scholarly journals Towards The Estimation Of The Fractal Dimension Of Heart Rate Variability Data

10.5580/86 ◽  
2005 ◽  
Vol 2 (1) ◽  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Fractal Dimension ◽  
Variability Data

Emotion Recognition from Heart Rate Variability Data of Smartwatch While Watching a Video

2021 ◽  
Author(s):  
Reika Takeshita ◽  
Aya Shoji ◽  
Tahera Hossain ◽  
Anna Yokokubo ◽  
Guillaume Lopez
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Emotion Recognition ◽  
Variability Data

Investigating fractal dimension, heart rate variability, and memory during different image sequencing regimes in young adults

2020 ◽  
Vol 30 (11) ◽  
pp. 113116
Author(s):  
David Aguillard ◽  
Vanessa Zarubin ◽  
Caroline Wilson ◽  
Katherine R. Mickley Steinmetz ◽  
Carolyn Martsberger
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Young Adults ◽  
Fractal Dimension

Typoloagical characteristics of the functional state of regulatory systems in schoolchildren and young athletes (According to Heart Rate Variability Data)

2009 ◽  
Vol 35 (6) ◽  
pp. 730-738 ◽  
Author(s):  
N. I. Shlyk ◽  
E. N. Sapozhnikova ◽  
T. G. Kirillova ◽  
V. G. Semenov
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Functional State ◽  
Young Athletes ◽  
Regulatory Systems ◽  
Variability Data

scholarly journals Behavioral and Physiological Differences between Working Horses and Chilean Rodeo Horses in a Handling Test

Animals ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 397 ◽  
Author(s):  
Paula Rosselot ◽  
Tiago Mendonça ◽  
Igor González ◽  
Tamara Tadich
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Physiological Responses ◽  
Group Differences ◽  
Monitor System ◽  
The Novel ◽  
Non Invasive ◽  
Lower Variability ◽  
Variability Data ◽  
Selection Of

Non-invasive measures are preferred when assessing animal welfare. Differences in behavioral and physiological responses toward a stressor could be the result of the selection of horses for specific uses. Behavioral and physiological responses of working and Chilean rodeo horses subjected to a handling test were assessed. Five behaviors, number of attempts, and the time to cross a bridge were video recorded and analyzed with the Observer XT software. Heart rate (HR) and heart rate variability (HRV), to assess the physiological response to the novel stimulus, were registered with a Polar Equine V800 heart rate monitor system during rest and the bridge test. Heart rate variability data were obtained with the Kubios software. Differences between working and Chilean rodeo horses were assessed, and within-group differences between rest and the test were also analyzed. Chilean rodeo horses presented more proactive behaviors and required significantly more attempts to cross the bridge than working horses. Physiologically, Chilean rodeo horses presented lower variability of the heart rate than working horses.

scholarly journals Direct application of an ECG-based sleep staging algorithm on reflective photoplethysmography data decreases performance

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
M. M. van Gilst ◽  
B. M. Wulterkens ◽  
P. Fonseca ◽  
M. Radha ◽  
M. Ross ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Direct Application ◽  
Alternative Methods ◽  
Sleep Staging ◽  
Practical Application ◽  
Sleep Monitoring ◽  
Data Source ◽  
Variability Data ◽  
Ecg Data

Abstract Objective The maturation of neural network-based techniques in combination with the availability of large sleep datasets has increased the interest in alternative methods of sleep monitoring. For unobtrusive sleep staging, the most promising algorithms are based on heart rate variability computed from inter-beat intervals (IBIs) derived from ECG-data. The practical application of these algorithms is even more promising when alternative ways of obtaining IBIs, such as wrist-worn photoplethysmography (PPG) can be used. However, studies validating sleep staging algorithms directly on PPG-based data are limited. Results We applied an automatic sleep staging algorithm trained and validated on ECG-data directly on inter-beat intervals derived from a wrist-worn PPG sensor, in 389 polysomnographic recordings of patients with a variety of sleep disorders. While the algorithm reached moderate agreement with gold standard polysomnography, the performance was significantly lower when applied on PPG- versus ECG-derived heart rate variability data (kappa 0.56 versus 0.60, p < 0.001; accuracy 73.0% versus 75.9% p < 0.001). These results show that direct application of an algorithm on a different source of data may negatively affect performance. Algorithms need to be validated using each data source and re-training should be considered whenever possible.

Comparison of Heart Rate Recovery Following Exercise to Device-Based Heart Rate Variability Data

2006 ◽  
Vol 12 (6) ◽  
pp. S66
Author(s):  
Michael P. Husby ◽  
Steve Eddy ◽  
Satish Goel ◽  
David B. De Lurgio
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Heart Rate Recovery ◽  
Variability Data

Anova-Based Method for Hurst Exponent Estimation of Heart Rate Variability Sequences

2014 ◽  
Vol 12 (1) ◽  
pp. 9-14
Author(s):  
G. Georgieva-Tsaneva ◽  
M. Dimitrova
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Information Systems ◽  
Comparative Analysis ◽  
Hurst Exponent ◽  
Medical Information ◽  
Medical Data ◽  
Medical Information Systems ◽  
Variability Data

Abstract A method for determination of the Hurst exponent based on Analysis of Variance for processing of medical data sequences is proposed in the paper. It is compared to the “rescaled adjusted range method” developed by Hurst and applied in this paper to heart rate variability data. The obtained results and the performed comparative analysis demonstrate the possibility for effective application of the proposed method in novel medical information systems.

Scaling patterns of heart rate variability data

2007 ◽  
Vol 28 (6) ◽  
pp. 721-730 ◽  
Author(s):  
E R Bojorges-Valdez ◽  
J C Echeverría ◽  
R Valdés-Cristerna ◽  
M A Peña
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Variability Data

Applying fractal analysis to short sets of heart rate variability data

2009 ◽  
Vol 47 (7) ◽  
pp. 709-717 ◽  
Author(s):  
M. A. Peña ◽  
J. C. Echeverría ◽  
M. T. García ◽  
R. González-Camarena
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Fractal Analysis ◽  
Variability Data
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