Machine Learning Driven Heart Rate Detection with Camera Photoplethysmography in Time Domain

2016 ◽  
pp. 324-334 ◽  
Author(s):  
Viktor Kessler ◽  
Markus Kächele ◽  
Sascha Meudt ◽  
Friedhelm Schwenker ◽  
Günther Palm
Keyword(s):  
Machine Learning ◽  
Heart Rate ◽  
Time Domain

scholarly journals Multivariate Analysis for the Classification of Chocolate According to its Percentage of Cocoa by Using Terahertz Time-Domain Spectroscopy (THz-TDS)

Proceedings ◽  
2020 ◽  
Vol 70 (1) ◽  
pp. 109
Author(s):  
Jimy Oblitas ◽  
Jorge Ruiz
Keyword(s):  
Machine Learning ◽  
Time Domain ◽  
Electromagnetic Pulse ◽  
Machine Learning Algorithms ◽  
Classification Models ◽  
Terahertz Time Domain Spectroscopy ◽  
Time Domain Spectroscopy ◽  
Svm Algorithm ◽  
Classification Of Images

Terahertz time-domain spectroscopy is a useful technique for determining some physical characteristics of materials, and is based on selective frequency absorption of a broad-spectrum electromagnetic pulse. In order to investigate the potential of this technology to classify cocoa percentages in chocolates, the terahertz spectra (0.5–10 THz) of five chocolate samples (50%, 60%, 70%, 80% and 90% of cocoa) were examined. The acquired data matrices were analyzed with the MATLAB 2019b application, from which the dielectric function was obtained along with the absorbance curves, and were classified by using 24 mathematical classification models, achieving differentiations of around 93% obtained by the Gaussian SVM algorithm model with a kernel scale of 0.35 and a one-against-one multiclass method. It was concluded that the combined processing and classification of images obtained from the terahertz time-domain spectroscopy and the use of machine learning algorithms can be used to successfully classify chocolates with different percentages of cocoa.

scholarly journals Sleep Indices and Cardiac Autonomic Activity Responses during an International Tournament in a Youth National Soccer Team

2021 ◽  
Vol 18 (4) ◽  
pp. 2076
Author(s):  
Pedro Figueiredo ◽  
Júlio Costa ◽  
Michele Lastella ◽  
João Morais ◽  
João Brito
Keyword(s):  
Heart Rate ◽  
Frequency Domain ◽  
Sleep Duration ◽  
Time Domain ◽  
Soccer Players ◽  
Autonomic Activity ◽  
Male Youth ◽  
Youth Soccer ◽  
Wrist Actigraphy ◽  
Cardiac Autonomic Activity

This study aimed to describe habitual sleep and nocturnal cardiac autonomic activity (CAA), and their relationship with training/match load in male youth soccer players during an international tournament. Eighteen elite male youth soccer players (aged 14.8 ± 0.3 years; mean ± SD) participated in the study. Sleep indices were measured using wrist actigraphy, and heart rate (HR) monitors were used to measure CAA during night-sleep throughout 5 consecutive days. Training and match loads were characterized using the session-rating of perceived exertion (s-RPE). During the five nights 8 to 17 players slept less than <8 h and only one to two players had a sleep efficiency <75%. Players’ sleep duration coefficient of variation (CV) ranged between 4 and 17%. Nocturnal heart rate variability (HRV) indices for the time-domain analyses ranged from 3.8 (95% confidence interval, 3.6; 4.0) to 4.1 ln[ms] (3.9; 4.3) and for the frequency-domain analyses ranged from 5.9 (5.6; 6.5) to 6.6 (6.3; 7.4). Time-domain HRV CV ranged from 3 to 10% and frequency-domain HRV ranged from 2 to 12%. A moderate within-subjects correlation was found between s-RPE and sleep duration [r = −0.41 (−0.62; −0.14); p = 0.003]. The present findings suggest that youth soccer players slept less than the recommended during the international tournament, and sleep duration was negatively associated with training/match load.

scholarly journals Heart rate variability: Analysis of time-domain indices in patients with chronic Chagas disease before and after an exercise program

2013 ◽  
Vol 32 (3) ◽  
pp. 219-227 ◽  
Author(s):  
Marcus Vinicius Amaral da Silva Souza ◽  
Carla Cristiane Santos Soares ◽  
Juliana Rega de Oliveira ◽  
Cláudia Rosa de Oliveira ◽  
Paloma Hargreaves Fialho ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Chagas Disease ◽  
Time Domain ◽  
Exercise Program ◽  
Heart Rate Variability Analysis ◽  
Variability Analysis ◽  
Before And After ◽  
Chronic Chagas Disease

scholarly journals Fetal Heart Rate Analysis for Automatic Detection of Perinatal Hypoxia Using Normalized Compression Distance and Machine Learning

2017 ◽  
Vol 8 ◽  
Author(s):  
Óscar Barquero-Pérez ◽  
Ricardo Santiago-Mozos ◽  
José M. Lillo-Castellano ◽  
Beatriz García-Viruete ◽  
Rebeca Goya-Esteban ◽  
...  
Keyword(s):  
Machine Learning ◽  
Heart Rate ◽  
Fetal Heart Rate ◽  
Fetal Heart ◽  
Automatic Detection ◽  
Perinatal Hypoxia ◽  
Rate Analysis ◽  
Normalized Compression Distance ◽  
Heart Rate Analysis

Effect of short-term mental stress on time- domain indices of heart rate variability in obese individuals – A case- control study

Biomedicine ◽  
2021 ◽  
Vol 41 (2) ◽  
pp. 274-277
Author(s):  
Priya S.A. ◽  
R. Rajalakshmi
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Neuronal Activity ◽  
Time Domain ◽  
Mental Stress ◽  
Mental Arithmetic ◽  
High Body Mass Index ◽  
Control Group ◽  
Stress Task ◽  
The Individual

  Introduction and Aim: Mental stress may impact dramatically on dynamic autonomic control on heart. Many studies have demonstrated association of high body mass index (BMI) with greater risk for cardiovascular disease with disturbance in autonomic neuronal activity. Analysis of Heart rate variability (HRV)during acute mental stress assesses the autonomic status of the individual. Hence, we aimed to study the effect of acute mental stress on time domain measures in obese adults.   Materials and Methods:Sixty male volunteers of 30 each in study group (obese individuals) and control group (non-obese individuals) were recruited for the study. A basal recording of ECG in lead II was done on all the individuals. Then they underwent mental arithmetic stress task for 5 minutes during which again ECG was recorded. The change in time domain measures of HRV during rest and stress task was analyzed and compared between both the groups.   Results: Analysis of time domain measures of HRV revealed a statistically significant increase (p ? 0.001) in mean heart rate in both obese and non-obese individuals, while rMSSD(root mean square differences of successive RR interval) and SDNN (standard deviation of all NN intervals) showed a statistically significant (p? 0.001) decrease in obese individuals and non-obese individuals did not show any statistically significant change during the mental stress task.   Conclusion: In response to acute mental stress there was increased heart rate in both the groups. But the autonomic neuronal activity differed by way of sympathetic dominance in non-obese individuals and parasympathetic withdrawal in obese individuals.  

Estimation of Dog Emotions by Machine Learning Using Heart Rate Data of Other Dogs

2021 ◽  
Vol 2021 (0) ◽  
pp. 2P1-M03
Author(s):  
Kotaro SATO ◽  
Kazunori OHNO ◽  
Ryoichiro TAMURA ◽  
Sandeep Kumar NAYAK ◽  
Shotaro KOJIMA ◽  
...  
Keyword(s):  
Machine Learning ◽  
Heart Rate ◽  
Rate Data ◽  
Heart Rate Data
Sign in / Sign up

Export Citation Format

Share Document