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Journal articles on the topic 'Heart rate calculation'

Author: Grafiati
Published: 23 June 2021
Last updated: 2 February 2022

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1

Connolly, Declan A. J. "How Accurate Is Your Training Heart Rate Calculation?" Strength and Conditioning Journal 24, no. 5 (2002): 15–16. http://dx.doi.org/10.1519/00126548-200210000-00004.

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2

Sedliar, I. "Calculation the intensity of aerobic exercise in fitness." Scientific Journal of National Pedagogical Dragomanov University. Series 15. Scientific and pedagogical problems of physical culture (physical culture and sports), no. 12(120) (December 25, 2019): 105–9. http://dx.doi.org/10.31392/npu-nc.series15.2019.12(120)19.21.

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According to the vast majority of experts, aerobic exercises are basic in fitness. Their effectiveness in the practice involves the rational regulation of load parameters, one of which is the intensity of exercises. However as practice shows the proposed methods for determining the necessary intensity of aerobic exercises do not quite adequately take into account the individual characteristics - age and fitness level.
 The purpose of the research is to evaluate methods for calculating intensity of aerobic exercise in fitness. In our studies we proceeded from the fact that calculation meth
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3

Kołodziej, Marcin, Andrzej Majkowski, Remigiusz J. Rak, Bartosz Świderski, and Andrzej Rysz. "System for automatic heart rate calculation in epileptic seizures." Australasian Physical & Engineering Sciences in Medicine 40, no. 3 (2017): 555–64. http://dx.doi.org/10.1007/s13246-017-0557-z.

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4

Ahmad, Imteyaz. "A Time Domain Method for Calculation of Heart Rate Variability." International Journal of Computer Applications 176, no. 40 (2020): 14–17. http://dx.doi.org/10.5120/ijca2020920482.

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5

Chabot, Denis, Max Bayer, and André de Roos. "Instantaneous heart rates and other techniques introducing errors in the calculation of heart rate." Canadian Journal of Zoology 69, no. 4 (1991): 1117–20. http://dx.doi.org/10.1139/z91-156.

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Data on heart rate can be analyzed in terms of beats per unit of time (heart rate) or its reciprocal, time per beat (interbeat interval). We show that counting beats (including fractions), averaging interbeat intervals, and measuring the time for a fixed number of beats are correct techniques to measure heart activity within observation periods. QRS counts are less precise, but not systematically biased. Conversely, averaging instantaneous heart rates always overestimates true heart rate. Arithmetic means across trials of equal duration are correct only when heart activity for each trial is ex
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6

Sedliar, Iurii. "Calculation of the intensity of health improving aerobic loads." Scientific Journal of National Pedagogical Dragomanov University. Series 15. Scientific and pedagogical problems of physical culture (physical culture and sports), no. 5(125) (September 27, 2020): 135–39. http://dx.doi.org/10.31392/npu-nc.series15.2020.5(125).27.

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The article analyzes the methods of calculating the intensity of aerobic health-improving loads and presents own solution the problem.
 The effective use of aerobic exercises is based on the formula calculation of the parameters of physical activity corresponding to the individual characteristics of the practitioners, among which one of the most important is intensity. However, the practical application of the proposed formulas indicates that they do not always adequately take into account the most important, in this case, age characteristics and the functional state of the cardiovascular
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7

Sharpley, Christopher F. "Differences in pulse rate and heart rate and effects on the calculation of heart rate reactivity during periods of mental stress." Journal of Behavioral Medicine 17, no. 1 (1994): 99–109. http://dx.doi.org/10.1007/bf01856885.

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8

Rajib, R. U. D., Moon Ho Lee, Shadiul Hoque, Rayhan Sharif, and Syeedur Rahman. "Heart Rate Calculation by Using Filtering Module Analysis from Electrocardiogram Data." Advanced Science, Engineering and Medicine 6, no. 1 (2014): 108–10. http://dx.doi.org/10.1166/asem.2014.1463.

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9

Lu, Yujia, Ping Du, Xiaotian Xiong, Lang Qian, Jianrong Ou, and Jinqu Zhang. "A Heart Rate Calculation Method Based on Dynamic Rectangular Window Interception." Journal of Physics: Conference Series 1168 (February 2019): 022038. http://dx.doi.org/10.1088/1742-6596/1168/2/022038.

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10

ChuDuc, Hoang, Phyllis K. Stein, and Hung PhamManh. "Effect of Calculation Algorithm on Heart Rate Variability by Chaos Theory." International Journal of Electronics and Electrical Engineering 1, no. 3 (2013): 145–48. http://dx.doi.org/10.12720/ijeee.1.3.145-148.

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11

Shelley, Kirk H. "Photoplethysmography: Beyond the Calculation of Arterial Oxygen Saturation and Heart Rate." Anesthesia & Analgesia 105, On Line Suppl. (2007): S31—S36. http://dx.doi.org/10.1213/01.ane.0000269512.82836.c9.

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12

Toth-Laufer, Edit, and Annamaria R. Varkonyi-Koczy. "Personal-Statistics-Based Heart Rate Evaluation in Anytime Risk Calculation Model." IEEE Transactions on Instrumentation and Measurement 64, no. 8 (2015): 2127–35. http://dx.doi.org/10.1109/tim.2014.2376111.

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13

Li, Zhang Yong, Xiao Bo Chen, Rui Leng, and Fei Ba Chang. "Measure Energy Consumption Combined Heart Rate and Acceleration." Advanced Materials Research 680 (April 2013): 597–601. http://dx.doi.org/10.4028/www.scientific.net/amr.680.597.

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This paper put forward a new kind of motion energy expenditure calculation model that combine movement heart rate, acceleration, height, gender, age, weight and other personalized parameters. In this model, using heart rate and personalized parameters to calculate the based energy consumption (BEE). Using acceleration and personalized parameters to calculate the movement work (EEact). The experimental results show that this method has a high accuracy in movement energy expenditure. So using this method can eliminate the contradiction between measurement accuracy and measuring cost.
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14

Zhang, Lu, Mei-Jia Huang, and Hui-Jin Wang. "A Novel Technique for Fetal Heart Rate Estimation Based on Ensemble Learning." Modern Applied Science 13, no. 10 (2019): 137. http://dx.doi.org/10.5539/mas.v13n10p137.

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The autocorrelation algorithm is the most commonly used method for extracting fetal heart rate from ultrasound Doppler fetal monitors. The traditional autocorrelation algorithm can not always extract the detection cycle accurately. During the calculation process, the heartbeat cycle may not be recognized, or the cycle may be doubled or halved recognized. Combining the characteristics of envelope curve with average magnitude difference function curve, this paper designs a set of extreme point search scheme and a fetal heart cycle recognition model based on ensemble learning to assist in screeni
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15

KUO, CHENG-DENG, YUH-SHOW TSAI, YAR-YI WANG, and BENJAMIN N. CHIANG. "THE HEART RATE AND HEART RATE VARIABILITY AFTER COMMENCEMENT OF EXERCISE ARE FRACTALS." Fractals 03, no. 02 (1995): 391–402. http://dx.doi.org/10.1142/s0218348x95000308.

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It is already well known that exercise can result in acceleration of heart rate (HR) and progressive withdrawal of vagal activity. However, the ways in which HR and the heart rate variability (HRV) change progressively during the initial stage of exercise have not been fully investigated. The aim of this study is to find a suitable mathematical description for the temporal evolutions of HR and HRV after the initiation of exercise, and to search for possible relation between HR and HRV during exercise in normal subjects. The index of HRV used in this study was the standard deviation (SD) of the
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16

Nagovitsyn, Roman, Elena Chelnokova, Olga Vaganova, Zhanna Smirnova, and Maxim Kutepov. "Calorimetry of students’ heart rate during exercises of various intensity." BIO Web of Conferences 26 (2020): 00033. http://dx.doi.org/10.1051/bioconf/20202600033.

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The purpose of the study: based on data analysis, to develop a formula for calorimetry of students’ heart rate during physical activity and experimentally prove the effectiveness of its application in the training process. The study participants (n=98) were divided by body weight into groups (n=7), regardless of gender and age (20-25 years). Various mobile devices with the function of heart rate calculation and monitoring of kilocalories burning were used in the implementation of control physical activities at different levels of intensity. Analysis of the obtained calorimetric data for each g
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17

Tejera, E., A. Plain, A. Portelinha, J. L. H. Caceres, I. Rebelo, and J. M. Nieto-Villar. "Heart Rate Variability Complexity in the Aging Process." Computational and Mathematical Methods in Medicine 8, no. 4 (2007): 287–96. http://dx.doi.org/10.1080/17486700701776413.

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In the present work, we propose a discrete model to the characterization of heart rate variability (HRV) complexity in the aging process of healthy subjects. We apply the Shannon entropy on the basis of an alternative way to probability calculation and to define a new index taking into consideration the transition probability that is related to the physiological complexity of the system. Our results suggest that in the aging process the capability response decreases according to the reduction of the physiological complexity. In the oldest group, an alternative mechanism emerges to compensate f
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18

Kashtalyan, O. A., and M. S. Prystrom. "Echocardiography indices, heart rate variability and cytokine profile in pregnant women." "Arterial’naya Gipertenziya" ("Arterial Hypertension") 15, no. 5 (2009): 585–89. http://dx.doi.org/10.18705/1607-419x-2009-15-5-585-589.

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Objective. To analyze heart rhythm variability, hemodinamics, pro- and anti-inflammatory plasma cytokines production in pregnant women. General clinical examination was carried out in both groups, echocardiography, Holter monitoring with subsequent calculation of generally accepted heart rate variability indices were performed. The circadian heart rate index (ratio day/night) was calculated. It was found that pregnancy-induced hypertension was accompanied by impaired cytokine balance. Altered immune homeostasis has been established to be a leading factor in the pattern of gestational complicat
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19

Hasibuan, Desima Klaudia, and Indra Hardian Mulyadi. "Real-Time Heart Rate Monitoring for Wearable Electrocardiography Using Filter-Based and Peak Threshold Algorithms: A Comparative Study." JURNAL INTEGRASI 10, no. 2 (2018): 54–58. http://dx.doi.org/10.30871/ji.v10i2.983.

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Wearable and wireless Electrocardiograph (ECG) enables real-time and long-term monitoring of heart rate (i.e. 24 hours). Several algorithms have been introduced to increase the accuracy of the heart rate calculation for this type of ECG. This study aims to compare the accuracy of two heart rate calculation algorithms: Filter-Based and Peak Threshold. Both algorithms were implemented into a wearable ECG prototype comprising AD8232, 8-bit microcontroller (ATMega328), and Bluetooth. ECG signals and heart rate (in Beat per Minute (BPM)) were sent via Bluetooth and displayed in real-time on a Windo
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20

Moran, Daniel, Yoram Epstein, Gad Keren, Arie Laor, Jack Sherez, and Yair Shapiro. "Calculation of Mean Arterial Pressure During Exercise as a Function of Heart Rate." Applied Human Science 14, no. 6 (1995): 293–95. http://dx.doi.org/10.2114/ahs.14.293.

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21

Liu, Nehemiah T., Andriy I. Batchinsky, José Salinas, and Leopoldo C. Cancio. "Robust real-time calculation of heart-rate complexity using multiple noisy waveform sources." Journal of Critical Care 28, no. 1 (2013): e15-e16. http://dx.doi.org/10.1016/j.jcrc.2012.10.046.

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22

Химикова, O. Khimikova, Эльман, et al. "Comparative characteristics of heart rate variability parameters of Yugra pupils." Complexity. Mind. Postnonclassic 4, no. 2 (2015): 11–20. http://dx.doi.org/10.12737/12006.

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This article presents a comparative analysis of the parameters of HRV students who are indigenous and non-indigenous residents of Yugra. Analysis was carried out carried out by multiple comparisons of three age subgroups and by multivariate analysis with the calculation of inter-cluster distances. The differences in the dynamics of age-related changes of Yugra schoolchildren reveals distinctive trend parameters of heart rate variability between indigenous and non-indigenous representatives of North. In particular, it revealed a higher adaptive capacity in Aboriginal representatives in comparis
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23

Casaleggio, A., S. Cerutti, and M. G. Signorini. "Study of the Lyapunov Exponents in Heart Rate Variability Signals." Methods of Information in Medicine 36, no. 04/05 (1997): 274–77. http://dx.doi.org/10.1055/s-0038-1636877.

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Abstract:Heart rate variability signals obtained from 24 h recordings are analyzed for normal and pathological subjects. This time series contains information about the autonomic nervous system action regulating the beat-to-beat heart rate. Nonlinear contributions to the long period variability have been assessed by the calculation of the entire spectrum of Lyapunov exponents, after the system trajectory reconstruction, starting from the original variability signal. The positivity of Lyapunov exponent values, obtained from an unknown process, can establish whether the structure generating it s
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24

Zhang, Yisong, Song Zhang, Lin Yang, et al. "A study of a fetal heart rate calculation system based on R-R interval." Technology and Health Care 28 (June 4, 2020): 187–95. http://dx.doi.org/10.3233/thc-209019.

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25

Yahya H., Mohammed, Ali Adil Turki, Ali H. F. Alnasraui, and Qasim shaker K. "Calculation of Heart Rate Variation Owing to the Effect of Electromagnetic Fields Waves (EMF)." Journal of Kufa Physics 10, no. 2 (2018): 48–53. http://dx.doi.org/10.31257/2018/jkp/100207.

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26

Huang, Mei-Jia, and Hui-Jin Wang. "Automated Detection of Fetal Movements Based on Baseline Calculation and Fetal Heart Rate Accelerations." Modern Applied Science 12, no. 9 (2018): 173. http://dx.doi.org/10.5539/mas.v12n9p173.

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Fetal electronic monitoring is extensive and important in obstetrics. Although fetal movement is ususally used as an important indicator for quantifying fetal wellbeing, non-invasive and long-term monitoring of fetal movement remains challenging. The object of this study is to develop an algorithm for automatic detection of the fetal movements based on the analysis of Doppler ultrasound signals. In order to detect fetal movements automatically, a two-step process was proposed to track fetal movement. In Step 1, to suppress the problem of error detection, we calculated the baseline of the fetal
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27

Nikulina, A., I. Tuyzarova, R. Shukanov, N. Altynova, and A. Shukanov. "ANALYSIS OF THE CARDIOVASCULAR SYSTEM IN SIMULATED CONDITIONS." Human Sport Medicine 19, no. 3 (2019): 7–13. http://dx.doi.org/10.14529/hsm190301.

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Aim. The article deals with establishing the correlations between the anthropometric, hemodynamic, and vegetative tone indicators in first and second-year students during their adaptation to university conditions. The morphophysiological status of students was corrected by Selenes+ and additional physical load. Materials and methods. Students aged 17–20 years (n = 60) participated in a longitudinal study. The following physiological methods were used: body length and mass measurement; BMI calculation; detection of selenium in blood serum; systolic and diastolic pressure measurement; heart rate
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28

Magrupova, M. T., and Yo T. Talatov. "Systematic Approach to Processing and Analysis Diagnostic Indicators of Electrocardiograms Based on Labview." Journal of the Russian Universities. Radioelectronics 23, no. 2 (2020): 82–88. http://dx.doi.org/10.32603/1993-8985-2020-23-2-82-88.

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Introduction. Cardiovascular disease occupies an important place throughout the world, which necessitates the development of more effective modern means of diagnosis and treatment. The primary diagnosis of heart disease is based on analysis and processing of an electrocardiogram (ECG). Despite the fact that there are many methods and algorithms for ECG analysis and processing, one of the urgent problems of cardiology remains to obtain the most complete information about heart electric potential, respectively, the behavior of the waves P, Q, R, S and T.Aim. Development of algorithms and softwar
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Gleich, Bernhard, Thomas Weyh, and Bernhard Wolf. "Magnetic Drug Targeting: An Analytical Model for the Influence of Blood Properties on Particle Trajectories." Applied Rheology 18, no. 5 (2008): 52023–1. http://dx.doi.org/10.1515/arh-2008-0016.

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Abstract Investigations on the behaviour of superparamagnetic nanoparticles under the influence of a high gradient magnetic field in the vascular system is required for a better under-standing of magnetic drug targeting. The influence on the particle transport of the non-Newtonian and Newtonian properties of blood as well as the influence of the heart rate was therefore studied. A analytical model was developed and the calculation of particle trajectories is presented and evaluated. The results show that the non-Newtonian properties of the blood have a positive influence on the number of reten
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30

MUS, K. "10.6 Comparison of fft and DFT algorithms in calculation of heart rate variability spectral parameters." Europace 4 (October 2003): A17. http://dx.doi.org/10.1016/s1099-5129(02)90077-2.

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31

Mus, K., A. Zienciuk, A. Lubinski, et al. "10.6 Comparison of fft and DFT algorithms in calculation of heart rate variability spectral parameters." EP Europace 4, Supplement_1 (2003): A17. http://dx.doi.org/10.1016/eupace/4.supplement_1.a17-c.

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32

Putri, Elsya Vira. "The Correlation between Physical Workload and the Increase in Workers’ Pulse Rate." Indonesian Journal of Occupational Safety and Health 8, no. 2 (2019): 206. http://dx.doi.org/10.20473/ijosh.v8i2.2019.206-214.

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Introduction: The workload that exceeds individual work capacity will increase the pulse rate rapidly. The purpose of this research was to study the correlation between physical workload and the increase in workers’ pulse rate. Methods: This research utilized cross-sectional design by using the observational method with 23 workers from the BRF area of PT X Sidoarjo as respondents. This research was conducted by conducting the direct observation by calculating the workload received by the worker by using %CVL method and calculating the resting and working heart rates. Results: The result showed
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33

Lee, Dae-Young, and Young-Seok Choi. "Multiscale Distribution Entropy Analysis of Short-Term Heart Rate Variability." Entropy 20, no. 12 (2018): 952. http://dx.doi.org/10.3390/e20120952.

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Electrocardiogram (ECG) signal has been commonly used to analyze the complexity of heart rate variability (HRV). For this, various entropy methods have been considerably of interest. The multiscale entropy (MSE) method, which makes use of the sample entropy (SampEn) calculation of coarse-grained time series, has attracted attention for analysis of HRV. However, the SampEn computation may fail to be defined when the length of a time series is not enough long. Recently, distribution entropy (DistEn) with improved stability for a short-term time series has been proposed. Here, we propose a novel
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Wierig, Maren, Leonard Mandtler, Peter Rottmann, et al. "Recording Heart Rate Variability of Dairy Cows to the Cloud—Why Smartphones Provide Smart Solutions." Sensors 18, no. 8 (2018): 2541. http://dx.doi.org/10.3390/s18082541.

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In the last decades, there has been an increasing interest in animal protection and welfare issues. Heart rate variability (HRV) measurement with portable heart rate monitors on cows has established itself as a suitable method for assessing physiological states. However, more forward-looking technologies, already successfully applied to evaluate HRV data, are pushing the market. This study examines the validity and usability of collecting HRV data by exchanging the Polar watch V800 as a receiving unit of the data compared to a custom smartphone application on cows. Therefore, both receivers ta
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35

Cao, Ping, Bailu Ye, Linghui Yang, et al. "Preprocessing Unevenly Sampled RR Interval Signals to Enhance Estimation of Heart Rate Deceleration and Acceleration Capacities in Discriminating Chronic Heart Failure Patients from Healthy Controls." Computational and Mathematical Methods in Medicine 2020 (March 31, 2020): 1–10. http://dx.doi.org/10.1155/2020/9763826.

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Objective. The deceleration capacity (DC) and acceleration capacity (AC) of heart rate, which are recently proposed variants to the heart rate variability, are calculated from unevenly sampled RR interval signals using phase-rectified signal averaging. Although uneven sampling of these signals compromises heart rate variability analyses, its effect on DC and AC analyses remains to be addressed. Approach. We assess preprocessing (i.e., interpolation and resampling) of RR interval signals on the diagnostic effect of DC and AC from simulation and clinical data. The simulation analysis synthesizes
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36

Butler, G. C., Y. Yamamoto, H. C. Xing, D. R. Northey, and R. L. Hughson. "Heart rate variability and fractal dimension during orthostatic challenges." Journal of Applied Physiology 75, no. 6 (1993): 2602–12. http://dx.doi.org/10.1152/jappl.1993.75.6.2602.

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Heart rate variability (HRV) spectral analysis has been used as a tool for short-term assessment of parasympathetic (PNS) and sympathetic nervous system (SNS) control of heart rate. However, it has been suggested that the PNS and SNS indicators are superimposed on a broad-band noise spectrum in which the power spectral densities are inversely proportional to their frequency (1/f beta). In this study, we have used coarse-graining spectral analysis to extract the harmonic components for calculation of PNS and SNS indicators and to obtain the slope (beta) of the 1/f beta component to estimate fra
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37

Устименко, A. Ustimenko, Третьяков, et al. "Thermodynamic and chaotic approaches for assessing the age dynamics of cardiovascular system in khanty-woman." Journal of New Medical Technologies. eJournal 8, no. 1 (2014): 0. http://dx.doi.org/10.12737/7355.

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Cardiorespiratory system is the most important part of the body, which provides high life expectancy. Special parameters of heart rate dynamics require the development of new approaches for analysis and prediction. The paper presents a comparison of the effective traditional statistical methods, the conventional (in physics) thermodynamic methods, with methods of chaos theory and self-organization to estimate the parameters of heart rate three age groups of Khanty-women in the aspect of identification of their age characteristics. It is proved that there are few statistical differences between
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38

Sufri, Saiful, and Aswardi Aswardi. "Alat Pendeteksi Detak Jantung dan Kesehatan Berbasis Arduino." JTEIN: Jurnal Teknik Elektro Indonesia 1, no. 2 (2020): 69–75. http://dx.doi.org/10.24036/jtein.v1i2.31.

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The heart is a human organ that pumps blood. The heart contracts, where one contraction cycle is usually called a heartbeat. Calculation of heart rate is often done manually by counting the pulse on the wrist for one minute. This method is considered inaccurate because it only relies on the human sense of touch. By making it easier to calculate the heart rate with the Electrocardiograph (ECG) device only but this tool is used in hospitals and cannot be moved. With a sensor that makes daily activities easier. For example, a pulse sensor that is easily available is a pulse sensor that can be use
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Guo, Chenghu, Mingjun Xu, Yu Zhang, et al. "RESTING HEART RATE DISTURBED THE CALCULATION OF CORONARY FLOW RESERVE IN PATIENTS WITH CORONARY MICROVASCULAR DISEASE." Journal of the American College of Cardiology 75, no. 11 (2020): 1782. http://dx.doi.org/10.1016/s0735-1097(20)32409-8.

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40

Atsumi, Bunji, Seiichi Sugiura, and Kenji Kimura. "Evaluation of Mental Work Load in Vehicle Driving by Analysis of Heart Rate Variability." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 37, no. 9 (1993): 574–78. http://dx.doi.org/10.1177/154193129303700912.

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This paper discusses the mental work load index in vehicle driving and operation of various instruments by the use of the analysis method of heart rate variability. According to what has been reported previously, the heart rate (HR) and the respiratory sinus arrhythmia (RSA) is obtained by the FFT analysis of the R-R Interval. However, the calculation to obtain RSA by the FFT method has a drawback in that it is so complicated that it is impossible to detect dynamic mental variation. Therefore, we have devised a new method of calcurating RSA, which calculates the R-R variability (RRV) at each 3
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Нерсисян, N. Nersisyan, Шакирова, et al. "Dynamics of spectral power of heart rate variability in students the latitudinal movement." Journal of New Medical Technologies. eJournal 10, no. 1 (2016): 0. http://dx.doi.org/10.12737/18602.

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In the conditions of sanatorium treatment the parameters of the cardiovascular system of schoolchildren with the latitudinal displacements were analyzed. Analysis of parameters of cardiovascular system of children in sanatoria from the position of the stochastics showed that the behavior of RR-intervals is still chaotic. The results of the study revealed that short-term treatment reduces the size of quasi-attractor vector of conditions of the human body and partially normalizes the indicators of the cardio-respiratory system of children. However, after the rest of the distance rX increasing, s
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Suzuki, Satoshi, Takemi Matsui, Keitaro Sugawara, Takafumi Asao, and Kentaro Kotani. "An Approach to Remote Monitoring of Heart Rate Variability (HRV) Using Microwave Radar during a Calculation Task." Journal of PHYSIOLOGICAL ANTHROPOLOGY 30, no. 6 (2011): 241–49. http://dx.doi.org/10.2114/jpa2.30.241.

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43

Yoshida, Yutaka, Kiyoko Yokoyama, and Naohiro Ishii. "Analysis of heart rate variability during breath-holding using fast and continuous calculation of frequency and power." Electronics and Communications in Japan 94, no. 6 (2011): 24–31. http://dx.doi.org/10.1002/ecj.10324.

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44

Pogliaghi, Silvia, Elisa Dussin, Cantor Tarperi, Antonio Cevese, and Federico Schena. "Calculation of oxygen uptake efficiency slope based on heart rate reserve end-points in healthy elderly subjects." European Journal of Applied Physiology 101, no. 6 (2007): 691–96. http://dx.doi.org/10.1007/s00421-007-0545-1.

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Liu, Nehemiah T., Leopoldo C. Cancio, Jose Salinas, and Andriy I. Batchinsky. "Reliable real-time calculation of heart-rate complexity in critically ill patients using multiple noisy waveform sources." Journal of Clinical Monitoring and Computing 28, no. 2 (2013): 123–31. http://dx.doi.org/10.1007/s10877-013-9503-0.

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46

Utomo, T. P., and N. Nuryani. "Photoplethysmogram peaks detection based on moving window integration and threshold for heart rate calculation on android smartphone." Journal of Physics: Conference Series 1825, no. 1 (2021): 012032. http://dx.doi.org/10.1088/1742-6596/1825/1/012032.

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Mikhalyuk, Evgen, Vitaliy Syvolap, Maryna Potapenko, Nikolay Bessarabov, and Sergey Polskoy. "FEATURES OF ELECTROCARDIOGRAPHIC INDICATORS AND DATA OF HEART RATE VARIABILITY IN YOUNG FOOTBALLERS." Science and Education 2020, no. 3 (2020): 57–64. http://dx.doi.org/10.24195/2414-4665-2020-3-8.

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The great importance has recently been attached to studying the functional capabilities of athletes taking into account the data of bioelectric activity of the myocardium, as well as vegetative status based on the analysis of heart rate variability. However, works in which questions regarding the age-related features of the ECG and the autonomic provision of the heart rate for young football players are not enough. In order to clarify the effect of age on ECG and heart rate variability (HRV), a comparative analysis of 5-minute records and standard ECG in 12 leads was conducted for young player
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48

Dai, Changzhi, and Zhiwei Lian. "The effects of sound loudness on subjective feeling, sympathovagal balance and brain activity." Indoor and Built Environment 27, no. 9 (2017): 1287–300. http://dx.doi.org/10.1177/1420326x17719490.

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This study explored the effects of sound loudness on human nervous system from four aspects: regional spontaneous brain activity, cognition performance, sympathovagal balance of the autonomic nervous system and subjective feelings. Functional magnetic resonance imaging and electrocardiogram were measured in 12 volunteered students under three noise conditions. Mental performance, fatigue, noise sensation, annoyance and subjective distraction were also investigated. Earplugs were found invalid to improve annoyance and distraction in a common office condition (45 dB(A)), although noisy feeling w
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49

He, Jiao Long, Shu Guang Chen, and Xin Sheng Zhang. "Research on Technology of Highway Curve and Slope Road Segment Alignment Safety Design." Applied Mechanics and Materials 204-208 (October 2012): 1665–68. http://dx.doi.org/10.4028/www.scientific.net/amm.204-208.1665.

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In the paper, Combination curved with slope road segment on the driving experiment , The paper is analyzed the curve and slope road segment on Gradient, Horizontal Curve Radius, Speed and heart rate these variables of the inherent relation and law. The model of the relationship of the longitudinal slope and horizontal curve radius and heart rate is set up. By employing regression analysis, Conduct quantitative analysis, calculation and can be determined by the minimum horizontal curve radius value of vertical slope corresponding to at different vehicle-speeds on curved with longitudinal slope,
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50

Kulagina, T. Yu, V. A. Sandrikov, R. Z. Zyabirova, J. N. Petrova, V. S. Klimenko, and N. V. Vlasova. "The rate of myocardial contraction in the assessment of diastolic function." Medical alphabet, no. 15 (July 6, 2021): 28–32. http://dx.doi.org/10.33667/2078-5631-2021-15-28-32.

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Objective: to evaluate the results of biomechanics of myocardial contraction during diastole in patients with coronary heart disease based on the results of vector analysisMATERIAL: the study is based on 79 patients with coronary heart disease with myocardial infarction and scarring of the heart muscle aged 53±4 years and 34 healthy volunteers — 41±3 years were examined. Before and after the operation of coronary artery bypass grafting, transthoracic echocardiography was performed, followed by computer image processing and calculation of hemodynamic parameters — EDV, ESV, EF, E\A. Vector analy
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