scholarly journals Individual differences in heart rate reveal a broad range of autonomic phenotypes in a free-living seabird population

2018 ◽  
Vol 221 (19) ◽  
pp. jeb182758 ◽  
Author(s):  
Martina S. Müller ◽  
Alexei L. Vyssotski ◽  
Maki Yamamoto ◽  
Ken Yoda
Keyword(s):  
Heart Rate ◽  
Individual Differences ◽  
Free Living ◽  
Seabird Population

Measures of RSA Suppression, Attentional Control, and Negative Affect Predict Self-Ratings of Executive Functions

2011 ◽  
Vol 25 (4) ◽  
pp. 164-173 ◽  
Author(s):  
Brian Healy ◽  
Aaron Treadwell ◽  
Mandy Reagan
Keyword(s):  
College Students ◽  
Heart Rate ◽  
Regression Analysis ◽  
Individual Differences ◽  
Negative Affect ◽  
Respiratory Sinus Arrhythmia ◽  
Attentional Control ◽  
Executive Processes ◽  
Sinus Arrhythmia ◽  
Low Levels

The current study was an attempt to determine the degree to which the suppression of respiratory sinus arrhythmia (RSA) and attentional control were influential in the ability to engage various executive processes under high and low levels of negative affect. Ninety-four college students completed the Stroop Test while heart rate was being recorded. Estimates of the suppression of RSA were calculated from each participant in response to this test. The participants then completed self-ratings of attentional control, negative affect, and executive functioning. Regression analysis indicated that individual differences in estimates of the suppression of RSA, and ratings of attentional control were associated with the ability to employ executive processes but only when self-ratings of negative affect were low. An increase in negative affect compromised the ability to employ these strategies in the majority of participants. The data also suggest that high attentional control in conjunction with attenuated estimates of RSA suppression may increase the ability to use executive processes as negative affect increases.

scholarly journals Accurate Estimation of Heart and Respiration Rates Based on an Optical Fiber Sensor Using Adaptive Regulations and Statistical Classifications Spectrum Analysis

2021 ◽  
Vol 3 ◽  
Author(s):  
Rongjian Zhao ◽  
Lidong Du ◽  
Zhan Zhao ◽  
Xianxiang Chen ◽  
Jie Sun ◽  
...  
Keyword(s):  
Heart Rate ◽  
Individual Differences ◽  
Optical Fiber ◽  
Confidence Intervals ◽  
Respiration Rate ◽  
Spectrum Analysis ◽  
Optical Fiber Sensor ◽  
Fiber Sensor ◽  
Respiration Rates ◽  
The Mean

The aim of this work is to present a method for accurately estimating heart and respiration rates under different actual conditions based on a mattress which was integrated with an optical fiber sensor. During the estimation, a ballistocardiogram (BCG) signal, which was obtained from the optical fiber sensor, was used for extracting the heart rate and the respiration rate. However, due to the detrimental effects of the differential detector, self-interference, and variation of installation status of the sensor, the ballistocardiogram (BCG) signal was difficult to detect. In order to resolve the potential concerns of individual differences and body interferences, adaptive regulations and statistical classifications spectrum analysis were used in this paper. Experiments were carried out to quantify heart and respiration rates of healthy volunteers under different breathing and posture conditions. From the experimental results, it could be concluded that (1) the heart rates of 40–150 beats per minute (bpm) and respiration rates of 10–20 breaths per minute (bpm) were measured for individual differences; (2) for the same individuals under four different posture contacts, the mean errors of heart rates were separately 1.60 ± 0.98 bpm, 1.94 ± 0.83 bpm, 1.24 ± 0.59 bpm, and 1.06 ± 0.62 bpm, in contrast, the mean errors of the polar beat device were 1.09 ± 0.96 bpm, 1.44 ± 0.99 bpm, and 1.78 ± 0.94 bpm. Furthermore, the experimental results were validated by conventional counterparts which used skin-contacting electrodes as their measurements. It was reported that the heart rate was 0.26 ± 2.80 bpm in 95% confidence intervals (± 1.96SD) in comparison with Philips sure-signs VM6 medical monitor, and the respiration rate was 0.41 ± 1.49 bpm in 95% confidence intervals (± 1.96SD) in comparison with ECG-derived respiratory (EDR) measurements for respiration rates. It was indicated that the developed system using adaptive regulations and statistical classifications spectrum analysis performed better and could easily be used under complex environments.

scholarly journals Review of Prediction Models to Estimate Activity-Related Energy Expenditure in Children and Adolescents

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Suzanne M. de Graauw ◽  
Janke F. de Groot ◽  
Marco van Brussel ◽  
Marjolein F. Streur ◽  
Tim Takken
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Prediction Model ◽  
Children And Adolescents ◽  
Prediction Models ◽  
Accurate Estimate ◽  
Healthy Children ◽  
Triaxial Accelerometer ◽  
Free Living ◽  
Doubly Labelled Water

Purpose. To critically review the validity of accelerometry-based prediction models to estimate activity energy expenditure (AEE) in children and adolescents.Methods. The CINAHL, EMBASE, PsycINFO, and PubMed/MEDLINE databases were searched. Inclusion criteria were development or validation of an accelerometer-based prediction model for the estimation of AEE in healthy children or adolescents (6–18 years), criterion measure: indirect calorimetry, or doubly labelled water, and language: Dutch, English or German.Results. Nine studies were included. Median methodological quality was5.5±2.0 IR (out of a maximum 10 points). Prediction models combining heart rate and counts explained 86–91% of the variance in measured AEE. A prediction model based on a triaxial accelerometer explained 90%. Models derived during free-living explained up to 45%.Conclusions. Accelerometry-based prediction models may provide an accurate estimate of AEE in children on a group level. Best results are retrieved when the model combines accelerometer counts with heart rate or when a triaxial accelerometer is used. Future development of AEE prediction models applicable to free-living scenarios is needed.

scholarly journals Validating accelerometry estimates of energy expenditure across behaviours using heart rate data in a free-living seabird

2017 ◽  
Vol 220 (10) ◽  
pp. 1875-1881 ◽  
Author(s):  
Olivia Hicks ◽  
Sarah Burthe ◽  
Francis Daunt ◽  
Adam Butler ◽  
Charles Bishop ◽  
...  
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Rate Data ◽  
Free Living ◽  
Heart Rate Data

scholarly journals Critical evaluation of the factorial and heart-rate recording methods for the determination of energy expenditure of free-living elderly people

1997 ◽  
Vol 78 (5) ◽  
pp. 709-722 ◽  
Author(s):  
Beatrice Morio ◽  
Patrick Ritz ◽  
Elisabeth Verdier ◽  
Christophe Montaurier ◽  
Bernard Beaufrere ◽  
...  
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Elderly People ◽  
Living Conditions ◽  
Energy Costs ◽  
Free Living ◽  
Factorial Method ◽  
Recording Method ◽  
Mean Differences ◽  
Free Living Conditions

The aim of the present study was to validate against the doubly-labelled water (DLW) technique the factorial method and the heart rate (HR) recording method for determining daily energy expenditure (DEE) of elderly people in free-living conditions. The two methods were first calibrated and validated in twelve healthy subjects (six males and six females; 70·1 (sd 2·7) years) from opencircuit whole-body indirect calorimetry measurements during three consecutive days and during 1 d respectively. Mean energy costs of the various usual activities were determined for each subject using the factorial method, and individual relationships were set up between HR and energy expenditure for the HR recording method. In free-living conditions, DEE was determined over the same period of time by the DLW, the factorial and the HR recording methods during 17, 14 and 4 d respectively. Mean free-living DEE values for men estimated using the DLW, the factorial and the HR recording methods were 12·8 (sd 3·1), 12·7 (sd 2·2) and 13·5 (sd 2·7) MJ/d respectively. Mean free-living DEE values for women were 9·6 (sd 0·8), 8·8 (sd 1·2) and 10·2 (sd 1·5) MJ/d respectively. No significant differences were found between the three methods for either sex, using the Bland & Altman (1986) test. Mean differences in DEE of men were -0·9 (sd 11·8) % between the factorial and DLW methods, and +4·7 (sd 16·1) % between the HR recording and DLW methods. Similarly, in women, mean differences were -7·7 (sd 12·7) % between the factorial and DLW methods, and +5·9 (sd 8·8) % between the HR recording and DLW methods. It was concluded that the factorial and the HR recording methods are satisfactory alternatives to the DLW method when considering the mean DEE of a group of subjects. Furthermore, mean energy costs of activities calculated in the present study using the factorial method were shown to be suitable for determining free-living DEE of elderly people when the reference value (i.e. sleeping metabolic rate) is accurately measured.

Validity of combining heart rate and uniaxial acceleration to measure free-living physical activity energy expenditure in young men

2012 ◽  
Vol 113 (11) ◽  
pp. 1763-1771 ◽  
Author(s):  
C. Villars ◽  
A. Bergouignan ◽  
J. Dugas ◽  
E. Antoun ◽  
D. A. Schoeller ◽  
...  
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Intraclass Correlation ◽  
Tolerance Test ◽  
Free Living ◽  
Individual Level ◽  
Individual Calibration ◽  
Old Men ◽  
Activity Energy ◽  
Free Living Conditions

Combining accelerometry (ACC) with heart rate (HR) monitoring is thought to improve activity energy expenditure (AEE) estimations compared with ACC alone to evaluate the validity of ACC and HR used alone or combined. The purpose of this study was to estimate AEE in free-living conditions compared with doubly labeled water (DLW). Ten-day free-living AEE was measured by a DLW protocol in 35 18- to 55-yr-old men (11 lean active; 12 lean sedentary; 12 overweight sedentary) wearing an Actiheart (combining ACC and HR) and a RT3 accelerometer. AEE was estimated using group or individual calibration of the HR/AEE relationship, based on an exercise-tolerance test. In a subset ( n = 21), AEE changes (ΔAEE) were measured after 1 mo of detraining (active subjects) or an 8-wk training (sedentary subjects). Actiheart-combined ACC/HR estimates were more accurate than estimates from HR or ACC alone. Accuracy of the Actiheart group-calibrated ACC/HR estimates was modest [intraclass correlation coefficient (ICC) = 0.62], with no bias but high root mean square error (RMSE) and limits of agreement (LOA). The mean bias of the estimates was reduced by one-third, like RMSE and LOA, by individual calibration (ICC = 0.81). Contrasting with group-calibrated estimates, the Actiheart individual-calibrated ACC/HR estimates explained 40% of the variance of the DLW-ΔAEE (ICC = 0.63). This study supports a good level of agreement between the Actiheart ACC/HR estimates and DLW-measured AEE in lean and overweight men with varying fitness levels. Individual calibration of the HR/AEE relationship is necessary for AEE estimations at an individual level rather than at group scale and for ΔAEE evaluation.

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