scholarly journals On the Minimal Adequate Sampling Frequency of the Photoplethysmogram for Pulse Rate Monitoring and Heart Rate Variability Analysis in Mobile and Wearable Technology

2019 ◽  
Vol 19 (5) ◽  
pp. 232-240 ◽  
Author(s):  
Szabolcs Béres ◽  
Lőrinc Holczer ◽  
László Hejjel
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
Pulse Rate ◽  
Sampling Error ◽  
Sampling Theorem ◽  
Sampling Frequency ◽  
Heart Rate Variability Analysis ◽  
Poincaré Plot ◽  
Adequate Sampling

Abstract Recently there has been great interest in photoplethysmogram signal processing. However, its minimally necessary sampling frequency for accurate heart rate variability parameters is ambiguous. In the present paper frequency-modulated 1.067 Hz cosine wave modelled the variable PPG in silico. The five-minute-long, 1 ms resolution master-signals were decimated (D) at 2-500 ms, then cubic spline interpolated (I) back to 1 ms resolution. The mean pulse rate, standard deviation, root mean square of successive pulse rate differences (RMSSD), and spectral components were computed by Varian 2.3 and compared to the master-series via relative accuracy error. Also Poincaré-plot morphology was assessed. Mean pulse rate is accurate down to 303 ms (D) and 400 ms (I). In low-variability series standard deviation required at least 5 ms (D) and 100 ms (I). RMSSD needed 10 ms (D), and 303 ms (I) in normal, whereas 2 ms (D) and 100 ms (I) in low- variability series. In the frequency domain 5 ms (D) and 100 ms (I) are required. 2 ms (D) and 100 ms (I) preserved the Poincaré-plot morphology. The minimal sampling frequency of PPG for accurate HRV analysis is higher than expected from the signal bandwidth and sampling theorem. Interpolation improves accuracy. The ratio of sampling error and expected variability should be considered besides the inherent sensitivity of the given parameter, the interpolation technique, and the pulse rate detection method.

Autonomie Correlates of Antidepressant Treatment Using Heart-Rate Variability Analysis

1998 ◽  
Vol 43 (2) ◽  
pp. 183-186 ◽  
Author(s):  
Yaariv Khaykin ◽  
Paul Dorian ◽  
Brian Baker ◽  
Colin Shapiro ◽  
Paul Sandor ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
Rating Scale ◽  
Antidepressant Treatment ◽  
Response To Therapy ◽  
Heart Rate Variability Analysis ◽  
Randomized Evaluation ◽  
Temporal Domain ◽  
Percentage Difference

Objective: To assess the 24-hour temporal-domain heart-rate variability correlates of treatment with fluoxetine or doxepinfor depression. Method: A randomized evaluation of fluoxetine and doxepin measured a 50% change in the Hamilton Depression Rating Scale (HDRS) score as a response to therapy and was correlated with measures of standard deviation of the mean of all 5-minute segments of normal electrocardiographic R-R intervals (SDANN), standard deviation of all normal R-R intervals (SDNN), root mean square of successive differences in R-R intervals (r-MSSD), and percentage difference between adjacent normal R-R intervals that are greater than 50 msec (pNN50)from 24-hour electrocardiogram (ECG) tapes. Results: Ten out of 14 patients responded. Response was associated with an increase in SDANN of 17% (P < 0.05). Nonresponse was associated with a 17% decrease in SDANN and a 22% decrease in SDNN (both P < 0.05). No other measures correlated with therapeutic response. No heart-rate variability (HRV) differences between the 2 drug therapies were observed. Conclusion: Twenty-four-hour HRV measures may be useful in assessing response to antidepressant therapy.

scholarly journals Electrocardiogram Sampling Frequency Range Acceptable for Heart Rate Variability Analysis

2018 ◽  
Vol 24 (3) ◽  
pp. 198 ◽  
Author(s):  
Ohhwan Kwon ◽  
Jinwoo Jeong ◽  
Hyung Bin Kim ◽  
In Ho Kwon ◽  
Song Yi Park ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sampling Frequency ◽  
Heart Rate Variability Analysis ◽  
Frequency Range ◽  
Variability Analysis

Characterization of HRV by Poincare Plot Analysis among the Female Tea Garden Workers of Northern Hilly Regions of West Bengal

2012 ◽  
pp. 206-215
Author(s):  
Somsirsa Chatterjee ◽  
Ankur Ganguly ◽  
Saugat Bhattacharya
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
West Bengal ◽  
Mean Value ◽  
Short Term ◽  
Poincaré Plot ◽  
Plot Analysis ◽  
Tea Garden

Recent research on Heart Rate Variability (HRV) has proven that Poincare Plot is a powerful tool to mark Short Term and Long Term Heart Rate Variability. This study focuses a comprehensive characterization of HRV among the Tea Garden Workers of the Northern Hilly Regions of West Bengal. The characterization, as available from the data sets, projects the average values of SD1 characteristics, that is, Short Term HRV in females as 58.265ms and SD2 as 149.474. The SDRR shows a mean value of 87.298 with a standard deviation of 119.669 and the S Characterization as 16505.99 ms and Standard deviation of 45882.31 ms. The SDRR shows a mean value of 87.298 with a standard deviation of 119.669 and the S Characterization as 16505.99 ms and Standard deviation of 45882.31 ms. ApEn Characterization showed mean value of 0.961 and standard deviation of 0.274.

Characterization of HRV by Poincare Plot Analysis among the Female Tea Garden Workers of Northern Hilly Regions of West Bengal

2010 ◽  
Vol 5 (2) ◽  
pp. 49-59 ◽  
Author(s):  
Somsirsa Chatterjee ◽  
Ankur Ganguly ◽  
Saugat Bhattacharya
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
West Bengal ◽  
Mean Value ◽  
Data Sets ◽  
Short Term ◽  
Poincaré Plot ◽  
Tea Garden

Recent research on Heart Rate Variability (HRV) has proven that Poincare Plot is a powerful tool to mark Short Term and Long Term Heart Rate Variability. This study focuses a comprehensive characterization of HRV among the Tea Garden Workers of the Northern Hilly Regions of West Bengal. The characterization, as available from the data sets, projects the average values of SD1 characteristics, that is, Short Term HRV in females as 58.265ms and SD2 as 149.474. The SDRR shows a mean value of 87.298 with a standard deviation of 119.669 and the S Characterization as 16505.99 ms and Standard deviation of 45882.31 ms. The SDRR shows a mean value of 87.298 with a standard deviation of 119.669 and the S Characterization as 16505.99 ms and Standard deviation of 45882.31 ms. ApEn Characterization showed mean value of 0.961 and standard deviation of 0.274.

Segmented Poincaré Plot Analysis for Risk Stratification in Patients with Dilated Cardiomyopathy

2010 ◽  
Vol 49 (05) ◽  
pp. 511-515 ◽  
Author(s):  
C. Fischer ◽  
R. Schroeder ◽  
H. R. Figulla ◽  
M. Goernig ◽  
A. Voss
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Risk Stratification ◽  
Dilated Cardiomyopathy ◽  
Heart Rate Variability Analysis ◽  
Poincaré Plot ◽  
Plot Analysis ◽  
Interval Time Series ◽  
Nonlinear Features ◽  
Cloud Of Points

Summary Background: The prognostic value of heart rate variability in patients with dilated cardiomyopathy (DCM) is limited and does not contribute to risk stratification although the dynamics of ventricular repolarization differs considerably between DCM patients and healthy subjects. Neither linear nor nonlinear methods of heart rate variability analysis could discriminate between patients at high and low risk for sudden cardiac death. Objective: The aim of this study was to analyze the suitability of the new developed segmented Poincaré plot analysis (SPPA) to enhance risk stratification in DCM. Methods: In contrast to the usual applied Poincaré plot analysis the SPPA retains nonlinear features from investigated beat-to-beat interval time series. Main features of SPPA are the rotation of cloud of points and their succeeded variability depended segmentation. Results: Significant row and column probabilities were calculated from the segments and led to discrimination (up to p < 0.005) between low and high risk in DCM patients. Conclusion: For the first time an index from Poincaré plot analysis of heart rate variability was able to contribute to risk stratification in patients suffering from DCM.

scholarly journals Heart rate variability analysis based on modified Poincaré plot

2012 ◽  
Vol 61 (19) ◽  
pp. 190506
Author(s):  
Huo Cheng-Yu ◽  
Zhuang Jian-Jun ◽  
Huang Xiao-Lin ◽  
Hou Feng-Zhen ◽  
Ning Xin-Bao
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Heart Rate Variability Analysis ◽  
Poincaré Plot ◽  
Variability Analysis

scholarly journals Heart Rate Variability Analysis and The Influence of Exercise Intensity Over Time in Young-healthy Women

2021 ◽  
Vol 1 (1) ◽  
pp. 1-6
Author(s):  
Aisha Widi Rahayu ◽  
Izza Alifa Hassya ◽  
Eki Dipo Laksono ◽  
Alvin Sahroni
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Exercise Intensity ◽  
Circulatory System ◽  
Heart Rate Variability Analysis ◽  
Regular Exercise ◽  
Poincaré Plot ◽  
Evaluation Period ◽  
Healthy Women ◽  
Exercise Period

Our heart is a vital organ that pumps blood and through the vessels of the circulatory system. In medical applications, we can observe the heart rate using Electrocardiograph (ECG). Currently, people tend to have high working activity without a proper exercise intensity. This study was conducted to observe the heart rate variability (HRV) on the healthy young woman who was not doing any exercise. We evaluated the HRV characteristics while exercising with a regular period and different intensity (light to hard) and how the difference before and after of evaluation period. Seven young-healthy women (19 - 21 years old) women were observed during three observation stages: pre-exercise, main exercise-period, and post-exercise for 2 months. We analyzed MeanRR, SDRR, CVRR, rMSSD, VLF, LF, HF, and the Poincaré plot parameters (SD1 and SD2) as the HRV properties. We found that SDRR was decreased from the first week (0.08 s) to the last week of the evaluation period (0.03 s) followed by the HF component (0.15 – 0.2 Hz). The Poincaré plot properties also reduced from the first week to the last week of the exercise period (0.07 s to 0.03 s). We indicated the characteristics of a woman's HRV during regular exercise periods with different intensity have made the heart more effective in pumping blood. We concluded that the heart condition would be improved during regular exercise with the increment of intensity even in a short of a period. Finally, the heart rate performance may be decreased during absent from regular exercise for a month.

scholarly journals Periodized Aerobic Interval Training Modifies Geometric Indices of Heart Rate Variability in Metabolic Syndrome

Medicina ◽  
2019 ◽  
Vol 55 (9) ◽  
pp. 532
Author(s):  
Laís Manata Vanzella ◽  
Denise Brugnoli Balbi Dagostinho ◽  
Maria Paula Ferreira de Figueiredo ◽  
Carlos Iván Mesa Castrillón ◽  
Jayme Netto Junior ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
Interval Training ◽  
Training Group ◽  
Control Group ◽  
Autonomic Modulation ◽  
Poincaré Plot ◽  
Aerobic Interval Training

Background: Metabolic syndrome (MetS) influences the autonomic modulation, increasing the risk of cardiovascular events, which demands the identification of effective treatments for this population. Considering this, the study has the objective of evaluating the effects of periodized aerobic interval training (AIT) on geometrical methods of heart rate variability (HRV) on individuals with MetS. Methods: 52 individuals with MetS were considered for analysis. They were divided into two groups: aerobic interval training group (AITG; n = 26) and control group (CG; n = 26). The AITG performed 16 weeks of periodized AIT. For HRV analysis, the heart rate was recorded beat-by-beat at the beginning and the end of the AIT program and geometrical methods were used for analysis. Results: significant increase was observed for triangular index (RRtri, −1.25 ± 0.58 vs. 1.41 ± 0.57), standard deviation of distances from diagonal to points (SD1, −0.13 ± 1.52 vs. 4.34 ± 1.49), and standard deviation of distances from points to lines (SD2, −2.14 ± 3.59 vs. 11.23 ± 3.52) on AITG compared to CG. Significant differences were not observed for triangular interpolation of normal heartbeats interval histogram (TINN, −4.05 ± 17.38 vs. 25.52 ± 17.03) and SD1/SD2 ratio (0.03 ± 0.02 vs. 0.00 ± 0.02). Qualitative analysis of the Poincaré plot identified increase on dispersion of both short and long-term intervals between successive heartbeats (RR interval) on AITG after the AIT program. Conclusion: geometric indices of HRV suggest an increase in cardiac autonomic modulation in individuals with MetS after 16 weeks of periodized AIT.

Sign in / Sign up

Export Citation Format

Share Document