Heart Rate Variability Extraction using Commodity Wi-Fi Devices via Time Domain Signal Processing

2021 ◽  
Author(s):  
Itsuki Shirakami ◽  
Takashi Sato
Keyword(s):  
Heart Rate ◽  
Signal Processing ◽  
Heart Rate Variability ◽  
Time Domain ◽  
Time Domain Signal

P7-02 The time-domain signal-average ECG and heart rate variability in mitral valve prolapse syndrome and normal Taiwanese

2004 ◽  
Vol 97 ◽  
pp. S61 ◽  
Author(s):  
Kuang-Ming Yang ◽  
Gen-Wang Yang ◽  
Chun-Cheng Lin ◽  
Chih-Ming Cheng ◽  
Ing-Fang Yang ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Mitral Valve ◽  
Time Domain ◽  
Mitral Valve Prolapse ◽  
Signal Average ◽  
Time Domain Signal ◽  
The Time Domain

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

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.  

Trends in Heart Rate and Heart Rate Variability during Pregnancy and Three Months Postpartum: Continuous Monitoring in a Free-Living Context (Preprint)

2021 ◽  
Author(s):  
Fatemeh Sarhaddi ◽  
Iman Azimi ◽  
Anna Axelin ◽  
Hannakaisa Niela-Vilen ◽  
Pasi Liljeberg ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Pregnant Women ◽  
Time Domain ◽  
Second Trimester ◽  
Third Trimester ◽  
Non Invasive ◽  
The Third ◽  
Invasive Method ◽  
Frequency Power

BACKGROUND Heart rate variability (HRV) is a non-invasive method reflecting autonomic nervous system (ANS) regulations. Altered HRV is associated with adverse mental or physical health complications. ANS also has a central role in physiological adaption during pregnancy causing normal changes in HRV. OBJECTIVE Assessing trends in heart rate (HR) and HRV parameters as a non-invasive method for remote maternal health monitoring during pregnancy and three months postpartum. METHODS Fifty-eight pregnant women were monitored using an Internet-of-Things (IoT)-based remote monitoring system during pregnancy and 3-months postpartum. Pregnant women were asked to continuously wear Gear sport smartwatch to monitor their HR and HRV. In addition, a cross-platform mobile application was utilized for collecting pregnancy-related information. The trends of HR and HRV parameters were extracted using reliable data. We also analyzed the trends of normalized HRV parameters based on HR to remove the effect of HR changes on HRV trends. Finally, we exploited hierarchical linear mixed models to analyze the trends of HR, HRV, and normalized HRV parameters. RESULTS HR increased significantly during the second trimester (P<.001) and decreased significantly during the third trimester (P<.01). Time-domain HRV parameters, average normal interbeat intervals (AVNN), standard deviation of normal interbeat intervals (SDNN), root mean square of the successive difference of normal interbeat intervals (RMSSD), normalized SDNN (nSDNN), and normalized RMSSD (nRMSSD) decreased significantly during the second trimester (P<.001) then increased significantly during the third trimester (P<.01). Some of the frequency domain parameters, low-frequency power (LF), high-frequency power (HF), and normalized HF (nHF) decreased significantly during the second trimester (P<.01), and HF increased significantly during the third trimester (P<.01). In the postpartum period, nRMSSD decreased (P<.05), and the LF to HF ratio (LF/HF) increased significantly (P<.01). CONCLUSIONS Our study showed that HR increased and HRV parameters decreased as the pregnancy proceeded, and the values returned to normal after the delivery. Moreover, our results show that HR started to decrease while time-domain HRV parameters and HF started to increase during the third trimester. Our results also demonstrate the possibility of continuous HRV monitoring in everyday life settings.

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