Journal articles: 'Cardio-respiratory modeling'

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Indic, Premananda, Elisabeth Bloch-Salisbury, Frank Bednarek, Emery N. Brown, David Paydarfar, and Riccardo Barbieri. "Assessment of cardio-respiratory interactions in preterm infants by bivariate autoregressive modeling and surrogate data analysis." Early Human Development 87, no. 7 (July 2011): 477–87. http://dx.doi.org/10.1016/j.earlhumdev.2011.04.001.

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Demin, A. V., A. V. Suvorov, and O. I. Orlov. "CHARACTERSTICS OF HEALTHY MEN HEMODYNAMICS IN A HYPOMAGNETIC ENVIRONMENT." Aerospace and Environmental Medicine 55, no. 2 (2021): 63–68. http://dx.doi.org/10.21687/0233-528x-2021-55-2-63-68.

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Hemodynamics was studied in essentially healthy resting 8 male subjects exposed to an experimental hypomagnetic environment (HME). The cardio-respiratory system functioning was evaluated by 8-hour continuous monitoring of heart rate (HR), blood pressure (BP) fluctuations during every cardiac cycle, Kerdo autonomic index (KAI) and blood oxygenation (SpO2) in the Earth's natural magnetic field and a field attenuated in approximately 1,000 times. Comparative analysis of the measurements made in the control and HME tests elicited different trends. Thus, the HR average reduction amounted to 4 bpm; BP dropped significantly, i.e. diastolic BP by 11 mmHg and systolic BP, 16 mmHg on average. In HME, KAI rose commonly 20 %. Hemoglobin saturation did not change. The paper contains graphic interpretations of the KAI dependence on duration of the HME exposure. Mathematical modeling suggests a physiological interpretation of these results. More often than not sitting at rest in HME reduced substantially the modulating effect of parasympathetic regulation on the cardiovascular system in comparison with the control test in the normal geomagnetic field.

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Umbarkar, Tejas S., and Clement Kleinstreuer. "Computationally Efficient Fluid-Particle Dynamics Simulations of Arterial Systems." Communications in Computational Physics 17, no. 2 (January 23, 2015): 401–23. http://dx.doi.org/10.4208/cicp.160114.120914a.

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AbstractRealistic and accurate computer simulations of the particle-hemodynamics in arterial systems can be a valuable tool for numerous biomedical applications. Examples include optimal by-pass grafting and optimal drug-delivery, as well as best medical management concerning the cardio-vascular system. However, such numerical analyses require large computer resources which may become prohibitive for extended sets of arterial bifurcations. A remedy is to develop a hybrid model where the first few generations of the bifurcating arteries of interest are simulated in full 3-D, while a 1-D model is then coupled for subsequent bifurcations. Alternatively, a 1-D computer model can be directly employed to simulate fluid-particle transport in complex bifurcating networks.Relying on a representative axial velocity profile, a physiological 1-D model has been developed and validated, which is capable of predicting with reasonable accuracy arterial flow, pressure field and elastic wall interaction as well as particle transport. The usefulness of the novel 1-D simulation approach is demonstrated via a comparison to 3-D blood flow and microsphere transport in a hepatic artery system, featuring as outlets one major branch and four small daughter vessels. Compared to the 3-D simulation, the 1-D analysis requires only about 1% of computational time. The hybrid modeling approach would be also applicable to the human respiratory tract to evaluate the fate of inhaled aerosols.A simple and cost-effective way to simulate particle-hemodynamics is using a 1-D model for simulating arterial pressures and flow rates as well as microsphere transport, based on assumptions involving the use of a simple algebraic pressure-area relation, an exponential elasticity model for the vessels, and considering only unidirectional flow with a representative skewed velocity profile. In summary, the novel contributions are:• Particle tracking in arteries via 1-D fluid modeling and selection of an averaged, skewed velocity profile based on 3-D simulation results to provide more realistic friction and inertia term values for modeling a flow system with bifurcations.• The 1-D model can be coupled to a 3-D model so that simulations can be run for larger regions of vascular or lung-airway systems.

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Haddad, Azzam, Yi Zhang, Steven Su, Branko Celler, and Hung Nguyen. "Modelling and regulating of cardio-respiratory response for the enhancement of interval training." BioMedical Engineering OnLine 13, no. 1 (2014): 9. http://dx.doi.org/10.1186/1475-925x-13-9.

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Paterson, David J., and Julian F. R. Paton. "Insights gleaned from pharmaco-genetic dissection and modelling of cardio-respiratory neural networks." Journal of Physiology 593, no. 14 (July 15, 2015): 3031. http://dx.doi.org/10.1113/jp270838.

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Ogawa, Teruyuki, Naoki Fukushima, Masanobu Kojo, Hirotomi Sonoda, Kazuya Goto, Kouichi Wakayama, and Shun Ishiwa. "Cardio-respiratory control in an infant with Ondine's curse. Multivariate autoregressive modelling approach." Journal of the Autonomic Nervous System 45, no. 3 (December 1993): 254. http://dx.doi.org/10.1016/0165-1838(93)90067-5.

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Munk, Marc-David, Dora M. Carboneau, Muhammed Hardan, and Faleh Mohamed Ali. "Seatbelt Use in Qatar in Association with Severe Injuries and Death in the Prehospital Setting." Prehospital and Disaster Medicine 23, no. 6 (December 2008): 547–52. http://dx.doi.org/10.1017/s1049023x00006397.

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AbstractIntroduction:Road traffic crashes (RTCs) are common in Qatar, and are now considered the third leading cause of mortality. In this study, the safety devices used by the Qatari public at the time of RTCs were assessed and the association between seatbelt use by vehicle occupants involved in RTCs and severe injury/death in the prehospital setting was determined.Methods:This study was a retrospective case-control investigation. A Hamad Medical Corporation Emergency Medical Services (EMS) database of RTCs occurring from January 2006 to April 2007 was utilized for this study, providing a total of 5,267 patient records (83.5 % male, 16.5% female, median age = 28 years). Patient demographics, crash characteristics, prehospital assessments, and interventions were identified, and use of safety devices was determined. Univariate analysis including chi-square, Student's t-test, and analysis of variance (ANOVA) was performed as appropriate. “Case” patients are defined as those who had specific, critical prehospital assessments, or who received advanced cardio-respiratory life support measures in the field. Logistic regression modeling was used to predict the probability of a case being unbelted, controlling for confounders.Results:Seatbelt use in Qatar was low: 33.9% of males and 32.6% of females wore seatbelts at the time of the RTC. Victims involved in a vehicle rollover crash were less likely to be belted than were those involved in a non-rollover incident (26.2% belted vs. 37.8%; OR = 0.59; 95%CI = 0.50–0.68). Case patients—those with defined critical assessment findings or resuscitation in the field—and control patients were similar in age (30 years vs. 28 years median). Case patients were disproportionately male (89.1% vs. 83.2%; OR = 1.65; 95%CI = 1.01–2.83) and were more likely to be victims of a vehicle rollover crash (44.7% vs. 23.8%; OR = 2.57; 95%CI = 1.84–3.59). Seatbelt use was significantly lower among cases than controls: 19.7% of cases were reported to have worn seatbelts compared to 34.2% of controls (OR = 0.47; 95%CI = 0.31–0.69). This relationship also persisted (OR = 0.51; 95%CI = 0.33–0.76) after controlling for confounders.Conclusions:Seatbelt use in Qatar is low. Seatbelts are protective: in the pre-hospital setting unbelted vehicle occupants involved in RTCs were nearly twice as likely to suffer severe injury or death compared to belted patients. Prehospital morbidity and mortality appears to be reduced significantly by the consistent use of seatbelts by the motoring population in Qatar.

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Ogawa, Teruyuki, Masanobu Kojo, Naoki Fukushima, Hirotomi Sonoda, Kazuya Goto, Shun Ishiwa, and Makoi Ishiguro. "Cardio-respiratory control in an infant with Ondine's curse: a multivariate autoregressive modelling approach." Journal of the Autonomic Nervous System 42, no. 1 (January 1993): 41–51. http://dx.doi.org/10.1016/0165-1838(93)90340-z.

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Huang, Yi, Francesca Dominici, and Michelle L. Bell. "Bayesian hierarchical distributed lag models for summer ozone exposure and cardio-respiratory mortality." Environmetrics 16, no. 5 (2005): 547–62. http://dx.doi.org/10.1002/env.721.

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Topczewska, Magdalena, Małgorzata Sawicka-Żukowska, Joanna Zapolska, Lucyna Ostrowska, and Maryna Krawczuk-Rybak. "Statistical Methods in the Evaluation of Cardio-Respiratory Parameters in Young Childhood Cancer Survivors and Healthy Peers." Studies in Logic, Grammar and Rhetoric 56, no. 1 (December 1, 2018): 29–44. http://dx.doi.org/10.2478/slgr-2018-0039.

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Abstract This study concerns the problem of late complications of antineo-plastic therapy. Reduced parameters of the cardiorespiratory system in childhood may have a tremendous impact on health. In order to assess the selected parameters, to evaluate physical endurance, and compare the results with those obtained for healthy children, a test was carried out on a treadmill, until 80% of maximum pulse rate was reached. To compare the differences between the treatment group and the control group, three approaches were used. The first one was the classical statistical inference, the second consisted in forming a multidimensional normal model and also involved modelling of the correlation between variables. The unstructured type of the working correlation matrix was chosen to obtain the results and correct standard errors. In the last approach, logistic regression was used to model the relationship between binary outcome and covariates, and to differentiate between the groups of patients on the basis of their cardiovascular parameters.

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Campbell, H. A., J. Z. Klepacki, and S. Egginton. "A new method in applying power spectral statistics to examine cardio-respiratory interactions in fish." Journal of Theoretical Biology 241, no. 2 (July 2006): 410–19. http://dx.doi.org/10.1016/j.jtbi.2005.12.005.

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Kopczyńska, Beata. "Role of VR1 and CB1 receptors in modelling of cardio-respiratory response to arvanil, an endocannabinoid and vanilloid hybrid, in rats." Life Sciences 83, no. 3-4 (July 2008): 85–91. http://dx.doi.org/10.1016/j.lfs.2008.04.023.

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Adebayo-Ojo, Temitope Christina, Janine Wichmann, Oluwaseyi Olalekan Arowosegbe, Nicole Probst-Hensch, Christian Schindler, and Nino Künzli. "Short-Term Joint Effects of PM10, NO2 and SO2 on Cardio-Respiratory Disease Hospital Admissions in Cape Town, South Africa." International Journal of Environmental Research and Public Health 19, no. 1 (January 3, 2022): 495. http://dx.doi.org/10.3390/ijerph19010495.

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Background/Aim: In sub-Sahara Africa, few studies have investigated the short-term association between hospital admissions and ambient air pollution. Therefore, this study explored the association between multiple air pollutants and hospital admissions in Cape Town, South Africa. Methods: Generalized additive quasi-Poisson models were used within a distributed lag linear modelling framework to estimate the cumulative effects of PM10, NO2, and SO2 up to a lag of 21 days. We further conducted multi-pollutant models and stratified our analysis by age group, sex, and season. Results: The overall relative risk (95% confidence interval (CI)) for PM10, NO2, and SO2 at lag 0–1 for hospital admissions due to respiratory disease (RD) were 1.9% (0.5–3.2%), 2.3% (0.6–4%), and 1.1% (−0.2–2.4%), respectively. For cardiovascular disease (CVD), these values were 2.1% (0.6–3.5%), 1% (−0.8–2.8%), and −0.3% (−1.6–1.1%), respectively, per inter-quartile range increase of 12 µg/m3 for PM10, 7.3 µg/m3 for NO2, and 3.6 µg/m3 for SO2. The overall cumulative risks for RD per IQR increase in PM10 and NO2 for children were 2% (0.2–3.9%) and 3.1% (0.7–5.6%), respectively. Conclusion: We found robust associations of daily respiratory disease hospital admissions with daily PM10 and NO2 concentrations. Associations were strongest among children and warm season for RD.

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Kirkman, E., and S. Watts. "Characterization of the response to primary blast injury." Philosophical Transactions of the Royal Society B: Biological Sciences 366, no. 1562 (January 27, 2011): 286–90. http://dx.doi.org/10.1098/rstb.2010.0249.

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Lung injuries, predominantly arising from blast exposure, are a clinical problem in a significant minority of current military casualties. This special feature consists of a series of articles on lung injury. This first article examines the mechanism of the response to blast lung (primary blast injury to the lung). Subsequent articles examine the incidence of blast lung, clinical consequences and current concepts of treatment, computer ( in silico ) modelling of lung injury and finally chemical injuries to the lungs. Blast lung is caused by a shock wave generated by an explosion causing widespread damage in the lungs, leading to intrapulmonary haemorrhage. This, and the ensuing inflammatory response in the lung, leads to a compromise in pulmonary gas exchange and hypoxia that can worsen over several hours. There is also a characteristic cardio-respiratory effect mediated via an autonomic reflex causing apnoea (or rapid shallow breathing), bradycardia and hypotension (the latter possibly also due to the release of nitric oxide). An understanding of this response, and the way it modifies other reflexes, can help the development of new treatment strategies for this condition and for the way it influences the patient's response to concomitant injuries.

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Kopczyńska, Beata. "The contribution of VR1 and CB1 receptors and the role of the afferent vagal pathway in modelling of cardio-respiratory effects of anandamide in rats." Life Sciences 80, no. 19 (April 2007): 1738–45. http://dx.doi.org/10.1016/j.lfs.2007.01.062.

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Brown, Kimberly, Valerie Andrews, Patricia Lea, Figaro Loresto, Maranatha McLean, Oma Morey, Jose Rojas, and Tammy Young. "Board #108 - Research Abstract Using Reflective Writing to Assess Impact of an Inter-Professional Cardio-Pulmonary Workshop for Medical, Nursing and Respiratory Therapy Students (Submission #8645)." Simulation in Healthcare: Journal of the Society for Simulation in Healthcare 9, no. 6 (December 2014): 400. http://dx.doi.org/10.1097/01.sih.0000459278.23632.cd.

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Rytsar, Romana, Smilja Djurdjevic, Alexander K. Nussbaum, Ashok Kaul, Emanuel Bennewitz, Peter N. Lee, and John S. Fry. "Estimated Public Health Gains From German Smokers Switching to Reduced-Risk Alternatives: Results From Population Health Impact Modelling." Contributions to Tobacco & Nicotine Research 31, no. 1 (March 1, 2022): 35–51. http://dx.doi.org/10.2478/cttr-2022-0004.

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Summary Background Smoking is associated with cancer and cardio-respiratory mortality. Reducing smoking prevalence will lead to fewer deaths and more life-years. Here, we estimate the impact of hypothetical introduction of reduced-risk products (heat-not-burn products and e-cigarettes) in Germany from 1995 to 2015 on mortality from lung cancer, chronic obstructive pulmonary disease, ischaemic heart disease, and stroke in men and women aged 30–79 years. Methods We used a previously described population health impact model, with individuals with a defined baseline cigarette smoking distribution followed under a “Null Scenario”, with reduced-risk products never introduced, and various “Alternative Scenarios” where they are. Transition probabilities allow product use to change annually, with the individual product histories allowing estimation of risks, relative to never users, which are then used to estimate reductions in deaths and life-years lost for each Alternative Scenario. Results In the Null Scenario, we estimated 852,000 deaths from cigarette smoking (42,600 per year), with 8.61 million life-years lost. Had everyone ceased smoking in 1995, and with no use of reduced-risk products, these numbers would reduce by 217,000 and 2.88 million. Compared to the Null Scenario, the estimated reductions would be 159,000 and 2.06 million with an immediate complete switch to heat-not-burn products and 179,000 and 2.34 million with 50% of smokers immediately switching to heat-not-burn products and 50% to e-cigarettes. In four Scenarios with a more gradual switch, the estimated decreases were 39,800–81,000 deaths and 0.50–1.05 million life-years, representing 17.5%–37.5% of the effect of immediate cessation in 1995. These estimates assume that switching to heat-not-burn products and e-cigarettes involves risk decreases of 80% and 95% of those from quitting, respectively. The reductions in mortality would be greater with more diseases and a wider age range considered or with a longer follow-up period, as the decreases increased markedly with time. Various limitations are discussed, none affecting the conclusion that introducing these new products into Germany in 1995 could have substantially reduced deaths and life-years lost. Conclusions Deaths from cigarette smoking could be substantially reduced not only by cessation but additionally by switching to reduced-risk products. Respective public health campaigns might increase such switching.

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Soleimani, Meisam, Axel Haverich, and Peter Wriggers. "Mathematical Modeling and Numerical Simulation of Atherosclerosis Based on a Novel Surgeon’s View." Archives of Computational Methods in Engineering, July 8, 2021. http://dx.doi.org/10.1007/s11831-021-09623-5.

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AbstractThis paper deals with the mathematical modeling of atherosclerosis based on a novel hypothesis proposed by a surgeon, Prof. Dr. Axel Haverich (Circulation 135(3):205–207, 2017). Atherosclerosis is referred as the thickening of the artery walls. Currently, there are two schools of thoughts for explaining the root of such phenomenon: thickening due to substance deposition and thickening as a result of inflammatory overgrowth. The hypothesis favored here is the second paradigm stating that the atherosclerosis is nothing else than the inflammatory response of of the wall tissues as a result of disruption in wall nourishment. It is known that a network of capillaries called vasa vasorum (VV) accounts for the nourishment of the wall in addition to the natural diffusion of nutrient from the blood passing through the lumen. Disruption of nutrient flow to the wall tissues may take place due to the occlusion of vasa vasorums with viruses, bacteria and very fine dust particles such as air pollutants referred to as PM 2.5. They can enter the body through the respiratory system at the first place and then reach the circulatory system. Hence in the new hypothesis, the root of atherosclerotic vessel is perceived as the malfunction of microvessels that nourish the vessel. A large number of clinical observation support this hypothesis. Recently and highly related to this work, and after the COVID-19 pandemic, one of the most prevalent disease in the lungs are attributed to the atherosclerotic pulmonary arteries, see Boyle and Haverich (Eur J Cardio Thorac Surg 58(6):1109–1110, 2020). In this work, a general framework is developed based on a multiphysics mathematical model to capture the wall deformation, nutrient availability and the inflammatory response. For the mechanical response an anisotropic constitutive relation is invoked in order to account for the presence of collagen fibers in the artery wall. A diffusion–reaction equation governs the transport of the nutrient within the wall. The inflammation (overgrowth) is described using a phase-field type equation with a double well potential which captures a sharp interface between two regions of the tissues, namely the healthy and the overgrowing part. The kinematics of the growth is treated by classical multiplicative decomposition of the gradient deformation. The inflammation is represented by means of a phase-field variable. A novel driving mechanism for the phase field is proposed for modeling the progression of the pathology. The model is 3D and fully based on the continuum description of the problem. The numerical implementation is carried out using FEM. Predictions of the model are compared with the clinical observations. The versatility and applicability of the model and the numerical tool allow.

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Violán, Concepción, Sergio Fernández-Bertolín, Marina Guisado-Clavero, Quintí Foguet-Boreu, Jose M. Valderas, Josep Vidal Manzano, Albert Roso-Llorach, and Margarita Cabrera-Bean. "Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models." Scientific Reports 10, no. 1 (October 9, 2020). http://dx.doi.org/10.1038/s41598-020-73231-9.

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Abstract This study aimed to analyse the trajectories and mortality of multimorbidity patterns in patients aged 65 to 99 years in Catalonia (Spain). Five year (2012–2016) data of 916,619 participants from a primary care, population-based electronic health record database (Information System for Research in Primary Care, SIDIAP) were included in this retrospective cohort study. Individual longitudinal trajectories were modelled with a Hidden Markov Model across multimorbidity patterns. We computed the mortality hazard using Cox regression models to estimate survival in multimorbidity patterns. Ten multimorbidity patterns were originally identified and two more states (death and drop-outs) were subsequently added. At baseline, the most frequent cluster was the Non-Specific Pattern (42%), and the least frequent the Multisystem Pattern (1.6%). Most participants stayed in the same cluster over the 5 year follow-up period, from 92.1% in the Nervous, Musculoskeletal pattern to 59.2% in the Cardio-Circulatory and Renal pattern. The highest mortality rates were observed for patterns that included cardio-circulatory diseases: Cardio-Circulatory and Renal (37.1%); Nervous, Digestive and Circulatory (31.8%); and Cardio-Circulatory, Mental, Respiratory and Genitourinary (28.8%). This study demonstrates the feasibility of characterizing multimorbidity patterns along time. Multimorbidity trajectories were generally stable, although changes in specific multimorbidity patterns were observed. The Hidden Markov Model is useful for modelling transitions across multimorbidity patterns and mortality risk. Our findings suggest that health interventions targeting specific multimorbidity patterns may reduce mortality in patients with multimorbidity.

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Sorelli, Michele, T. Noah Hutson, Leonidas Iasemidis, and Leonardo Bocchi. "Linear and Nonlinear Directed Connectivity Analysis of the Cardio-Respiratory System in Type 1 Diabetes." Frontiers in Network Physiology 2 (March 8, 2022). http://dx.doi.org/10.3389/fnetp.2022.840829.

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In this study, we explored the possibility of developing non-invasive biomarkers for patients with type 1 diabetes (T1D) by quantifying the directional couplings between the cardiac, vascular, and respiratory systems, treating them as interconnected nodes in a network configuration. Towards this goal, we employed a linear directional connectivity measure, the directed transfer function (DTF), estimated by a linear multivariate autoregressive modelling of ECG, respiratory and skin perfusion signals, and a nonlinear method, the dynamical Bayesian inference (DBI) analysis of bivariate phase interactions. The physiological data were recorded concurrently for a relatively short time period (5 min) from 10 healthy control subjects and 10 T1D patients. We found that, in both control and T1D subjects, breathing had greater influence on the heart and perfusion with respect to the opposite coupling direction and that, by both employed methods of analysis, the causal influence of breathing on the heart was significantly decreased (p < 0.05) in T1D patients compared to the control group. These preliminary results, although obtained from a limited number of subjects, provide a strong indication for the usefulness of a network-based multi-modal analysis for the development of biomarkers of T1D-related complications from short-duration data, as well as their potential in the exploration of the pathophysiological mechanisms that underlie this devastating and very widespread disease.

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Wang, Xu, Eleni-Rosalina Andrinopoulou, Kevin M. Veen, Ad J. J. C. Bogers, and Johanna J. M. Takkenberg. "Statistical primer: An introduction to the application of linear mixed-effects models in cardiothoracic surgery outcomes research-a case study using homograft pulmonary valve replacement data." European Journal of Cardio-Thoracic Surgery, August 25, 2022. http://dx.doi.org/10.1093/ejcts/ezac429.

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Abstract Objectives The emergence of big cardio-thoracic surgery datasets that include not only short-term and long-term discrete outcomes but also repeated measurements over time, offers the opportunity to apply more advanced modeling of outcomes. This article presents a detailed introduction to developing and interpreting linear mixed-effects models for repeated measurements in the setting of cardiothoracic surgery outcomes research. Methods A retrospective dataset containing serial echocardiographic measurements in patients undergoing surgical pulmonary valve replacement (PVR) from 1986 to 2017 in Erasmus MC was used to illustrate the steps of developing a linear mixed-effects model for clinician-researchers. Results Essential aspects of constructing the model are illustrated with the dataset including theories of linear mixed-effects models, missing values, collinearity, interaction, nonlinearity, model specification, results interpretation, and assumptions evaluation. A comparison between linear regression models and linear mixed-effects models is done to elaborate on the strengths of linear mixed-effects models. An R script is provided for the implementation of the linear mixed-effects model. Conclusions Linear mixed-effects models can provide evolutional details of repeated measurements and give more valid estimates compared to linear regression models in the setting of cardio-thoracic surgery outcomes research.

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Sudha, G., and S. Suguna. "Health Hazard." International journal of health sciences, March 26, 2022, 630–42. http://dx.doi.org/10.53730/ijhs.v6ns2.5066.

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Health of every living being is dependent on level of pollutant in the environment, weather condition, etc, which are interrelated and influencing each other. Presence of pollution particles in high percentage such as particulate matter of size 10 and 2.5 (PM10, PM25) microns in creates higher risk in lung functionality, respiratory disease and reduces cardio functionality; also affects the quality of water sources. Rainfall, technically known as precipitation, occur at non season also create health hazards, seasonal diseases. In our previous work, the relationship between precipitation and pollution were analysed; it is observed that pollution attribute particulate matter, PM2.5, influences precipitation. Pollution data as well as numerical weather data are time series data in nature. This research work analyses the time series data (day wise observations) of pollution and weather, recorded at Chennai city at the year 2017. ARIMA model is constructed after applying required transformations on underlying data. Trend and seasonality found in underlying time series data set are unique since time series components are data-dependent and autocorrelated with previous day observations. Improved forecasting of PM2.5 and precipitation are obtained through ARIMA modelling.

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de Almeida e Bueno, Leonardo, Man Ting Kwong, William R. F. Milnthorpe, Runbei Cheng, and Jeroen H. M. Bergmann. "Applying ubiquitous sensing to estimate perceived exertion based on cardiorespiratory features." Sports Engineering 24, no. 1 (April 22, 2021). http://dx.doi.org/10.1007/s12283-021-00346-1.

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AbstractReliable monitoring of one’s response to exercise intensity is imperative to effectively plan and manage training, but not always practical in impact sports settings. This study aimed to evaluate if an inexpensive mobile cardio-respiratory monitoring system can achieve similar performance to a metabolic cart in estimating rated perceived exertion. Eight adult men volunteered to perform treadmill tests under different conditions. Cardiorespiratory data were collected using a metabolic cart and an instrumented oral-cavity device, as well as their ratings of perceived exertion. Pearson correlation corrected for repeated measurements and stepwise regression analysis were used to observe the relationship between the cardiorespiratory features and the ratings of perceived exertion and determine the proportion of the variance of exertion that could be explained by the measurements. Minute ventilation was found to be the most associated variable to perceived exertion, closely followed by a novel metric called the audio minute volume, which can be collected by the oral-cavity device. A generalised linear model combining minute ventilation, audio minute volume, heart rate and respiration rate accounted for 64% of the variance in perceived exertion, whilst a model with only audio minute volume accounted for 56%. Our study indicates that minute ventilation is key to estimating perceived exertion during indoor running exercises. Audio minute volume was also observed to perform comparably to a lab-based metabolic cart in estimating perceived exertion. This research indicates that mobile techniques offer the potential for real-world data collection of an athlete’s physiological load and estimation of perceived exertion.

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Journal articles on the topic 'Cardio-respiratory modeling'

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