scholarly journals Limitations of power-spectrum and time-domain analysis of heart rate variability in short-term ECG recorded using telemetry in unrestrained rats

2003 ◽  
Author(s):  
J.P. Couderc ◽  
A. Elder ◽  
C. Cox ◽  
W. Zareba ◽  
G. Oberdorster
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Power Spectrum ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Short Term

scholarly journals Impaired circadian heart rate variability in Parkinson’s disease: a time-domain analysis in ambulatory setting

2019 ◽  
Author(s):  
Valentina Arnao ◽  
Antonio Cinturino ◽  
Sergio Mastrilli ◽  
Carmelo Buttà ◽  
Carlo Maida ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Heart Rate ◽  
Parkinson's Disease ◽  
Heart Rate Variability ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Ambulatory Setting ◽  
Yahr Stage

Abstract Background Heart rate variability (HRV) decreases in Parkinson’s disease (PD) and it can be considered a marker for cardiovascular dysautonomia.Purpose To evaluate long-term time-domain analysis of HRV of PD patients and compare the results with those of matched healthy individuals.Method Idiopathic PD patients without comorbidity impairing HRV, and age-matched healthy individuals were recruited in a pilot study. A long-term time domain analysis of HRV using 24-hour ambulatory ECG was performed.Results 18 PD patients fulfilling inclusion criteria completed the evaluation (mean age was 55.6 ±8.8, disease duration: 5.0±4.7). Mean SCOPA-AUT score was 10.1±7.3. Patients were on Hoehn & Yahr stage 1-2 and mean Levodopa Equivalent Dose (LED) was 311 ± 239.9. Mean of the 5-minute standard deviation (SD) of R-R intervals distribution (SDNN) for all 5 min segments of the entire recording (ISDNN) was significantly lower in patients compared to controls. ISDNN significantly correlated with age, LED, levodopa and SCOPA-AUT scores.Conclusion In our population characterized by mild to moderate disease severity, time-domain assessment of HRV seemed to be a potential tool to characterize cardiovascular dysautonomia. Decrease of ISDNN in PD may reflect a circadian overall sympathetic and parasympathetic disarrangement.

scholarly journals Impaired circadian heart rate variability in Parkinson’s disease: a time-domain analysis in ambulatory setting

2020 ◽  
Author(s):  
Valentina Arnao ◽  
Antonio Cinturino ◽  
Sergio Mastrilli ◽  
Carmelo Buttà ◽  
Carlo Maida ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Heart Rate ◽  
Parkinson's Disease ◽  
Heart Rate Variability ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Ambulatory Setting ◽  
Healthy Individuals

Abstract Background Heart rate variability (HRV) decreases in Parkinson’s disease (PD) and it can be considered a marker for cardiovascular dysautonomia. Purpose To evaluate long-term time-domain analysis of HRV of PD patients and compare the results with those of matched healthy individuals. Method Idiopathic PD patients without comorbidity impairing HRV, and age-matched healthy individuals were recruited in a pilot study. A long-term time domain analysis of HRV using 24-hour ambulatory ECG was performed. Results Overall, 18 PD patients fulfilling inclusion criteria completed the evaluation (mean age was 55.6 ±8.8, disease duration: 5.0±4.7). Mean SCOPA-AUT score was 10.1±7.3. Patients were on Hoehn & Yahr stage 1-2 and mean Levodopa Equivalent Dose (LED) was 311 ± 239.9. Mean of the 5-minute standard deviation (SD) of R-R intervals distribution (SDNN) for all 5 min segments of the entire recording (ISDNN) was significantly lower in patients compared to controls. ISDNN was significantly different between Parkinson’s disease patients and healthy controls.Conclusion In our population characterized by mild to moderate disease severity, time-domain assessment of HRV seemed to be a potential tool to characterize cardiovascular dysautonomia. Decrease of ISDNN in PD may reflect an autonomic derangement extending all day and night long.

scholarly journals Impaired circadian heart rate variability in Parkinson’s disease: a time-domain analysis in ambulatory setting

2020 ◽  
Author(s):  
Valentina Arnao ◽  
Antonio Cinturino ◽  
Sergio Mastrilli ◽  
Carmelo Buttà ◽  
Carlo Maida ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Heart Rate ◽  
Parkinson's Disease ◽  
Heart Rate Variability ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Ambulatory Setting ◽  
Healthy Individuals

Abstract Background Heart rate variability (HRV) decreases in Parkinson’s disease (PD) and it can be considered a marker for cardiovascular dysautonomia. Purpose To evaluate long-term time-domain analysis of HRV of PD patients and compare the results with those of matched healthy individuals. Method Idiopathic PD patients without comorbidity impairing HRV, and age-matched healthy individuals were recruited in a pilot study. A long-term time domain analysis of HRV using 24-hour ambulatory ECG was performed. Results Overall, 18 PD patients fulfilling inclusion criteria completed the evaluation (mean age was 55.6 ±8.8, disease duration: 5.0±4.7). Mean SCOPA-AUT score was 10.1±7.3. Patients were on Hoehn & Yahr stage 1-2 and mean Levodopa Equivalent Dose (LED) was 311 ± 239.9. Mean of the 5-minute standard deviation (SD) of R-R intervals distribution (SDNN) for all 5 min segments of the entire recording (ISDNN) was significantly lower in patients compared to controls. ISDNN was significantly different between Parkinson’s disease patients and healthy controls. Conclusion In our population characterized by mild to moderate disease severity, time-domain assessment of HRV seemed to be a potential tool to characterize cardiovascular dysautonomia. Decrease of ISDNN in PD may reflect an autonomic derangement extending all day and night long.

scholarly journals Measurement and time domain analysis of heart rate variability in dairy cattle

2001 ◽  
Vol 149 (25) ◽  
pp. 772-774 ◽  
Author(s):  
M. Minero ◽  
E. Canali ◽  
V. Ferrante ◽  
C. Carenzi
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Dairy Cattle ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis

Time-Domain Analysis of Heart Rate Variability in Diabetic Patients with and without Autonomic Neuropathy

2002 ◽  
Vol 22 (5-6) ◽  
pp. 400-403 ◽  
Author(s):  
Awdah Al-Hazimi ◽  
Nabil Al-Ama ◽  
Ahmad Syiamic ◽  
Reem Qosti ◽  
Khidir Abdel-Galil
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Autonomic Neuropathy ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Diabetic Patients

scholarly journals Entropy-Based Measures of Hypnopompic Heart Rate Variability Contribute to the Automatic Prediction of Cardiovascular Events

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 241 ◽  
Author(s):  
Xueya Yan ◽  
Lulu Zhang ◽  
Jinlian Li ◽  
Ding Du ◽  
Fengzhen Hou
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Cardiovascular Events ◽  
Predictive Performance ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Short Term ◽  
Cvd Risk ◽  
Term Prediction

Surges in sympathetic activity should be a major contributor to the frequent occurrence of cardiovascular events towards the end of nocturnal sleep. We aimed to investigate whether the analysis of hypnopompic heart rate variability (HRV) could assist in the prediction of cardiovascular disease (CVD). 2217 baseline CVD-free subjects were identified and divided into CVD group and non-CVD group, according to the presence of CVD during a follow-up visit. HRV measures derived from time domain analysis, frequency domain analysis and nonlinear analysis were employed to characterize cardiac functioning. Machine learning models for both long-term and short-term CVD prediction were then constructed, based on hypnopompic HRV metrics and other typical CVD risk factors. CVD was associated with significant alterations in hypnopompic HRV. An accuracy of 81.4% was achieved in short-term prediction of CVD, demonstrating a 10.7% increase compared with long-term prediction. There was a decline of more than 6% in the predictive performance of short-term CVD outcomes without HRV metrics. The complexity of hypnopompic HRV, measured by entropy-based indices, contributed considerably to the prediction and achieved greater importance in the proposed models than conventional HRV measures. Our findings suggest that Hypnopompic HRV assists the prediction of CVD outcomes, especially the occurrence of CVD event within two years.

scholarly journals Remote monitoring can predict lethal arrhythmic events through time-domain analysis of heart rate variability in patients with implantable cardioverter defibrillator

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
Y Shirakawa ◽  
S Niwano ◽  
J Oikawa ◽  
D Saito ◽  
T Sato ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Implantable Cardioverter Defibrillator ◽  
Time Domain ◽  
Remote Monitoring ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Cardioverter Defibrillator ◽  
The Mean ◽  
Hrv Analysis

Abstract Background We prospectively collected device and heart rate data, i.e. heart rate variability (HRV), through remote monitoring (RM) of patients with implantable cardioverter defibrillator (ICD). Several studies have demonstrated usefulness of RM in implanted device patients, however, reports concerning the predictors of lethal ventricular arrhythmias are limited. Purpose The objective was to identify the predictors of lethal arrhythmic events (VT/VF). Methods Thirty-three patients (mean age: 50 years) with ICDs [with functionality of HRV analysis] were divided into 2 groups [VT/VF(+), VT/VF(−)]. Clinical, device (ventricular lead impedance; amplitude of ventricular electrogram), and HRV data were compared between the 2 groups. As the index of time-domain HRV analysis, NN intervals-index (SDNNi) was calculated for every 5 minutes, and the mean, maximum, and minimum SDNNi during the 24-hour period were used. Results During the observation period (median 12 months), 10 patients experienced VT/VF events. In HRV data, the mean, max, and min SDNNi were higher in VT/VF(+) than VT/VF(−) group (132.9±9.3 v.s. 93.5±6.1, p=0.0013; 214.6±10.6 v.s. 167.0±7.0, p=0.0007; 71.2±7.5 v.s. 43.9±4.9, p=0.0047). The other parameters did not exhibit significant difference. On logistic regression analysis, the mean SDNNi of 100.1, max SDNNi of 185.0 and min SDNNi of 52.0 as cut-off values for prediction of VT/VF event demonstrated significant receiver operating characteristics (ROC) curves (AUC=0.86, p=0.0007; AUC=0.84, p=0.0005; AUC=0.78, p=0.0030). Furthermore, in cases of VT/VF(+) group, the max ΔSDNNi, i.e., difference from baseline SDNNi, and min ΔSDNNi in 7 and 28 days preceding VT/VF events exhibited time course changes in comparison with baseline values. They were significant predictors of VT/VF events (max ΔSDNNi cut-off: 46.8, AUC=0.91, p=0.0002; min ΔSDNNi cut-off: −42.4, AUC=0.88, p=0.0014). Conclusion Time-domain analysis of HRV through RM may help identify patients at high risk of lethal arrhythmic events, and predict occurrence of such arrhythmic events. Funding Acknowledgement Type of funding source: None

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