Accuracy Of Blood Pressure Estimation Research Articles

New photoplethysmogram indicators for improving cuffless and continuous blood pressure estimation accuracy

Objective: The accuracy of cuffless and continuous blood pressure (BP) estimation has been improved, but it is still unsatisfactory for clinical uses. This study was designed to further increase BP estimation accuracy. Approach: In this study, a number of new indicators were extracted from photoplethysmogram (PPG) recordings and a linear regression method was used to construct BP estimation models based on the PPG indicators and pulse transit time (PTT). The performance of the BP estimation models was evaluated by the PPG recordings from 22 subjects when they performed mental arithmetic stress and Valsalva’s manoeuvre tasks that could induce BP fluctuations. Main results: Our results showed that the best PPG-based BP estimation model could achieve a decrease of 0.31 ± 0.08 mmHg in systolic BP (SBP) and 0.33 ± 0.01 mmHg in diastolic BP (DBP) on estimation errors of grand absolute mean (GAM) and standard deviation (GSD) in comparison to the previously reported PPG-based methods. The best estimation model based on the combination of PPG and PPT could achieve a decrease (GAM & GSD) of 0.81 ± 0.95 mmHg in SBP and 0.75 ± 0.54 mmHg in DBP in comparison to the PPT-based methods. Significance: The findings suggest that the newly proposed PPG indicators would be promising for improving the accuracy of continuous and cuffless BP estimation.

Single-source PPG-based local pulse wave velocity measurement: a potential cuffless blood pressure estimation technique

Objective: A novel photoplethysmograph probe employing dual photodiodes excited using a single infrared light source was developed for local pulse wave velocity (PWV) measurement. The potential use of the proposed system in cuffless blood pressure (BP) techniques was demonstrated. Approach: Initial validation measurements were performed on a phantom using a reference method. Further, an in vivo study was carried out in 35 volunteers (age = 28 ± 4.5 years). The carotid local PWV, carotid to finger pulse transit time (PTTR) and pulse arrival time at the carotid artery (PATC) were simultaneously measured. Beat-by-beat variation of the local PWV due to BP changes was studied during post-exercise relaxation. The cuffless BP estimation accuracy of local PWV, PATC, and PTTR was investigated based on inter- and intra-subject models with best-case calibration. Main results: The accuracy of the proposed system, hardware inter-channel delay (<0.1 ms), repeatability (beat-to-beat variation = 4.15%–11.38%) and reproducibility of measurement (r = 0.96) were examined. For the phantom experiment, the measured PWV values did not differ by more than 0.74 m s−1 compared to the reference PWV. Better correlation was observed between brachial BP parameters versus local PWV (r = 0.74–0.78) compared to PTTR (|r| = 0.62–0.67) and PATC (|r| = 0.52–0.68). Cuffless BP estimation using local PWV was better than PTTR and PATC with population-specific models. More accurate estimates of arterial BP levels were achieved using local PWV via subject-specific models (root-mean-square error ⩽2.61 mmHg). Significance: A reliable system for cuffless BP measurement and local estimation of arterial wall properties.

Deep learning ensemble with asymptotic techniques for oscillometric blood pressure estimation

Background and Objective: This paper proposes a deep learning based ensemble regression estimator with asymptotic techniques, and offers a method that can decrease uncertainty for oscillometric blood pressure (BP) measurements using the bootstrap and Monte-Carlo approach. While the former is used to estimate SBP and DBP, the latter attempts to determine confidence intervals (CIs) for SBP and DBP based on oscillometric BP measurements.Method: This work originally employs deep belief networks (DBN)-deep neural networks (DNN) to effectively estimate BPs based on oscillometric measurements. However, there are some inherent problems with these methods. First, it is not easy to determine the best DBN-DNN estimator, and worthy information might be omitted when selecting one DBN-DNN estimator and discarding the others. Additionally, our input feature vectors, obtained from only five measurements per subject, represent a very small sample size; this is a critical weakness when using the DBN-DNN technique and can cause overfitting or underfitting, depending on the structure of the algorithm. To address these problems, an ensemble with an asymptotic approach (based on combining the bootstrap with the DBN-DNN technique) is utilized to generate the pseudo features needed to estimate the SBP and DBP. In the first stage, the bootstrap-aggregation technique is used to create ensemble parameters. Afterward, the AdaBoost approach is employed for the second-stage SBP and DBP estimation. We then use the bootstrap and Monte-Carlo techniques in order to determine the CIs based on the target BP estimated using the DBN-DNN ensemble regression estimator with the asymptotic technique in the third stage.Results: The proposed method can mitigate the estimation uncertainty such as large the standard deviation of error (SDE) on comparing the proposed DBN-DNN ensemble regression estimator with the DBN-DNN single regression estimator, we identify that the SDEs of the SBP and DBP are reduced by 0.58 and 0.57 mmHg, respectively. These indicate that the proposed method actually enhances the performance by 9.18% and 10.88% compared with the DBN-DNN single estimator.Conclusion: The proposed methodology improves the accuracy of BP estimation and reduces the uncertainty for BP estimation.

Using a new PPG indicator to increase the accuracy of PTT-based continuous cuffless blood pressure estimation.

Pulse transit time (PTT) has been identified as a potential indicator to estimate blood pressure (BP) continuously and cufflessly in the previous studies, but it is still unsatisfactory for clinical uses. In order to improve the BP estimation accuracy, another candidate signal, photoplethysmogram (PPG) has been used to estimate continuous BP. In this study, a new PPG indicator, the intensity ratio of the first derivative wave of PPG (1st dPIR), was proposed and a novel BP estimation algorithm by using both PTT and 1st dPIR was developed with an attempt to further increase the BP estimation accuracy. The performance of the proposed algorithm was examined and validated using the ECG and PPG recordings from 22 healthy subjects when they performed both mental arithmetic stress and Valsalva's manoeuvre tests that could induce their BP fluctuations. The continuous Finapres® BP were measured with a finger cuff as a referenced BP value. Our results showed that using the proposed BP estimation algorithm, the grand absolute mean and standard deviation (SD) errors between the estimated and referenced BP were 3.22±8.02 mmHg for systolic BP (SBP) and 3.13±4.82mmHg for diastolic BP (DBP). It could achieve a decrease of 0.34±0.27 mmHg in SBP and 0.33±0.44 mmHg in DBP on the grand absolute mean and SD estimation errors in comparison to the state-of-the-art PPT-based method. Findings from this study suggest that the newly proposed PPG indicator would be promising for improving the accuracy of current PTT-based continuous and cuffless BP estimation algorithms.

Cuff-Less Blood Pressure Estimation Using Pulse Waveform Analysis and Pulse Arrival Time.

Using the massive MIMIC physiological database, we tried to validate pulse wave analysis (PWA) based on multiparameters model whether it can continuously estimate blood pressure (BP) values on single site of one hand. In addition, to consider the limitation of insufficient data acquirement for home user, we used pulse arrival time (PAT) driven BP information to determine the individual scale factors of the PWA-BP estimation model. Experimental results indicate that the accuracy of the average regression model has error standard deviations of mmHg (PAT), mmHg (PWA) for SBP and mmHg (PAT), mmHg (PWA) for DBP on 23 subjects over a 1 day period. We defined a local-model which is extracted regression model from sparsely selected small dataset, contrast to full dataset for 24h (average-model). The limit of BP estimation accuracy from the local-model of PWA is lower than that of PAT-BP average-model. Whereas the error of the BP estimation local-model was reduced using more data for scaling, it required more than four times the 1 min data extracted over the 12 h calibration period to predict BP for 1 day. This study shows that PWA has possibility to estimate BP value and PAT-driven BP information could be used to determine the individual scale factors of the PWA-BP estimation model for home users.

Cuff-less blood pressure measurement using pulse arrival time and a Kalman filter

The present study designs an algorithm to increase the accuracy of continuous blood pressure (BP) estimation. Pulse arrival time (PAT) has been widely used for continuous BP estimation. However, because of motion artifact and physiological activities, PAT-based methods are often troubled with low BP estimation accuracy. This paper used a signal quality modified Kalman filter to track blood pressure changes. A Kalman filter guarantees that BP estimation value is optimal in the sense of minimizing the mean square error. We propose a joint signal quality indice to adjust the measurement noise covariance, pushing the Kalman filter to weigh more heavily on measurements from cleaner data. Twenty 2 h physiological data segments selected from the MIMIC II database were used to evaluate the performance. Compared with straightforward use of the PAT-based linear regression model, the proposed model achieved higher measurement accuracy. Due to low computation complexity, the proposed algorithm can be easily transplanted into wearable sensor devices.

Photoplethysmogram intensity ratio: A potential indicator for improving the accuracy of PTT-based cuffless blood pressure estimation.

The most commonly used method for cuffless blood pressure (BP) measurement is using pulse transit time (PTT), which is based on Moens-Korteweg (M-K) equation underlying the assumption that arterial geometries such as the arterial diameter keep unchanged. However, the arterial diameter is dynamic which varies over the cardiac cycle, and it is regulated through the contraction or relaxation of the vascular smooth muscle innervated primarily by the sympathetic nervous system. This may be one of the main reasons that impair the BP estimation accuracy. In this paper, we propose a novel indicator, the photoplethysmogram (PPG) intensity ratio (PIR), to evaluate the arterial diameter change. The deep breathing (DB) maneuver and Valsalva maneuver (VM) were performed on five healthy subjects for assessing parasympathetic and sympathetic nervous activities, respectively. Heart rate (HR), PTT, PIR and BP were measured from the simultaneously recorded electrocardiogram (ECG), PPG, and continuous BP. It was found that PIR increased significantly from inspiration to expiration during DB, whilst BP dipped correspondingly. Nevertheless, PIR changed positively with BP during VM. In addition, the spectral analysis revealed that the dominant frequency component of PIR, HR and SBP, shifted significantly from high frequency (HF) to low frequency (LF), but not obvious in that of PTT. These results demonstrated that PIR can be potentially used to evaluate the smooth muscle tone which modulates arterial BP in the LF range. The PTT-based BP measurement that take into account the PIR could therefore improve its estimation accuracy.

How sensitive are cardiac surgeons' fingers?

During open heart surgery for many years surgeons have used estimates of arterial and pulmonary artery pressure from direct digital palpation despite the array of monitoring equipment that is in evidence at the time of the operation. The reasons for this range from disbelief in the accuracy of often ancient monitoring equipment to the not uncommonly seen difference between central aortic pressure and peripheral radial artery pressure after cardiopulmonary bypass.1 2 Claims by cardiac surgeons that their digital estimates of pressure may be accurate are often greeted with derision by their anaesthetic and junior surgical colleagues. The purpose of this study was to investigate the accuracy of blood pressure estimation by digital palpation of major vessels during heart surgery by different grades of surgical staff. Subjects were the cardiac surgical staff of one consultant firm. The study was carried out during 18 consecutive open heart operations. After cardiopulmonary …