A Novel Approach in Heart-Rate-Variability Analysis Based on Modified Poincaré Plots
Heart-rate variability (HRV), measured by the fluctuation of beat-to-beat intervals, has been growingly considered the most important hallmark of heart rate (HR) time series. The HRV can be characterized by various statistical measures both in the time and frequency domains, or by nonlinear methods....
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9741767/ |
| _version_ | 1818669138717966336 |
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| author | Andras Buzas Tamas Horvath Andras Der |
| author_facet | Andras Buzas Tamas Horvath Andras Der |
| author_sort | Andras Buzas |
| collection | DOAJ |
| description | Heart-rate variability (HRV), measured by the fluctuation of beat-to-beat intervals, has been growingly considered the most important hallmark of heart rate (HR) time series. The HRV can be characterized by various statistical measures both in the time and frequency domains, or by nonlinear methods. During the past decades, an overwhelming amount of HRV data has been piled up in the research community, but the individual results are difficult to reconcile due to the different measuring conditions and the usually HR-dependent statistical HRV-parameters applied. Moreover, the precise HR-dependence of HRV parameters is not known. Using data gathered by a wearable sensor of combined heart-rate and actigraphy modalities, here, we introduce a novel descriptor of HRV, based on a modified Poincaré plot of 24-h RR-recordings. We show that there exists a – regressive biexponential – HRV versus HR “master” curve (“M-curve”) that is highly conserved for a healthy individual on short and medium terms (on the hours to months scale, respectively). At the same time, we reveal how this curve is related to age in the case of healthy people, and establish alterations of the M-curves of heart-attack patients. A stochastic neuron model accounting for the observed phenomena is also elaborated, in order to facilitate physiological interpretation of HRV data. Our novel evaluation procedure applied on the time series of interbeat intervals allows the description of the HRV(HR) function with unprecedented precision. To utilize the full strength of the method, we suggest a 24-hour-long registration period under natural, daily-routine circumstances (i.e., no special measuring conditions are required). By establishing a patient’s M-curve, it is possible to monitor the development of his/her status over an extended period of time. On these grounds, the new method is suggested to be used as a competent tool in future HRV analyses for both clinical and training applications, as well as for everyday health promotion. |
| first_indexed | 2024-12-17T06:47:27Z |
| format | Article |
| id | doaj.art-d137470c6fff4a4e8c86b5ad0fb151f7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T06:47:27Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d137470c6fff4a4e8c86b5ad0fb151f72022-12-21T21:59:42ZengIEEEIEEE Access2169-35362022-01-0110366063661510.1109/ACCESS.2022.31622349741767A Novel Approach in Heart-Rate-Variability Analysis Based on Modified Poincaré PlotsAndras Buzas0https://orcid.org/0000-0003-1841-7907Tamas Horvath1Andras Der2https://orcid.org/0000-0001-6112-884XBiological Research Centre, Institute of Biophysics, Szeged, HungaryCentre of Cardiology, Medical Faculty, University of Szeged, Szeged, HungaryBiological Research Centre, Institute of Biophysics, Szeged, HungaryHeart-rate variability (HRV), measured by the fluctuation of beat-to-beat intervals, has been growingly considered the most important hallmark of heart rate (HR) time series. The HRV can be characterized by various statistical measures both in the time and frequency domains, or by nonlinear methods. During the past decades, an overwhelming amount of HRV data has been piled up in the research community, but the individual results are difficult to reconcile due to the different measuring conditions and the usually HR-dependent statistical HRV-parameters applied. Moreover, the precise HR-dependence of HRV parameters is not known. Using data gathered by a wearable sensor of combined heart-rate and actigraphy modalities, here, we introduce a novel descriptor of HRV, based on a modified Poincaré plot of 24-h RR-recordings. We show that there exists a – regressive biexponential – HRV versus HR “master” curve (“M-curve”) that is highly conserved for a healthy individual on short and medium terms (on the hours to months scale, respectively). At the same time, we reveal how this curve is related to age in the case of healthy people, and establish alterations of the M-curves of heart-attack patients. A stochastic neuron model accounting for the observed phenomena is also elaborated, in order to facilitate physiological interpretation of HRV data. Our novel evaluation procedure applied on the time series of interbeat intervals allows the description of the HRV(HR) function with unprecedented precision. To utilize the full strength of the method, we suggest a 24-hour-long registration period under natural, daily-routine circumstances (i.e., no special measuring conditions are required). By establishing a patient’s M-curve, it is possible to monitor the development of his/her status over an extended period of time. On these grounds, the new method is suggested to be used as a competent tool in future HRV analyses for both clinical and training applications, as well as for everyday health promotion.https://ieeexplore.ieee.org/document/9741767/Holter-monitoringpoincaré-plotRMSSDheart-rate dependenceneuron-model |
| spellingShingle | Andras Buzas Tamas Horvath Andras Der A Novel Approach in Heart-Rate-Variability Analysis Based on Modified Poincaré Plots IEEE Access Holter-monitoring poincaré-plot RMSSD heart-rate dependence neuron-model |
| title | A Novel Approach in Heart-Rate-Variability Analysis Based on Modified Poincaré Plots |
| title_full | A Novel Approach in Heart-Rate-Variability Analysis Based on Modified Poincaré Plots |
| title_fullStr | A Novel Approach in Heart-Rate-Variability Analysis Based on Modified Poincaré Plots |
| title_full_unstemmed | A Novel Approach in Heart-Rate-Variability Analysis Based on Modified Poincaré Plots |
| title_short | A Novel Approach in Heart-Rate-Variability Analysis Based on Modified Poincaré Plots |
| title_sort | novel approach in heart rate variability analysis based on modified poincar x00e9 plots |
| topic | Holter-monitoring poincaré-plot RMSSD heart-rate dependence neuron-model |
| url | https://ieeexplore.ieee.org/document/9741767/ |
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