| 1. |
- Bailon, Raquel, et al.
(författare)
-
Analysis of heart rate variability during exercise stress testing using respiratory information
- 2010
-
Ingår i: Biomedical Signal Processing and Control. - : Elsevier BV. - 1746-8094. ; 5:4, s. 299-310
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel method for the analysis of heart rate variability (HRV) during exercise stress testing enhanced with respiratory information. The instantaneous frequency and power of the low frequency (LF) and high frequency (HF) bands of the HRV are estimated by parametric decomposition of the instantaneous autocorrelation function (ACF) as a sum of damped sinusoids. The instantaneous ACF is first windowed and filtered to reduce the cross terms. The inclusion of respiratory information is proposed at different stages of the analysis, namely, the design of the filter applied to the instantaneous ACF, the parametric decomposition, and the definition of a dynamic HF band. The performance of the method is evaluated on simulated data as well as on a stress testing database. The simulation results show that the inclusion of respiratory information reduces the estimation error of the amplitude of the HF component from 3.5% to 2.4% in mean and related SD from 3.0% to 1.7% when a tuned time smoothing window is used at an SNR of 15 dB. Results from the stress testing database show that information on respiratory frequency produces HF power estimates which closely resemble those from the simulations which exhibited lower SD. The mean SD of these estimates with respect to their mean trends is reduced by 84% (from 0.74 x 10(-3) s(-2) to 0.12 x 10(-3) s(-2)). The analysis of HRV in the stress testing database reveals a significant decrease in the power of both the LF and HF components around peak stress. (C) 2010 Elsevier Ltd. All rights reserved.
|
|
| 2. |
- Kontaxis, Spyridon, et al.
(författare)
-
Investigating Respiratory Rate Estimation during Paroxysmal Atrial Fibrillation Using an Improved ECG Simulation Model
- 2020
-
Ingår i: 2020 Computing in Cardiology, CinC 2020. - 2325-887X .- 2325-8861. - 9781728173825 ; 2020-September
-
Konferensbidrag (refereegranskat)abstract
- The present study addresses the problem of respiratory rate estimation from ECG-derived respiration (EDR) signals during paroxysmal atrial fibrillation (AF). Novel signal-to-noise ratios between various components of the ECG including the influence of respiration, measured by QRS ensemble variance, the amplitude of fibrillatory waves (f-waves), and the QRS amplitude are introduced to characterize EDR performance. Using an improved ECG simulation model accounting for morphological variation induced by respiration, the results show that 1. the error in estimating the respiratory rate increases as a function of the time spent in AF, 2. the leads farthest away from the atria, i.e., V_{4}, V_{5}, V_{6}, exhibit the best performance due to lower f-wave amplitudes, 3. lower errors in leads with similar f-wave amplitude are due to a more pronounced respiratory influence, and 4. the respiratory influence is higher in V_{2}, V_{3}, and V_{4} compared to other precordial leads.
|
|
| 3. |
- Lázaro, Jesús, et al.
(författare)
-
ECG-Derived Respiratory Rate in Atrial Fibrillation
- 2020
-
Ingår i: IEEE Transactions on Biomedical Engineering. - 1558-2531. ; 67:3, s. 905-914
-
Tidskriftsartikel (refereegranskat)abstract
- Objective: The present study addresses the problem of estimating the respiratory rate from the mor- phological ECG variations in the presence of atrial fibrilla- tory waves (f-waves). The significance of performing f-wave suppression before respiratory rate estimation is investi- gated. Methods: The performance of a novel approach to ECG-derived respiration, named “slope range” (SR) and de- signed particularly for operation in atrial fibrillation (AF), is compared to that of two well-known methods based on ei- ther R-wave angle (RA) or QRS loop rotation angle (LA). A novel rule is proposed for spectral peak selection in respira- tory rate estimation. The suppression of f-waves is accom- plished using signal- and noise-dependent QRS weighted averaging. The performance evaluation embraces real as well as simulated ECG signals acquired from patients with persistent AF; the estimation error of the respiratory rate is determined for both types of signals. Results: Using real ECG signals and reference respiratory signals, rate estima- tion without f-wave suppression resulted in a median error of 0.015 ± 0.021 Hz and 0.019 ± 0.025 Hz for SR and RA, respectively, whereas LA with f-wave suppression resulted in 0.034 ± 0.039 Hz. Using simulated signals, the results also demonstrate that f-wave suppression is superfluous for SR and RA, whereas it is essential for LA. Conclusion: The results show that SR offers the best performance as well as computational simplicity since f-wave suppression is not needed. Significance: The respiratory rate can be robustly estimated from the ECG in the presence of AF.
|
|
| 4. |
- Lazaro, Jesus, et al.
(författare)
-
Electrocardiogram derived respiration from QRS slopes : Evaluation with stress testing recordings
- 2013
-
Ingår i: 2013 Computing in Cardiology. - 9781479908844 ; 40, s. 655-658
-
Konferensbidrag (refereegranskat)abstract
- A method for respiratory rate estimation from electrocardiogram (ECG), based on variations in QRS complexes slopes, is evaluated over stress testing recordings. Besides the 12 standard, and the 3 vectorcardiogram (VCG), 2 additional leads derived from the VCG are analyzed. A total of 34 slope series were studied, 2 for each lead: slopes between the peaks of the Q and R waves, and between the peaks of the R and S waves. Respiratory rate is estimated by using a time-frequency based algorithm which can combine information from several derived respiration signals. Evaluation was performed over a database containing ECG and respiratory signals simultaneously recorded from 30 subjects spontaneously breathing during a stress test. Respiratory rate estimation is performed with information of 4 different combinations of QRS slope series. The best results in respiratory rate estimation error terms are -1.07 ± 8.86% (-11.47 ± 37.97 mHz). These results suggest that proposed methods based on QRS slopes are highly suitable for respiratory rate estimation from ECG signal, specially at very non-stationary and noise scenarios as stress test.
|
|
| 5. |
- Sandberg, Frida, et al.
(författare)
-
Prediction of hypotension in hemodialysis patients
- 2014
-
Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 35:9, s. 1885-1898
-
Tidskriftsartikel (refereegranskat)abstract
- Intradialytic hypotension (IDH) is the most common adverse complication during hemodialysis. Its early prediction and prevention will dramatically improve the quality of life for patients with an end stage renal disease. In a recent study, changes in the normalized envelope of the test statistic of the photoplethysmograpic (PPG) signal were found to predict acute symptomatic IDH. In the present study, the PPG-based predictor is generalized to include a patient-dependent threshold which incorporates on-line information on heart rate variability and heart rate turbulence. From datasets with patients prone and resistant to IDH, the results show that symptomatic IDH could be correctly predicted in 9 out of 14 cases, while 5 out of 24 were falsely predicted. In a subset of the data containing only patients prone to IDH, acute symptomatic IDH could be correctly predicted in 5 out of 5 cases, with one false prediction out of 14. When testing the robustness of the predictor, no significant changes were observed in the test statistic when controlled changes occurred in dialysis fluid temperature, ultrafiltration rate and body position.
|
|
| 6. |
- Sandberg, Frida, et al.
(författare)
-
Prediction of intradialytic hypotension using PPG and ECG
- 2013
-
Ingår i: 2013 Computing in Cardiology. - 9781479908844 ; 40, s. 1227-1230
-
Konferensbidrag (refereegranskat)abstract
- Intradialytic hypotension (IDH) is the most common complication during hemodialysis; early prediction and prevention of IDH would dramatically improve the living conditions for patients with end stage renal disease. A recently published study suggests that a decrease in the envelope of the photoplethysmograpy (PPG) signal can be used for predicting acute symptomatic IDH. In the present study, the PPG based method is extended by introducing a patient dependent detection threshold, which involves information on heart rate variability (HRV) and heart rate turbulence (HRT) from the current dialysis session. This is motivated since several studies have found significant differences in HRV and HRT between hypotension-prone and hypotension-resistant patients. Recordings from 15 patients during 38 hemodialysis sessions were used to evaluate the method. Symptomatic IDH was correctly predicted in 9 out of 14 cases, while 5 out of 24 cases were falsely predicted. The performance was better for acute symptomatic IDH, 5 out of 5 cases were correctly predicted. The present method represents a novel approach to combining information derived from ECG and PPG signals.
|
|
| 7. |
- Sornmo, Leif, et al.
(författare)
-
Spectral Analysis of Heart Rate Variability in Time-Varying Conditions and in the Presence of Confounding Factors
- 2022
-
Ingår i: IEEE Reviews in Biomedical Engineering. - 1937-3333. ; , s. 1-21
-
Tidskriftsartikel (refereegranskat)abstract
- The tools for spectrally analyzing heart rate variability (HRV) has in recent years grown considerably, with emphasis on the handling of time-varying conditions and confounding factors. Time–frequency analysis holds since long an important position in HRV analysis, however, this technique cannot alone handle a mean heart rate or a respiratory frequency which vary over time. Overlapping frequency bands represents another critical condition which needs to be dealt with to produce accurate spectral measurements. The present survey offers a comprehensive account of techniques designed to handle such conditions and factors by providing a brief description of the main principles of the different methods. Several methods derive from a mathematical/statistical model, suggesting that the model can be used to simulate data used for performance evaluation. The inclusion of a respiratory signal, whether measured or derived, is another feature of many recent methods, e.g., used to guide the decomposition of the HRV signal so that signals related as well as unrelated to respiration can be analyzed. It is concluded that the development of new approaches to handling time-varying scenarios are warranted, as is benchmarking of performance evaluated in technical as well as in physiological/clinical terms.
|
|
| 8. |
- Varon, Carolina, et al.
(författare)
-
A Comparative Study of ECG-derived Respiration in Ambulatory Monitoring using the Single-lead ECG
- 2020
-
Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1
-
Tidskriftsartikel (refereegranskat)abstract
- Cardiorespiratory monitoring is crucial for the diagnosis and management of multiple conditions such as stress and sleep disorders. Therefore, the development of ambulatory systems providing continuous, comfortable, and inexpensive means for monitoring represents an important research topic. Several techniques have been proposed in the literature to derive respiratory information from the ECG signal. Ten methods to compute single-lead ECG-derived respiration (EDR) were compared under multiple conditions, including different recording systems, baseline wander, normal and abnormal breathing patterns, changes in breathing rate, noise, and artifacts. Respiratory rates, wave morphology, and cardiorespiratory information were derived from the ECG and compared to those extracted from a reference respiratory signal. Three datasets were considered for analysis, involving a total 59 482 one-min, single-lead ECG segments recorded from 156 subjects. The results indicate that the methods based on QRS slopes outperform the other methods. This result is particularly interesting since simplicity is crucial for the development of ECG-based ambulatory systems.
|
|
