scholarly journals THE RELATIONSHIP BETWEEN HEART RATE AND CARDIAC FUNCTION DURING HYPOXIA-ASPHYXIA IN NEWBORN PIGLETS

2018 ◽  
Vol 34 (10) ◽  
pp. S97
Author(s):  
W. Shen ◽  
X. Xu ◽  
T. Lee ◽  
M. Lu ◽  
G. Schmolzer ◽  
...  
Keyword(s):  
Heart Rate ◽  
Cardiac Function ◽  
Newborn Piglets ◽  
The Relationship

scholarly journals The effects of an angiotensin-converting inhibitor (enalapril) on patients with mild cardiac failure-evaluating cardiac function based on the relationship between daily walking pace and heart rate

1998 ◽  
Vol 21 (12) ◽  
pp. 893-898 ◽  
Author(s):  
Eji Ino-Oka ◽  
Showko Umeda ◽  
Yoshiharu Kutsuwa ◽  
Takashi Takahashi ◽  
Kouichi Sagawa ◽  
...  
Keyword(s):  
Heart Rate ◽  
Cardiac Function ◽  
Cardiac Failure ◽  
The Relationship

scholarly journals Usability of Wearable Devices With a Novel Cardiac Force Index for Estimating the Dynamic Cardiac Function: Observational Study (Preprint)

2019 ◽  
Author(s):  
Po-Jen Hsiao ◽  
Chih-Chien Chiu ◽  
Ke-Hsin Lin ◽  
Fu-Kang Hu ◽  
Pei-Jan Tsai ◽  
...  
Keyword(s):  
Heart Rate ◽  
Waist Circumference ◽  
Cardiac Function ◽  
Prediction Model ◽  
Fold Increase ◽  
Physiological Parameters ◽  
Long Distance ◽  
Running Performance ◽  
Study Results ◽  
The Relationship

BACKGROUND Long-distance running can be a form of stress to the heart. Technological improvements combined with the public’s gradual turn toward mobile health (mHealth), self-health, and exercise effectiveness have resulted in the widespread use of wearable exercise products. The monitoring of dynamic cardiac function changes during running and running performance should be further studied. OBJECTIVE We investigated the relationship between dynamic cardiac function changes and finish time for 3000-meter runs. Using a wearable device based on a novel cardiac force index (CFI), we explored potential correlations among 3000-meter runners with stronger and weaker cardiac functions during running. METHODS This study used the American product BioHarness 3.0 (Zephyr Technology Corporation), which can measure basic physiological parameters including heart rate, respiratory rate, temperature, maximum oxygen consumption, and activity. We investigated the correlations among new physiological parameters, including CFI = weight * activity / heart rate, cardiac force ratio (CFR) = CFI of running / CFI of walking, and finish times for 3000-meter runs. RESULTS The results showed that waist circumference, smoking, and CFI were the significant factors for qualifying in the 3000-meter run. The prediction model was as follows: ln (3000 meters running performance pass probability / fail results probability) = –2.702 – 0.096 × [waist circumference] – 1.827 × [smoke] + 0.020 × [ACi7]. If smoking and the ACi7 were controlled, contestants with a larger waist circumference tended to fail the qualification based on the formula above. If waist circumference and ACi7 were controlled, smokers tended to fail more often than nonsmokers. Finally, we investigated a new calculation method for monitoring cardiac status during exercise that uses the CFI of walking for the runner as a reference to obtain the ratio between the cardiac force of exercise and that of walking (CFR) to provide a standard for determining if the heart is capable of exercise. A relationship is documented between the CFR and the performance of 3000-meter runs in a healthy 22-year-old person. During the running period, data are obtained while participant slowly runs 3000 meters, and the relationship between the CFR and time is plotted. The runner’s CFR varies with changes in activity. Since the runner’s acceleration increases, the CFR quickly increases to an explosive peak, indicating the runner’s explosive power. At this period, the CFI revealed a 3-fold increase (CFR=3) in a strong heart. After a time lapse, the CFR is approximately 2.5 during an endurance period until finishing the 3000-meter run. Similar correlation is found in a runner with a weak heart, with the CFR at the beginning period being 4 and approximately 2.5 thereafter. CONCLUSIONS In conclusion, the study results suggested that measuring the real-time CFR changes could be used in a prediction model for 3000-meter running performance.

scholarly journals Usability of Wearable Devices With a Novel Cardiac Force Index for Estimating the Dynamic Cardiac Function: Observational Study

10.2196/15331 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e15331 ◽  
Author(s):  
Po-Jen Hsiao ◽  
Chih-Chien Chiu ◽  
Ke-Hsin Lin ◽  
Fu-Kang Hu ◽  
Pei-Jan Tsai ◽  
...  
Keyword(s):  
Heart Rate ◽  
Waist Circumference ◽  
Cardiac Function ◽  
Prediction Model ◽  
Fold Increase ◽  
Physiological Parameters ◽  
Long Distance ◽  
Running Performance ◽  
Study Results ◽  
The Relationship

Background Long-distance running can be a form of stress to the heart. Technological improvements combined with the public’s gradual turn toward mobile health (mHealth), self-health, and exercise effectiveness have resulted in the widespread use of wearable exercise products. The monitoring of dynamic cardiac function changes during running and running performance should be further studied. Objective We investigated the relationship between dynamic cardiac function changes and finish time for 3000-meter runs. Using a wearable device based on a novel cardiac force index (CFI), we explored potential correlations among 3000-meter runners with stronger and weaker cardiac functions during running. Methods This study used the American product BioHarness 3.0 (Zephyr Technology Corporation), which can measure basic physiological parameters including heart rate, respiratory rate, temperature, maximum oxygen consumption, and activity. We investigated the correlations among new physiological parameters, including CFI = weight * activity / heart rate, cardiac force ratio (CFR) = CFI of running / CFI of walking, and finish times for 3000-meter runs. Results The results showed that waist circumference, smoking, and CFI were the significant factors for qualifying in the 3000-meter run. The prediction model was as follows: ln (3000 meters running performance pass probability / fail results probability) = –2.702 – 0.096 × [waist circumference] – 1.827 × [smoke] + 0.020 × [ACi7]. If smoking and the ACi7 were controlled, contestants with a larger waist circumference tended to fail the qualification based on the formula above. If waist circumference and ACi7 were controlled, smokers tended to fail more often than nonsmokers. Finally, we investigated a new calculation method for monitoring cardiac status during exercise that uses the CFI of walking for the runner as a reference to obtain the ratio between the cardiac force of exercise and that of walking (CFR) to provide a standard for determining if the heart is capable of exercise. A relationship is documented between the CFR and the performance of 3000-meter runs in a healthy 22-year-old person. During the running period, data are obtained while participant slowly runs 3000 meters, and the relationship between the CFR and time is plotted. The runner’s CFR varies with changes in activity. Since the runner’s acceleration increases, the CFR quickly increases to an explosive peak, indicating the runner’s explosive power. At this period, the CFI revealed a 3-fold increase (CFR=3) in a strong heart. After a time lapse, the CFR is approximately 2.5 during an endurance period until finishing the 3000-meter run. Similar correlation is found in a runner with a weak heart, with the CFR at the beginning period being 4 and approximately 2.5 thereafter. Conclusions In conclusion, the study results suggested that measuring the real-time CFR changes could be used in a prediction model for 3000-meter running performance.

Emotional Experiences of Students in the Classroom

2010 ◽  
Vol 15 (2) ◽  
pp. 142-151 ◽  
Author(s):  
Wondimu Ahmed ◽  
Greetje van der Werf ◽  
Alexander Minnaert
Keyword(s):  
Heart Rate ◽  
Emotional Response ◽  
Task Difficulty ◽  
Physiological Reactivity ◽  
Emotional Experiences ◽  
Heart Rate Monitoring ◽  
Coding Scheme ◽  
Stimulated Recall ◽  
Response Systems ◽  
The Relationship

In this article, we report on a multimethod qualitative study designed to explore the emotional experiences of students in the classroom setting. The purpose of the study was threefold: (1) to explore the correspondence among nonverbal expressions, subjective feelings, and physiological reactivity (heart rate changes) of students’ emotions in the classroom; (2) to examine the relationship between students’ emotions and their competence and value appraisals; and (3) to determine whether task difficulty matters in emotional experiences. We used multiple methods (nonverbal coding scheme, video stimulated recall interview, and heart rate monitoring) to acquire data on emotional experiences of six grade 7 students. Concurrent correspondence analyses of the emotional indices revealed that coherence between emotional response systems, although apparent, is not conclusive. The relationship between appraisals and emotions was evident, but the effect of task difficulty appears to be minimal.

The Relationship Between Mindfulness and Heart Rate Variability

2010 ◽  
Author(s):  
Erin V. Rodgers ◽  
Raymond Fleming ◽  
Aaryn R. Schuster
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
The Relationship

The Relationship between Heart Rate Variability and Metabolic Syndrome at a Rural Area

2004 ◽  
Vol 16 (4) ◽  
pp. 459
Author(s):  
Kyoung Bok Min ◽  
Jin Young Min ◽  
Kyung Hee Jung-Choi ◽  
Hyung Joon Jhun ◽  
Sung Il Cho ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Rural Area ◽  
The Relationship
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