Rest heart rate and mortality: More physical exercise for the rabbit?

2013 ◽  
Vol 165 (2) ◽  
pp. 358 ◽  
Author(s):  
Giuseppe Lippi ◽  
Fabian Sanchis-Gomar ◽  
Gianfranco Cervellin
Circulation ◽  
1995 ◽  
Vol 92 (12) ◽  
pp. 3415-3423 ◽  
Author(s):  
Ype S. Tuininga ◽  
Harry J.G.M. Crijns ◽  
Jan Brouwer ◽  
Maarten P. van den Berg ◽  
Arie J. Man in’t Veld ◽  
...  

Metabolism ◽  
2013 ◽  
Vol 62 (5) ◽  
pp. 717-724 ◽  
Author(s):  
Nedim Soydan ◽  
Reinhard G. Bretzel ◽  
Britta Fischer ◽  
Florian Wagenlehner ◽  
Adrian Pilatz ◽  
...  

2019 ◽  
Vol 3 (1) ◽  
pp. 1-4 ◽  
Author(s):  
Lianning Zhu ◽  
Chen Kan ◽  
Yuncheng Du ◽  
Dongping Du

2016 ◽  
Vol 30 (1) ◽  
pp. 79-84 ◽  
Author(s):  
R. E. Carpenter ◽  
S. J. Emery ◽  
O. Uzun ◽  
D. Rassi ◽  
M. J. Lewis

2015 ◽  
Vol 22 (12) ◽  
pp. 2391-2395 ◽  
Author(s):  
Navaneet K. Lakshminarasimha Murthy ◽  
Pavan C. Madhusudana ◽  
Pradyumna Suresha ◽  
Vijitha Periyasamy ◽  
Prasanta Kumar Ghosh

2021 ◽  
Vol 12 (1) ◽  
pp. 89-102
Author(s):  
Bjørn-Jostein Singstad ◽  
Naomi Azulay ◽  
Andreas Bjurstedt ◽  
Simen S. Bjørndal ◽  
Magnus F. Drageseth ◽  
...  

Abstract Due to the possibilities in miniaturization and wearability, photoplethysmography (PPG) has recently gained a large interest not only for heart rate measurement, but also for estimating heart rate variability, which is derived from ECG by convention. The agreement between PPG and ECG-based HRV has been assessed in several studies, but the feasibility of PPG-based HRV estimation is still largely unknown for many conditions. In this study, we assess the feasibility of HRV estimation based on finger PPG during rest, mild physical exercise and mild mental stress. In addition, we compare different variants of signal processing methods including selection of fiducial point and outlier correction. Based on five minutes synchronous recordings of PPG and ECG from 15 healthy participants during each of these three conditions, the PPG-based HRV estimation was assessed for the SDNN and RMSSD parameters, calculated based on two different fiducial points (foot point and maximum slope), with and without outlier correction. The results show that HRV estimation based on finger PPG is feasible during rest and mild mental stress, but can give large errors during mild physical exercise. A good estimation is very dependent on outlier correction and fiducial point selection, and SDNN seems to be a more robust parameter compared to RMSSD for PPG-based HRV estimation.


2020 ◽  
Vol 20 (2) ◽  
pp. 63-70
Author(s):  
Felipe de Ornelas ◽  
Danilo Rodrigues Batista ◽  
Vlademir Meneghel ◽  
Wellington Gonçalves Dias ◽  
Guilherme Borsetti Businari ◽  
...  

Physical inactivity is main cause of disease worldwide. Identify the physical exercise preference, resulting in increases adherence and future intention to perform physical activity. The preference of the intensity of exercise questionnaire (PRETIE-Q) is the main tool used to assess preference in physical exercise. Variables as age, body mass index (BMI), usual physical activity level (PAL), maximal oxygen uptake (VO2máx), can influence in PRETIE-Q answers. The purpose of this study was investigate if there is relation between preference for exercise intensity with maximal aerobic speed (MAS), PAL and heart rate variability (HRV) in postmenopausal women phase. Participated of study 30 subjects who answer PRETIE-Q together with analyses of MAS, PAL and HRV. Preference was large correlated with MAS (r = 0.63), PAL (r = 0.57) and HRVRMSSD (r = 0.52). Together, MAS (40.4%), PAL (10.7%) and HRVRMSSD (6.4%) explained 57.5% of the preference score. This results study allow to health professional, that prescribe physical exercise, understand that subjects with high aerobic capacity, cardiovagal modulation and usual PAL will have preference for high intensity exercise. In consequence, can increase the adherence to systematic practice of physical exercise. Conclude that preference of exercise intensity for women in postmenopausal phase is related with aerobic capacity, high HRV and physical activity level.


Author(s):  
Sugiono Sugiono ◽  
Sudjito Suparman ◽  
Teguh Oktiarso ◽  
Willy Satrio

Employee durability is a critical factor to improve a company performance. Company management must control employee health conditions. The purpose of this paper is to determine the effect of office worker’s BMI variation on human energy expenditure behavior including the recovery process. This study started with literature reviews of BMI, human biology, energy expenditure, and physiology ergonomics. The data was collected randomly from 126 nonphysical office workers in productive ages from 20 to 40 years old. The BMI, resting heart rate, activity heart rate, and recovery heart rate of all respondents then recorded. The results shows that the respondents BMI scores are classified into underweight (BMI <18.5) with totaling = 4%, healthy weight (18.5 ≤ BMI ≤ 22.9) = 34.1%, light obesity (23 ≤ BMI ≤ 24.9) = 23%, medium obesity (25 ≤ BMI ≤ 29.9) = 29.4%, and weight obesity (BMI> 30) = 9.5%. The underweight class has the lowest average rest heart rate = 68.6 bpm and the overweight class has the highest average rest heart rate = 84.6 bpm. Consequently, heart rate during activity for each class from underweight to overweight is 88.4 bpm, 90.9 bpm, 93.3 bpm, 95.1 bpm, and 98.6 bpm. With the same order, the heart rate reduction percentage during the recovery phase is 4.6%, 11.0%, 13.1%, 16.0%, and 8.8%. In brief, the BMI variation strongly correlated with Time to Recovery (TTR) of nonphysical office workers.


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