Continuous Heart Rate Variability Monitoring Through Complex Demodulation Implemented with the Fast Fourier Transform and Its Inverse

1995 ◽  
Vol 18 (7) ◽  
pp. 1401-1410 ◽  
Author(s):  
MIGUEL BURGUERA ◽  
RAFAEL GANDIA ◽  
FRANCISCO J. CHORRO ◽  
ROBERTO GARCIA-CIVERA ◽  
RICARDO RUIZ ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Complex Demodulation

scholarly journals Cognición, respuesta electroencefalográfica y su relación con la variabilidad de la frecuencia cardíaca

2017 ◽  
Vol 65 (1) ◽  
pp. 67-72
Author(s):  
Henry Humberto León-Ariza ◽  
Daniel Alfonso Botero-Rosas ◽  
Alveiro Sánchez-Jiménez ◽  
Jhon Fredy Ramírez-Villada ◽  
Edward Javier Acero-Mondragón
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Para Determinar

Introducción. La corteza cerebral frontal tiene una mayor actividad teta durante procesos cognitivos de observación y aprendizaje.Objetivo. Establecer la relación entre actividad electroencefalográfica orbitofrontal y sistema nervioso autónomo en procesos cognitivos.Materiales y métodos. 20 hombres y 19 mujeres con edad promedio de 21.2 (±2.32) años fueron evaluados mediante electroencefalografía (EGG) FP1-T3, FP2-T4 y electrocardiografía (EKG, del alemán elektrokardiogramm) para determinar frecuencia cardíaca (HR, del inglés heart rate) y variabilidad de la frecuencia cardíaca (HRV, del inglés heart rate variability). La evaluación tuvo cinco fases: reposo, observación, memoria, concentración y juego. Las señales de EGG y EKG fueron analizadas en el dominio de la frecuencia usando la transformada rápida de Fourier (FFT, del inglés fast Fourier transform). Las diferencias por etapa entre las variables se establecieron con el uso de ANOVA de dos vías.Resultados. Comparado con el reposo, se observó en todas las fases incremento de la actividad teta del EGG (p<0.01), aumento en la baja frecuencia LF (p<0.01) y la HR (p<0.01) y disminución de la alta frecuencia HF (p<0.01). Además, hubo una correlación inversa entre la actividad teta y la potencia de HF (r=-0.86).Conclusiones. Los datos mostraron una reducción de la actividad parasimpática y un aumento de la actividad simpática asociado a actividad teta de la corteza orbitofrontal, mediante una conexión con el núcleo central de la amígdala.

Comparison of fast Fourier transform and autoregressive spectral analysis for the study of heart rate variability in diabetic patients

2005 ◽  
Vol 104 (3) ◽  
pp. 307-313 ◽  
Author(s):  
Denis Chemla ◽  
Jacques Young ◽  
Fabio Badilini ◽  
Pierre Maison-Blanche ◽  
Hélène Affres ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Diabetic Patients

scholarly journals Is the algorithm used to process heart rate variability data clinically relevant? Analysis in male adolescents

2016 ◽  
Vol 14 (2) ◽  
pp. 196-201 ◽  
Author(s):  
Antonio Henrique Germano Soares ◽  
Breno Quintella Farah ◽  
Gabriel Grizzo Cucato ◽  
Carmelo José Albanez Bastos-Filho ◽  
Diego Giulliano Destro Christofaro ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Total Power ◽  
Cross Sectional ◽  
Negatively Associated ◽  
Male Adolescents

ABSTRACT Objective To analyze whether the algorithm used for the heart rate variability assessment (fast Fourier transform versus autoregressive methods) influenced its association with cardiovascular risk factors in male adolescents. Methods This cross-sectional study included 1,152 male adolescents (aged 14 to 19 years). The low frequency, high frequency components (absolute numbers and normalized units), low frequency/high frequency ratio, and total power of heart rate variability parameters were obtained using the fast Fourier transform and autoregressive methods, while the adolescents were resting in a supine position. Results All heart rate variability parameters calculated from both methods were different (p<0.05). However, a low effect size (<0.1) was found for all parameters. The intra-class correlation between methods ranged from 0.96 to 0.99, whereas the variation coefficient ranged from 7.4 to 14.8%. Furthermore, waist circumference was negatively associated with high frequency, and positively associated with low frequency and sympatovagal balance (p<0.001 for both fast Fourier transform and autoregressive methods in all associations). Systolic blood pressure was negatively associated with total power and high frequency, whereas it was positively associated with low frequency and sympatovagal balance (p<0.001 for both fast Fourier transform and autoregressive methods in all associations). Body mass index was negatively associated with high frequency, while it was positively associated with low frequency and sympatovagal balance (p values ranged from <0.001 to 0.007). Conclusion There are significant differences in heart rate variability parameters obtained with the fast Fourier transform and autoregressive methods in male adolescent; however, these differences are not clinically significant.

Heart rate and heart rate variability of healthy cats in home and hospital environments

2005 ◽  
Vol 7 (3) ◽  
pp. 195-202 ◽  
Author(s):  
Jonathan A Abbott
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Sinus Arrhythmia ◽  
Rr Intervals ◽  
Rr Interval ◽  
Hospital Environments ◽  
Echocardiographic Examination ◽  
Veterinary Hospital

To investigate heart rate and its variability, a telemetry device was affixed to 16 healthy, young cats. Prior to inclusion in the study, cats were subject to echocardiographic examination. The heart rate (HR) when cats were restrained for echocardiography (HRr) was calculated from 4–5 consecutive RR intervals obtained from a simultaneously recorded electrocardiogram. Electrocardiographic data were then acquired by telemetry in a quiet room in the veterinary hospital (VTH) and later, in the owner's home (home). The ambulatory data were digitally sampled and the RR interval tachogram from a 4 min epoch subject to Fast Fourier Transform to yield measures of heart rate variability (HRV). Sinus arrhythmia was often observed in resting cats. Heart rates (bpm) expressed as mean (±SD) were: HRr: 187 (±25), HRVTH: 150 (±23), HRhome: 132 (±19); each of these rates was significantly different from the others. Significant differences in profiles of HRV suggested that sympathetic tone was higher (and parasympathetic tone lower) when cats were in the hospital.

scholarly journals Stress Classification Using K-means Clustering and Heart Rate Variability from Electrocardiogram

2021 ◽  
Vol 14 ◽  
pp. 251-254
Author(s):  
Mingu Kang ◽  
Siho Shin ◽  
Jaehyo Jung ◽  
Youn Tae Kim
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Fourier Transform ◽  
Stress State ◽  
Fast Fourier Transform ◽  
Stress Level ◽  
Ecg Signal ◽  
Stress Classification ◽  
S Peak

In this study, we propose a method to classify individuals under stress and those without stress using k-means clustering. After extracting the R and S peak values from the ECG signal, the heart rate variability is extracted using a fast Fourier transform. Then, a criterion for classifying the ECG signal for the stress state is set, and the stress state is classified through k-means clustering. In addition, the stress level is indicated using the 𝐑 − 𝐒𝐩𝐞𝐚𝐤 value. This method is expected to be applied to the U-healthcare field to help manage the mental health of people suffering from stress.

Spectral analysis of heart rate variability: interchangeability between autoregressive analysis and fast Fourier transform

2006 ◽  
Vol 39 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Aurélien Pichon ◽  
Manuel Roulaud ◽  
Sophie Antoine-Jonville ◽  
Claire de Bisschop ◽  
André Denjean
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Autoregressive Analysis
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