scholarly journals Obesity, Nutrition and Heart Rate Variability

2021 ◽  
Vol 22 (8) ◽  
pp. 4215
Author(s):  
Anna Strüven ◽  
Christina Holzapfel ◽  
Christopher Stremmel ◽  
Stefan Brunner
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Weight Reduction ◽  
Dietary Intervention ◽  
Special Focus ◽  
Heart Rate Monitoring ◽  
Self Monitoring ◽  
Additional Tool ◽  
External Stimuli ◽  
Electrocardiogram Ecg

Heart rate variability (HRV) represents the activity and balance of the autonomic nervous system and its capability to react to internal and external stimuli. As a measure of general body homeostasis, HRV is linked to lifestyle factors and it is associated with morbidity and mortality. It is easily accessible by heart rate monitoring and gains interest in the era of smart watches and self-monitoring. In this review, we summarize effects of weight loss, training, and nutrition on HRV with a special focus on obesity. Besides weight reduction, effects of physical activity and dietary intervention can be monitored by parameters of HRV, including its time and frequency domain components. In the future, monitoring of HRV should be included in any weight reduction program as it provides an additional tool to analyze the effect of body weight on general health and homeostasis. HRV parameters could, for example, be monitored easily by implementation of an electrocardiogram (ECG) every two to four weeks during weight reduction period. Indices presumibly showing beneficial changes could be a reduction in heart rate and the number of premature ventricular complexes as well as an increase in standard deviation of normal-to-normal beat intervals (SDNN), just to name some.

scholarly journals Differential effects of the blood pressure state on pulse rate variability and heart rate variability in critically ill patients

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Elisa Mejía-Mejía ◽  
James M. May ◽  
Mohamed Elgendi ◽  
Panayiotis A. Kyriacou
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Pulse Rate ◽  
Pulse Transit Time ◽  
Pulse Rate Variability ◽  
Physiological Factors ◽  
Ecg Signals ◽  
Non Invasive ◽  
Electrocardiogram Ecg

AbstractHeart rate variability (HRV) utilizes the electrocardiogram (ECG) and has been widely studied as a non-invasive indicator of cardiac autonomic activity. Pulse rate variability (PRV) utilizes photoplethysmography (PPG) and recently has been used as a surrogate for HRV. Several studies have found that PRV is not entirely valid as an estimation of HRV and that several physiological factors, including the pulse transit time (PTT) and blood pressure (BP) changes, may affect PRV differently than HRV. This study aimed to assess the relationship between PRV and HRV under different BP states: hypotension, normotension, and hypertension. Using the MIMIC III database, 5 min segments of PPG and ECG signals were used to extract PRV and HRV, respectively. Several time-domain, frequency-domain, and nonlinear indices were obtained from these signals. Bland–Altman analysis, correlation analysis, and Friedman rank sum tests were used to compare HRV and PRV in each state, and PRV and HRV indices were compared among BP states using Kruskal–Wallis tests. The findings indicated that there were differences between PRV and HRV, especially in short-term and nonlinear indices, and although PRV and HRV were altered in a similar manner when there was a change in BP, PRV seemed to be more sensitive to these changes.

scholarly journals Musical Rhythms Affect Heart Rate Variability: Algorithm and Models

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Hui-Min Wang ◽  
Sheng-Chieh Huang
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
High Frequency ◽  
Physiological Model ◽  
Psychological Model ◽  
Two Measures ◽  
Electrocardiogram Ecg ◽  
Musical Rhythms ◽  
Increased Valence ◽  
Affect Heart Rate

There were a lot of psychological music experiments and models but there were few psychological rhythm experiments and models. There were a lot of physiological music experiments but there were few physiological music models. There were few physiological rhythm experiments but there was no physiological rhythm model. We proposed a physiological rhythm model to fill this gap. Twenty-two participants, 4 drum loops as stimuli, and electrocardiogram (ECG) were employed in this work. We designed an algorithm to map tempo, complexity, and energy into two heart rate variability (HRV) measures, the standard deviation of normal-to-normal heartbeats (SDNN) and the ratio of low- and high-frequency powers (LF/HF); these two measures form the physiological valence/arousal plane. There were four major findings. Initially, simple and loud rhythms enhanced arousal. Secondly, the removal of fast and loud rhythms decreased arousal. Thirdly, fast rhythms increased valence. Finally, the removal of fast and quiet rhythms increased valence. Our work extended the psychological model to the physiological model and deepened the musical model into the rhythmic model. Moreover, this model could be the rules of automatic music generating systems.

scholarly journals Sex Differences in Time-Domain and Frequency-Domain Heart Rate Variability Measures of Fatigued Drivers

2020 ◽  
Vol 17 (22) ◽  
pp. 8499
Author(s):  
Chao Zeng ◽  
Wenjun Wang ◽  
Chaoyang Chen ◽  
Chaofei Zhang ◽  
Bo Cheng
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sex Differences ◽  
Frequency Domain ◽  
Time Domain ◽  
Mental States ◽  
Male And Female ◽  
Frequency Domain Methods ◽  
The Difference ◽  
Electrocardiogram Ecg

The effects of fatigue on a driver’s autonomic nervous system (ANS) were investigated through heart rate variability (HRV) measures considering the difference of sex. Electrocardiogram (ECG) data from 18 drivers were recorded during a simulator-based driving experiment. Thirteen short-term HRV measures were extracted through time-domain and frequency-domain methods. First, differences in HRV measures related to mental state (alert or fatigued) were analyzed in all subjects. Then, sex-specific changes between alert and fatigued states were investigated. Finally, sex differences between alert and fatigued states were compared. For all subjects, ten measures showed significant differences (Mann-Whitney U test, p < 0.01) between different mental states. In male and female drivers, eight and four measures, respectively, showed significant differences between different mental states. Six measures showed significant differences between males and females in an alert state, while ten measures showed significant sex differences in a fatigued state. In conclusion, fatigue impacts drivers’ ANS activity, and this impact differs by sex; more differences exist between male and female drivers’ ANS activity in a fatigued state than in an alert state.

scholarly journals Effect of a weight reduction program on baseline and stress-induced heart rate variability in children with obesity

Obesity ◽  
2015 ◽  
Vol 24 (2) ◽  
pp. 439-445 ◽  
Author(s):  
Nazar Mazurak ◽  
Helene Sauer ◽  
Katja Weimer ◽  
Dirk Dammann ◽  
Stephan Zipfel ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Weight Reduction ◽  
Weight Reduction Program ◽  
Reduction Program

scholarly journals Fractal Based Analysis of the Influence of Odorants on Heart Activity

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Hamidreza Namazi ◽  
Vladimir V. Kulish
Keyword(s):  
Heart Rate ◽  
Heart Diseases ◽  
Approximate Entropy ◽  
Ecg Signal ◽  
Heart Activity ◽  
Heart Research ◽  
Olfactory Stimuli ◽  
Important Challenge ◽  
External Stimuli ◽  
Electrocardiogram Ecg

Abstract An important challenge in heart research is to make the relation between the features of external stimuli and heart activity. Olfactory stimulation is an important type of stimulation that affects the heart activity, which is mapped on Electrocardiogram (ECG) signal. Yet, no one has discovered any relation between the structures of olfactory stimuli and the ECG signal. This study investigates the relation between the structures of heart rate and the olfactory stimulus (odorant). We show that the complexity of the heart rate is coupled with the molecular complexity of the odorant, where more structurally complex odorant causes less fractal heart rate. Also, odorant having higher entropy causes the heart rate having lower approximate entropy. The method discussed here can be applied and investigated in case of patients with heart diseases as the rehabilitation purpose.

scholarly journals Heart Rate Variability Time Analyses of the Streptozotocin- Diabetic Rat

2007 ◽  
Vol 4 (1) ◽  
pp. 64
Author(s):  
M. Jacobson ◽  
F.C. Howarth ◽  
E. Adeghate ◽  
K. Fatima-Shad
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Diabetic Rat ◽  
Physiological Effects ◽  
Short Term ◽  
The World ◽  
Electrocardiogram Ecg ◽  
Prevalence Of Diabetes Mellitus ◽  
Streptozotocin Diabetic Rat

As the world prevalence of diabetes mellitus (DM) increases, animal models of the disease's progression are required for researching effective treatment. The streptozotocin (STZ) treated rat is known to cause hyperglycaemia. This study confirms that this animal model also displays DM physiological effects in the animal heart rate (HR) and heart rate variability (HRV). In particular, 5 minutes of rat (n=13) electrocardiogram (ECG) is acquired hourly for 30 days. At day 10, the animal (n=7) is dosed with STZ and the ECG is analyzed in order to determine the HR and HRV. The HRV is indexed using two time-based analyses, based on long-term (24hr) and short-term (5min) analyses. All analyses are compared to control non-STZ dosed animals (n=6) and display significant DM effects. 

HRV

2020 ◽  
pp. 236-264
Author(s):  
Kirti Rawal ◽  
Gaurav Sethi ◽  
Barjinder Singh Saini ◽  
Indu Saini
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Input Signal ◽  
Medical Tourism ◽  
Ecg Signal ◽  
Rr Intervals ◽  
Experimental Protocols ◽  
Hrv Analysis ◽  
Electrocardiogram Ecg ◽  
Electrical Interference

The most important factor involved in heart rate variability (HRV) analysis is cardiac input signal, which is achieved in the form of electrocardiogram (ECG). The ECG signal is used for identifying many electrical defects associated with the heart. In this chapter, many issues involved while ECG recording such as type of the recording instrument, various sources of noise, artifacts, and electrical interference from surroundings is presented. Most importantly, this chapter comprises the details about the experimental protocols followed while ECG recording. Also, the brief overview of medical tourism as well as various interpolation methods used for pre-processing of RR intervals are presented in this chapter.

scholarly journals Heart Rate Monitoring Sensor Based on Singlemode-Multimode-Singlemode Fiber

2019 ◽  
Vol 10 (2) ◽  
pp. 186-193
Author(s):  
Ninik Irawati ◽  
Agus Muhamad Hatta ◽  
Yoseph Gita Yhun Yhuwana ◽  
Sekartedjo
Keyword(s):  
Heart Rate ◽  
High Stability ◽  
Pulse Signal ◽  
Fiber Structure ◽  
Heart Rate Monitoring ◽  
Structure Changes ◽  
Optical Output ◽  
Structure Monitoring ◽  
Electrocardiogram Ecg

AbstractThe singlemode-multimode-singlemode (SMS) fiber structure for a heart rate monitoring is proposed and developed. An artificial electrocardiogram (ECG) signal is used to simulate the heart pulse at different rates ranging from 50 beats per minute (bpm) to 200 bpm. The SMS fiber structure is placed at the center of a loudspeaker and it senses the vibration of the pulse. The vibration of the pulse signal applied to the SMS fiber structure changes the intensity of the optical output power. The proposed sensor shows a linear frequency of the heart rate sensing range that matches well with the relevant heart rate from the artificial ECG. This work shows the capability of the SMS fiber structure monitoring the heart rate frequencies for a long term, high stability realization, and reproducibility, and being suitable for the observation in hospitals as well as in other environments.

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