Jaroslav Novak

The relationship between anaerobic performance and muscle metabolic capacity and fibre distribution

SummaryRelationships between functional anaerobic indicators and the character of cellular muscle energy metabolism were studied. Twelve untrained male students were tested by a specific anaerobic test on the treadmill. The mean values of the anaerobic test were as follows: blood lactate 10.69 mmol · 1−1, running speed 16.08 km · h−1 and duration 92.67 s. The average distribution of muscle fibres (m. vastus lateralis) was: type I 52.2%, type II A 29.0% and type II B 18.8%. The mean enzyme activity values were: triosephosphate dehydrogenase (TPDH) 4.67 Μkat · g−1 w.w., lactate dehydrogenase (LDH) 5.76 Μkat · g−1 w.w, citrate synthase (CS) 0.21 Μkat · g−1 w.w. and hydroxyacyl-CoA dehydrogenase (HAD) 0.12 Μkat · g−1 w.w. Significant negative correlations were found between δLA and CS (r=0.64) and % of fibre type II B and CS (r=0.78) and positive correlations between % of fibre type I and CS and/or HAD (r=0.60 andr=0.62, respectively).

Models of Physiological Parameters for Runners and Cyclists

The study of physiological parameters dynamic is currently the main area of research in exercise physiology. The most common physiological data to collect include heart rate, oxygen saturation, core body and skin temperature, blood pressure, ECG, oxygen consumption and others. The data obtained are often related to various forms and intensities of physical activity, and in accordance with the principles of personalized medicine evaluated. Mathematical models are able to simulate some physiological parameters e.g. heart rate, oxygen consumption etc. during cycling exercise on bicycle ergometer or running exercise on treadmill. Workload intensity (in Watts) on bicycle ergometer and running velocity (in km/h) on the treadmill are taken as input for dynamic models. Determination of dynamic models of physiological parameters is fundamental for athletic training methodology, as well as evaluation of cardiorespiratory capacity and fitness. The present work demonstrates the application of dynamic systems models to the simulation of heart rate kinetics and oxygen consumption during workloads of time-varying intensity. Optimization of free model parameters could be used as important information about the health condition of the subject with special reference to the cardiorespiratory capacity and fitness age. The models could be used both for athletes as well as for untrained sedentary population.

Indirect Cardiac Output and Stroke Volume Assessment During Spiroergometric Examination

Cardiac output can be accurately estimated from VO2 (oxygen consumption) during exercise in normal subjects and in patients with heart failure by measuring the LAT (lactate acidosis threshold) or VO2peak (peak oxygen consumption) during bicycle ergometer test. Hence, during step-vice increased workload on bicycle ergometer with continuous measurement of oxygen consumption changes in cardiac output and stroke volume (SV) can be calculated. Our measurement documented usefulness of this method in subjects of different performance level, both men and women. Non-invasive evaluation of cardiac output and stroke volume during spiroergometric stress test enables to extent the information about the health status of the subject and about the functional reserve of his circulatory apparatus. The examples presented in this study prove the applicability of this method in evaluation of fitness level in healthy male and female subjects of different age. The data of cardiac output and stroke volume will be added into the software program of final protocol of complex sports medical examination. This method can enrich the scale of parameters testifying the functional capacity of the subjects.

High-Sensitivity Troponins after a Standardized 2-Hour Treadmill Run

Summary The aim of this study was to examine high-sensitivity troponin T and I (hsTnT and hsTnI) after a treadmill run under laboratory conditions and to find a possible connection with echocardiographic, laboratory and other assessed parameters. Nineteen trained men underwent a standardized 2-hour-long treadmill run. Concentrations of hsTnT and hsTnI were assessed before the run, 60, 120 and 180 minutes after the start and 24 hours after the run. Changes in troponins were tested using non-parametric analysis of variance (ANOVA). The multiple linear regression model was used to find the explanatory variables for hsTnT and hsTnI changes. Values of troponins were evaluated using the 0h/1h algorithm. Changes in hsTnT and hsTnI levels were statistically significant (p<0.0001 and p<0.0001, respectively). In a multiple regression model (adjusted R2: 0.60, p=0.005 for hsTnT and adjusted R2: 0.60, p=0.005 for hsTnI), changes in both troponins can be explained by relative left wall thickness (LV), training volume, body temperature after the run and creatinine changes. According to the 0h/1h algorithm, none of the runners was evaluated as negative. Relative LV wall thickness, creatinine changes, training volume and body temperature after the run can predict changes in hsTnT and hsTnI levels. When medical attention is needed after physical exercise, hsTn levels should be tested only when clinical suspicion and the patient’s history indicate a high probability of myocardial damage.

Dynamic models of some physiological parameters in response to exercise

The study of physiological parameters dynamic is currently the main area of research in exercise physiology. Finding dynamical models of heart rate, oxygen uptake, pulmonary ventilation and other parameters is fundamental for training methodology in sport, as well as for our knowledge of cardiorespiratory health. The present work demonstrates the application of dynamic systems models to the simulation of heart rate kinetics and oxygen consumption during workloads of time-varying intensity. The use of modern mathematical methods of analysis such as the model parameters estimation could be beneficial for understanding the relationship between the physiological responses to load and/or athletic performance, for identifying certain features in the physiological time series. As a result, the application of such methods for analysis and modeling will have a large impact not only on the development and better understanding training methodology and the testing data of athletes but also in the area of exercise medicine.

Modeling of heart rate during exercise

The study of physiological parameters dynamic is currently the main area of research in exercise physiology. Finding dynamical models of heart rate, oxygen uptake, pulmonary ventilation and other parameters is fundamental for training methodology in sport, as well as for our knowledge of cardiorespiratory health. The present work demonstrates the application of dynamic systems models to the simulation of heart rate kinetics during workloads The simulation results compared with real measured data are presented.

Use of accelerometer for walk-run or shot analysis for sport and rehabilitation purposes

Human movement analysis is a research field with clinical and biometrics application. It has been shown useful in the objective measurement of gait, balance, falls risk assessment and mobility monitoring. Running and/or walking are also integral activities to most athletic disciplines. From a technological point of view, biometric walk-run recognition can be categorized into three approaches: machine vision based, floor sensor based and wearable sensor based. In this paper the accelerometer-based walk-run and shot measuring system is described. The results can be used for medical and sport purposes and also for biometric identification. The electronic system and results of measurement walk-run under laboratory conditions have been presented.

Optimalization of recovery, regeneration and rehabilitation

Scientific objectives Physically active subjects have superior aerobic performance and effort tolerance compared to the less active subjects. There was observed association between high exercise capacity and low mortality. The protective effect of physical activity and exercise capacity preventing the progression of diseases, and thus on premature death, could be one of explanations for this association. Most of this protection is assumed to result from the beneficial effects of physical exercise on blood lipids, blood pressure, glucose metabolism, vascular function, autonomic tone, blood coagulation, and inflammation.