is more realistic than previous ones because actual driving pressure waveforms are used together with actual values of effective inspiratory impedance.
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Herrmann, Jacob, Merryn H. Tawhai, and David W. Kaczka. "Regional gas transport in the heterogeneous lung during oscillatory ventilation." Journal of Applied Physiology 121, no. 6 (December 1, 2016): 1306–18. http://dx.doi.org/10.1152/japplphysiol.00097.2016.
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Regional ventilation in the injured lung is heterogeneous and frequency dependent, making it difficult to predict how an oscillatory flow waveform at a specified frequency will be distributed throughout the periphery. To predict the impact of mechanical heterogeneity on regional ventilation distribution and gas transport, we developed a computational model of distributed gas flow and CO2 elimination during oscillatory ventilation from 0.1 to 30 Hz. The model consists of a three-dimensional airway network of a canine lung, with heterogeneous parenchymal tissues to mimic effects of gravity and injury. Model CO2 elimination during single frequency oscillation was validated against previously published experimental data (Venegas JG, Hales CA, Strieder DJ, J Appl Physiol 60: 1025–1030, 1986). Simulations of gas transport demonstrated a critical transition in flow distribution at the resonant frequency, where the reactive components of mechanical impedance due to airway inertia and parenchymal elastance were equal. For frequencies above resonance, the distribution of ventilation became spatially clustered and frequency dependent. These results highlight the importance of oscillatory frequency in managing the regional distribution of ventilation and gas exchange in the heterogeneous lung.
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Menon, A. S., S. J. England, E. Vallieres, A. S. Rebuck, and A. S. Slutsky. "Influence of phasic afferent information on phrenic neural output during hypercapnia." Journal of Applied Physiology 65, no. 2 (August 1, 1988): 563–69. http://dx.doi.org/10.1152/jappl.1988.65.2.563.
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We measured the moving time average (MTA) of the phrenic neurogram before and after removal of phasic afferent information from the lungs, chest wall, and oscillations in blood gases by using constant-flow ventilation (CFV). Anesthetized dogs were studied at various levels of steady-state and progressive hypercapnia during spontaneous breathing and during CFV. When steady-state and progressive hypercapnia were compared, the frequency and height of the MTA phrenic neurogram were independent of the rate of induction of hypercapnia during each mode of ventilation. During spontaneous ventilation, the response to hypercapnia comprised mainly an increase in frequency with only a slight increase in the amplitude of the MTA phrenic waveform. During muscular paralysis and CFV, the responses were similar to those observed after vagotomy with mainly an increase in the amplitude and only a small increase in frequency. For both spontaneous breathing and CFV, increases in frequency were achieved mainly by a shortening in expiratory time with the inspiratory time remaining relatively constant. Our data support the concept of a centrally patterned respiratory generator, whose inherent pattern is modified by phasic feedback from peripheral receptors mainly of vagal origin.
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Burke, W. C., P. S. Crooke, T. W. Marcy, A. B. Adams, and J. J. Marini. "Comparison of mathematical and mechanical models of pressure-controlled ventilation." Journal of Applied Physiology 74, no. 2 (February 1, 1993): 922–33. http://dx.doi.org/10.1152/jappl.1993.74.2.922.
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Recent evidence that volume-cycled mechanical ventilation may itself produce lung injury has focused clinical attention on the pressure waveform applied to the respiratory system. There has been an increasing use of pressure-controlled ventilation (PCV), because it limits peak cycling pressure and provides a decelerating flow profile that may improve gas exchange. In this mode, however, the relationships are of machine adjustments to ventilation and alveolar pressure are not straightforward. Consequently, setting selection remains largely an empirical process. In previous work, we developed a biexponential model of PCV that provides a conceptual framework for understanding these interactions (J. Appl. Physiol. 67: 1081–1092, 1989). We tested the validity of this mathematical model in a single-compartment analogue of the respiratory system across wide ranges of clinician-set variables (frequency, duty cycle, applied pressure) and impedance conditions (inspiratory and expiratory resistance and system compliance). Our data confirm the quantitative validity of the proposed model when approximately rectilinear waves of pressure are applied and appropriate values for impedance are utilized. Despite a fixed-circuit configuration, however, resistance proved to be a function of each clinician-set variable, requiring remeasurement of system impedance as adjustments in these variables were made. With further modification, this model may provide a practical as well as a conceptual basis for understanding minute ventilation and alveolar pressure fluctuations during PCV in the clinical setting.
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Ito, Satoru, Kenneth R. Lutchen, and Béla Suki. "Effects of heterogeneities on the partitioning of airway and tissue properties in normal mice." Journal of Applied Physiology 102, no. 3 (March 2007): 859–69. http://dx.doi.org/10.1152/japplphysiol.00884.2006.
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We measured the mechanical properties of the respiratory system of C57BL/6 mice using the optimal ventilation waveform method in closed- and open-chest conditions at different positive end-expiratory pressures. The tissue damping (G), tissue elastance (H), airway resistance (Raw), and hysteresivity were obtained by fitting the impedance data to three different models: a constant-phase model by Hantos et al. (Hantos Z, Daroczy B, Suki B, Nagy S, Fredberg JJ. J Appl Physiol 72: 168–178, 1992), a heterogeneous Raw model by Suki et al. (Suki B, Yuan H, Zhang Q, Lutchen KR. J Appl Physiol 82: 1349–1359, 1997), and a heterogeneous H model by Ito et al. (Ito S, Ingenito EP, Arold SP, Parameswaran H, Tgavalekos NT, Lutchen KR, Suki B. J Appl Physiol 97: 204–212, 2004). Both in the closed- and open-chest conditions, G and hysteresivity were the lowest and Raw the highest in the heterogeneous Raw model, and G and H were the largest in the heterogeneous H model. Values of G, Raw, and hysteresivity were significantly higher in the closed-chest than in the open-chest condition. However, H was not affected by the conditions. When the tidal volume of the optimal ventilation waveform was decreased from 8 to 4 ml/kg in the closed-chest condition, G and hysteresivity significantly increased, but there were smaller changes in H or Raw. In summary, values of the obtained mechanical properties varied among these models, primarily due to heterogeneity. Moreover, the mechanical parameters were significantly affected by the chest wall and tidal volume in mice. Contribution of the chest wall and heterogeneity to the mechanical properties should be carefully considered in physiological studies in which partitioning of airway and tissue properties are attempted.
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Dellacà, Raffaele L., Lauren D. Black, Haytham Atileh, Antonio Pedotti, and Kenneth R. Lutchen. "Effects of posture and bronchoconstriction on low-frequency input and transfer impedances in humans." Journal of Applied Physiology 97, no. 1 (July 2004): 109–18. http://dx.doi.org/10.1152/japplphysiol.00721.2003.
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We simultaneously evaluated the mechanical response of the total respiratory system, lung, and chest wall to changes in posture and to bronchoconstriction. We synthesized the optimal ventilation waveform (OVW) approach, which simultaneously provides ventilation and multifrequency forcing, with optoelectronic plethysmography (OEP) to measure chest wall flow globally and locally. We applied an OVW containing six frequencies from 0.156 to 4.6 Hz to the mouth of six healthy men in the seated and supine positions, before and after methacholine challenge. We measured mouth, esophageal, and transpulmonary pressures, airway flow by pneumotachometry, and total chest wall, pulmonary rib cage, and abdominal volumes by OEP. We computed total respiratory, lung, and chest wall input impedances and the total and regional transfer impedances (Ztr). These data were appropriately sensitive to changes in posture, showing added resistance in supine vs. seated position. The Ztr were also highly sensitive to lung constriction, more so than input impedance, as the former is minimally distorted by shunting of flow into alveolar gas compression and airway walls. Local impedances show that, during bronchoconstriction and at typical breathing frequencies, the contribution of the abdomen becomes amplified relative to the rib cage. A similar redistribution occurs when passing from seated to supine. These data suggest that the OEP-OVW approach for measuring Ztr could noninvasively track important lung and respiratory conditions, even in subjects who cannot cooperate. Applications might range from routine evaluation of airway hyperreactivity in asthmatic subjects to critical conditions in the supine position during mechanical ventilation.
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Kaczka, David W., Edward P. Ingenito, Bela Suki, and Kenneth R. Lutchen. "Partitioning airway and lung tissue resistances in humans: effects of bronchoconstriction." Journal of Applied Physiology 82, no. 5 (May 1, 1997): 1531–41. http://dx.doi.org/10.1152/jappl.1997.82.5.1531.
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Kaczka, David W., Edward P. Ingenito, Bela Suki, and Kenneth R. Lutchen. Partitioning airway and lung tissue resistances in humans: effects of bronchoconstriction. J. Appl. Physiol. 82(5): 1531–1541, 1997.—The contribution of airway resistance (Raw) and tissue resistance (Rti) to total lung resistance (R l ) during breathing in humans is poorly understood. We have recently developed a method for separating Raw and Rti from measurements of Rland lung elastance (El) alone. In nine healthy, awake subjects, we applied a broad-band optimal ventilator waveform (OVW) with energy between 0.156 and 8.1 Hz that simultaneously provides tidal ventilation. In four of the subjects, data were acquired before and during a methacholine (MCh)-bronchoconstricted challenge. The Rland Eldata were first analyzed by using a model with a homogeneous airway compartment leading to a viscoelastic tissue compartment consisting of tissue damping and elastance parameters. Our OVW-based estimates of Raw correlated well with estimates obtained by using standard plethysmography and were responsive to MCh-induced bronchoconstriction. Our data suggest that Rti comprises ∼40% of total Rlat typical breathing frequencies, which corresponds to ∼60% of intrathoracic Rl. During mild MCh-induced bronchoconstriction, Raw accounts for most of the increase in Rl. At high doses of MCh, there was a substantial increase in Rlat all frequencies and in El at higher frequencies. Our analysis showed that both Raw and Rti increase, but most of the increase is due to Raw. The data also suggest that widespread peripheral constriction causes airway wall shunting to produce additional frequency dependence in El.
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Fuhrman, B. P., D. L. Smith-Wright, T. J. Kulik, and J. E. Lock. "Effects of static and fluctuating airway pressure on intact pulmonary circulation." Journal of Applied Physiology 60, no. 1 (January 1, 1986): 114–22. http://dx.doi.org/10.1152/jappl.1986.60.1.114.
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The direct effects on the pulmonary circulation of static and fluctuation airway pressure were compared in intact close-chest infant lambs with reactive pulmonary vasculature under alpha-chloralose anesthesia. A preparation developed to permit independent ventilation of right and left lungs and independent measurement of right and left lung blood flow was employed to separate direct from indirect effects of unilateral airway pressure changes on pulmonary vascular resistance (PVR). Both static and fluctuating unilateral airway pressure interventions directly elevated ipsilateral PVR. For purposes of comparison mean alveolar pressure (PA) was estimated for both static and fluctuating trials. Fluctuating interventions increased PVR more than did static trials at comparable levels of PA. Substantially less PA was needed to double ipsilateral PVR by fluctuating than by static interventions (16 vs. 26 mmHg, respectively). These data indicate that, in the intact animal with reactive pulmonary vasculature, both PA and the waveform of airway pressure applied can influence PVR.
Books on the topic "Ventilation Waveform Data"
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Lucangelo, Umberto, and Massimo Ferluga. Pulmonary mechanical dysfunction in the critically ill. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0084.
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In intensive care units practitioners are confronted every day with mechanically-ventilated patients and should be able to sort out from all the data available from modern ventilators to tailored patient ventilatory strategy. Real-time visualization of pressure, flow and tidal volume provide valuable information on the respiratory system, to optimize ventilatory support and avoiding complications associated with mechanical ventilation. Early determination of patient–ventilator asynchrony, air-trapping, and variation in respiratory parameters is important during mechanical ventilation. A correct evaluation of data becomes mandatory to avoid a prolonged need for ventilatory support. During dynamic hyperinflation the lungs do not have time to reach the functional residual capacity at the end of expiration, increasing the work of breathing and promoting patient-ventilator asynchrony. Expiratory capnogram provides qualitative information on the waveform patterns associated with mechanical ventilation and quantitative estimation of expired CO2. The concept of dead space accounts for those lung areas that are ventilated but not perfused. Calculations derived from volumetric capnography are useful indicators of pulmonary embolism. Moreover, alveolar dead space is increased in acute lung injury and its value decreased in case of positive end-expiratory pressure (PEEP)-induced recruitment, whereas PEEP-induced overdistension tends to increment alveolar dead space.
Conference papers on the topic "Ventilation Waveform Data"
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Adams, J. Y., G. B. Rehm, I. Cortes-Puch, B. T. Kuhn, J. I. Nguyen, N. R. Anderson, and C. N. Chuah. "A Machine Learning Classifier for Early Detection of ARDS Using Raw Ventilator Waveform Data." In American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a2745.
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