scholarly journals Poincaré’s Section Analysis of Photoplethysmography Signals for Cuff-Less Non-Invasive Blood Pressure Measurement

2021 ◽  
Author(s):  
Fatemeh Shoeibi ◽  
Esmaeil Najafiaghdam ◽  
Afshin Ebrahimi
Keyword(s):  
Blood Pressure ◽  
Diastolic Pressure ◽  
Blood Pressure Measurement ◽  
Systolic Pressure ◽  
Absolute Error ◽  
Research Area ◽  
Special Importance ◽  
Hardware Complexity ◽  
Non Invasive ◽  
Blood Pressure Estimation

Abstract Background and Objective: Hypertension is a serious problem that has become dramatically more common in recent decades. Hypertension can be managed in its early stages by regular monitoring of blood pressure. Blood pressure, as a vital signal, has an essential role in the prediction of many cardiovascular diseases. Therefore, non-invasive, cuff-less, continuous monitoring of blood pressure has special importance in personal health care. Recently, due to the capabilities of PPG sensors in embedding and compacting as a wearable device, application of the PPG signal and its characteristics as a useful facilities for BP measurement have been highlighted. Methods: This study attempts to provide a new indicator of PPG waveforms to help the rapid developments in this research area. The proof of the feasibility of using Poincaré’s section for extracting the profitable features of the PPG signal for BP estimation is one of the key achievements of this paper. Results: The performance of the method was evaluated on 101 subject’s clinical data from the MIMIC II database. The proposed method obtains a mean absolute error of 2.1 mmHg for systolic pressure and 1.4 mmHg for diastolic pressure prediction. Also, the results meet the AAMI and BHS standards, which demonstrate the feasibility of Poincaré’s section-based indices in BP estimation. Conclusions: The results confirm the proficiency of this method in the blood pressure estimation and a straightforward way to reduce the computational and hardware complexity, which in turn helps to achieve a real-time wearable BP monitoring system.

scholarly journals Wearable Piezoelectric-Based System for Continuous Beat-to-Beat Blood Pressure Measurement

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 851 ◽  
Author(s):  
Ting-Wei Wang ◽  
Shien-Fong Lin
Keyword(s):  
Blood Pressure ◽  
Pressure Measurement ◽  
Blood Pressure Monitoring ◽  
Low Cost ◽  
Blood Pressure Measurement ◽  
Pressure Change ◽  
Absolute Error ◽  
Non Invasive ◽  
Blood Pressure Estimation

Non-invasive continuous blood pressure measurement is an emerging issue that potentially can be applied to cardiovascular disease monitoring and prediction. Recently, many groups have proposed the pulse transition time (PTT) method to estimate blood pressure for long-term monitoring. However, the PTT-based methods for blood pressure estimation are limited by non-specific estimation models and require multiple calibrations. This study aims to develop a low-cost wearable piezoelectric-based system for continuous beat-to-beat blood pressure measurement. The pressure change in the radial artery was extracted by systolic and diastolic feature points in pressure pulse wave (PPW) and the pressure sensitivity of the sensor. The proposed system showed a reliable accuracy of systolic blood pressure (SBP) (mean absolute error (MAE) ± standard deviation (SD) 1.52 ± 0.30 mmHg) and diastolic blood pressure (DBP, MAE ± SD 1.83 ± 0.50), and its performance agreed with standard criteria of MAE within 5 mmHg and SD within ±8 mmHg. In conclusion, this study successfully developed a low-cost, high-accuracy piezoelectric-based system for continuous beat-to-beat SBP and DBP measurement without multiple calibrations and complex regression analysis. The system is potentially suitable for continuous, long-term blood pressure-monitoring applications.

scholarly journals Non-invasive cuff-less blood pressure estimation using a hybrid deep learning model

2021 ◽  
Vol 53 (2) ◽  
Author(s):  
Sen Yang ◽  
Yaping Zhang ◽  
Siu-Yeung Cho ◽  
Ricardo Correia ◽  
Stephen P. Morgan
Keyword(s):  
Machine Learning ◽  
Blood Pressure ◽  
Deep Learning ◽  
Absolute Error ◽  
Learning Model ◽  
Physiological Measurement ◽  
British Hypertension Society ◽  
Non Invasive ◽  
Blood Pressure Estimation ◽  
Deep Learning Model

AbstractConventional blood pressure (BP) measurement methods have different drawbacks such as being invasive, cuff-based or requiring manual operations. There is significant interest in the development of non-invasive, cuff-less and continual BP measurement based on physiological measurement. However, in these methods, extracting features from signals is challenging in the presence of noise or signal distortion. When using machine learning, errors in feature extraction result in errors in BP estimation, therefore, this study explores the use of raw signals as a direct input to a deep learning model. To enable comparison with the traditional machine learning models which use features from the photoplethysmogram and electrocardiogram, a hybrid deep learning model that utilises both raw signals and physical characteristics (age, height, weight and gender) is developed. This hybrid model performs best in terms of both diastolic BP (DBP) and systolic BP (SBP) with the mean absolute error being 3.23 ± 4.75 mmHg and 4.43 ± 6.09 mmHg respectively. DBP and SBP meet the Grade A and Grade B performance requirements of the British Hypertension Society respectively.

Effects of Crossing Legs on Blood Pressure Measurement

2001 ◽  
Vol 10 (2) ◽  
pp. 202-213 ◽  
Author(s):  
Rebecca Keele-Smith ◽  
CeCilia Price-Daniel
Keyword(s):  
Blood Pressure ◽  
Pressure Measurement ◽  
Diastolic Pressure ◽  
Blood Pressure Measurement ◽  
Systolic Pressure ◽  
Nursing Intervention ◽  
Health Condition ◽  
Senior Population

The purpose of this study was to determine if blood pressure measurement is affected by the leg crossed at the knee as compared with feet flat on the floor in a well-senior population. Participants (N = 110) either had their blood pressure measured with feet flat first and then crossed or the reverse of this. Results indicate that blood pressure was significantly higher when legs were crossed versus uncrossed. Systolic pressure changed by 5.9 mmHg, from 127.32 to 133.24, whereas diastolic pressure changed by 2.97, from 72.54 to 75.52. There were no significant differences between those who had their blood pressure measured first with their legs crossed versus uncrossed or between those with and without hypertension. Instructing patients to keep feet flat on the floor during blood pressure measurement is an important nursing intervention that can contribute to the accurate measurement, interpretation, and treatment of a patient's health condition.

Indirect Arterial Blood Pressure Measurement in Nonsedated Irish Wolfhounds: Reference Values for the Breed

2002 ◽  
Vol 38 (6) ◽  
pp. 521-526 ◽  
Author(s):  
Janice M. Bright ◽  
Mariellen Dentino
Keyword(s):  
Blood Pressure ◽  
Arterial Blood Pressure ◽  
Reference Values ◽  
Diastolic Pressure ◽  
Blood Pressure Measurement ◽  
Systolic Pressure ◽  
Standing Position ◽  
Mean Value ◽  
Pressure Measurements ◽  
Arterial Blood

Arterial blood pressure measurements were obtained from 158 healthy Irish wolfhounds using the oscillometric technique to establish reference values for the breed. In contrast to other sight hounds, Irish wolfhounds have low arterial blood pressure. Mean systolic pressure for the group was 116.0 mm Hg. Mean diastolic pressure was 69.2 mm Hg, and the mean value for mean arterial pressure was 87.8 mm Hg. Blood pressure measurements were higher in older wolfhounds than in young dogs. There was no difference between systolic and mean arterial blood pressures in lateral recumbency compared to standing position. However, diastolic pressure was slightly lower when standing. Calm dogs had lower pressure than anxious wolfhounds. There was a significant interaction between the effects of age, gender, and mood on systolic, diastolic, and mean arterial blood pressure values.

scholarly journals PTT-based Contact-less Blood Pressure Measurement using an RGB-Camera

2021 ◽  
Vol 7 (2) ◽  
pp. 375-378
Author(s):  
Carolin Wuerich ◽  
Robin Rademacher ◽  
Christian Wiede ◽  
Anton Grabmaier
Keyword(s):  
Blood Pressure ◽  
Diastolic Blood Pressure ◽  
Pressure Measurement ◽  
Blood Pressure Measurement ◽  
Systolic Pressure ◽  
Pulse Transit Time ◽  
Invasive Blood Pressure ◽  
Non Invasive ◽  
Individual Calibration ◽  
Cardiac System

Abstract Commonly used blood pressure measurement devices have noticeable limitations in accuracy, measuring time, comfort or safety. To overcome these limitations, we developed and tested a surrogate-based, non-invasive blood pressure measurement method using an RGB-camera. Our proposed method employs the relation between the pulse transit time (PTT) and blood pressure. Two remote photoplethysmography (rPPG) signals at different distances from the heart are extracted to calculate the temporal delay of the pulse wave. In order to establish the correlation between the PTT values and the blood pressure, a regression model is trained and evaluated. Tests were performed with five subjects, where each subject was recorded fifteen times for 30 seconds. Since the physiological parameters of the cardiac system are different for each person, an individual calibration is required to obtain the systolic and diastolic blood pressure from the PTT values. The calibration results are limited by the small number of samples and the accuracy of the reference system. However, our results show a strong correlation between the PTT values and the blood pressure and we obtained a mean error of 0.18 +/- 5.50 mmHg for the diastolic blood pressure and 0.01 +/- 7.71 mmHg for the systolic pressure, respectively.

scholarly journals Pulse Transit Time Derivation Using Xiphoidal and Carotid Seismocardiograms

2017 ◽  
Author(s):  
Ajay K. Verma ◽  
John Zanetti ◽  
Reza Fazel-Rezai ◽  
Kouhyar Tavakolian
Keyword(s):  
Blood Pressure ◽  
Aortic Valve ◽  
Transit Time ◽  
Pulse Wave ◽  
Blood Pressure Measurement ◽  
Pulse Transit Time ◽  
Non Invasive ◽  
Arterial Blood ◽  
Pressure Estimation ◽  
Blood Pressure Estimation

Blood pressure is an indicator of a cardiovascular functioning and could provide early symptoms of cardiovascular system impairment. Blood pressure measurement using catheterization technique is considered the gold standard for blood pressure measurement [1]. However, due its invasive nature and complexity, non-invasive techniques of blood pressure estimation such as auscultation, oscillometry, and volume clamping have gained wide popularity [1]. While these non-invasive cuff based methodologies provide a good estimate of blood pressure, they are limited by their inability to provide a continuous estimate of blood pressure [1–2]. Continuous blood pressure estimate is critical for monitoring cardiovascular diseases such as hypertension and heart failure. Pulse transit time (PTT) is a time taken by a pulse wave to travel between a proximal and distal arterial site [3]. The speed at which pulse wave travels in the artery has been found to be proportional to blood pressure [1, 3]. A rise in blood pressure would cause blood vessels to increase in diameter resulting in a stiffer arterial wall and shorter PTT [1–3]. To avail such relationship with blood pressure, PTT has been extensively used as a marker of arterial elasticity and a non-invasive surrogate for arterial blood pressure estimation. Typically, a combination of electrocardiogram (ECG) and photoplethysmogram (PPG) or arterial blood pressure (ABP) signal is used for the purpose of blood pressure estimation [3], where the proximal and distal timing of PTT (also referred as pulse arrival time, PAT) is marked by R peak of ECG and a foot/peak of a PPG, respectively. In the literature, it has been shown that PAT derived using ECG-PPG combination infers an inaccurate estimate of blood pressure due to the inclusion of isovolumetric contraction period [1–3, 4]. Seismocardiogram (SCG) is a recording of chest acceleration due to heart movement, from which the opening and closing of the aortic valve can be obtained [5]. There is a distinct point on the dorso-ventral SCG signal that marks the opening of the aortic valve (annotated as AO). In the literature, AO has been proposed for timing the onset of the proximal pulse of the wave [6–8]. A combination of AO as a proximal pulse and PPG as a distal pulse has been used to derive pulse transit time and is shown to be correlated with blood pressure [7]. Ballistocardiogram (BCG) which is a measure of recoil forces of a human body in response to pumping of blood in blood vessels has also been explored as an alternative to ECG for timing proximal pulse [5, 9]. Use of SCG or BCG for timing the proximal point of a pulse can overcome the limitation of ECG-based PTT computation [6–7, 9]. However, a limitation of current blood pressure estimation systems is the requirement of two morphologically different signals, one for annotating the proximal (ECG, SCG, BCG) and other for annotating the distal (PPG, ABP) timing of a pulse wave. In the current research, we introduce a methodology to derive PTT from seismocardiograms alone. Two accelerometers were used for such purpose, one was placed on the xiphoid process of the sternum (marks proximal timing) and the other one was placed on the external carotid artery (marks distal timing). PTT was derived as a time taken by a pulse wave to travel between AO of both the xiphoidal and carotid SCG.

scholarly journals Advanced Bio-Inspired System for Noninvasive Cuff-Less Blood Pressure Estimation from Physiological Signal Analysis

Computation ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 46 ◽  
Author(s):  
Francesco Rundo ◽  
Alessandro Ortis ◽  
Sebastiano Battiato ◽  
Sabrina Conoci
Keyword(s):  
Blood Pressure ◽  
Ad Hoc ◽  
Diastolic Pressure ◽  
Skin Surface ◽  
Physiological Data ◽  
Measuring Device ◽  
Physiological Signal ◽  
Non Invasive ◽  
Pressure Estimation ◽  
Blood Pressure Estimation

Blood Pressure (BP) is one of the most important physiological indicators that provides useful information in the field of health-care monitoring. Blood pressure may be measured by both invasive and non-invasive methods. A novel algorithmic approach is presented to estimate systolic and diastolic blood pressure accurately in a way that does not require any explicit user calibration, i.e., it is non-invasive and cuff-less. The approach herein described can be applied in a medical device, as well as in commercial mobile smartphones by an ad hoc developed software based on the proposed algorithm. The authors propose a system suitable for blood pressure estimation based on the PhotoPlethysmoGraphy (PPG) physiological signal sampling time-series. Photoplethysmography is a simple optical technique that can be used to detect blood volume changes in the microvascular bed of tissue. It is non-invasive since it takes measurements at the skin surface. In this paper, the authors present an easy and smart method to measure BP through careful neural and mathematical analysis of the PPG signals. The PPG data are processed with an ad hoc bio-inspired mathematical model that estimates systolic and diastolic pressure values through an innovative analysis of the collected physiological data. We compared our results with those measured using a classical cuff-based blood pressure measuring device with encouraging results of about 97% accuracy.

scholarly journals PERBANDINGAN TEKANAN DARAH ANTARA ANAK YANG TINGGAL DI PEGUNUNGAN DAN PESISIR PANTAI

e-CliniC ◽  
2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Queen Mandang ◽  
Adrian Umboh ◽  
Stefanus Gunawan
Keyword(s):  
Blood Pressure ◽  
Diastolic Pressure ◽  
Sodium Intake ◽  
Blood Pressure Measurement ◽  
Systolic Pressure ◽  
Coastal Areas ◽  
Cross Sectional ◽  
The Difference ◽  
Cross Sectional Design ◽  
History Of Obesity

Abstract: Blood pressure in children varies because there are many factors that influence. One is geographic factors. Based on data from the Health Research in 2007 found that the prevalence of hypertension is highest in coastal areas while the lowest prevalence of hypertension in the coastal area. Altitude and different sodium intake on mountain and coastal areas are assumed to affect the blood pressure. This study aimed to determine the difference in blood pressure between children who live in the mountains and in the coast. We used descriptive analytic method with cross sectional design, with 107 samples according to criteria of children aged 6-12 years with no family history of obesity and hypertension. Data were obtained by using questionnaire, measurement of weight and height (BMI) and blood pressure measurement using a sphygmomanometer and cuff child. The results showed 15.5% of children with high-normal systolic pressure and 17.4% of children with high diastolic pressure in the mountains. In coastal areas, found 28% of children with normal systolic pressure-high, 13% of children of normal-high diastolic pressure, and 5% of children of high diastolic pressure. These data were analyzed using Mann Whitney test, showing the results were not statistically significantly systolic (p = 0.815) diastolic (p = 0.221) so that H0 and H1 is rejected. Conclusion: There was no difference in blood pressure among children aged 6-12 years who live in the mountains and the coast.Keywords: child's blood pressure, mountains, coastal.Abstrak: Tekanan darah pada anak bervariasi karena ada banyak faktor yang memengaruhi. Salah satunya adalah faktor geografis. Berdasarkan data Riset Kesehatan Dasar tahun 2007 didapatkan prevalensi hipertensi tertinggi di wilayah pantai sedangkan prevalensi hipertensi terendah di wilayah pantai. Ketinggian lokasi dan asupan natrium yang berbeda pada daerah pegunungan dan pesisir pantai diasumsikan berpengaruh terhadap tekanan darah. Penelitian ini bertujuan untuk mengetahui perbedaan tekanan darah antara anak yang tinggal di pegunungan dan pesisir pantai. Metode penelitian deskriptif analitik dengan rancangan potong lintang, dengan 107 sampel sesuai kriteria anak umur 6-12 tahun tanpa obesitas dan riwayat keluarga hipertensi. Data diperoleh melalui kuesioner, pengukuran berat badan dan tinggi badan (IMT) dan pengukuran tekanan darah menggunakan sphygmomanometer dan manset anak. Hasil penelitian menunjukkan 15,5% anak dengan tekanan sistolik normal-tinggi dan 17,4% anak dengan tekanan diastolik tinggi pada daerah pegunungan. Pada daerah pesisir pantai ditemukan 28% anak dengan tekanan sistolik normal-tinggi, 13% anak tekanan diastolik normal-tinggi, dan 5% anak tekanan diastolik tinggi. Data ini dianalisis menggunakan uji mann whitney, menunjukkan hasil secara statistik tidak bermakna sistolik (p=0,815) diastolik (p=0,221) sehingga H0 diterima dan H1 ditolak. Simpulan: Tidak ada perbedaan tekanan darah antara anak berumur 6-12 tahun yang tinggal di pegunungan dan pesisir pantai.Kata kunci: tekanan darah anak, pegunungan, pantai.

scholarly journals Combined deep CNN–LSTM network-based multitasking learning architecture for noninvasive continuous blood pressure estimation using difference in ECG-PPG features

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Da Un Jeong ◽  
Ki Moo Lim
Keyword(s):  
Blood Pressure ◽  
Blood Pressure Measurement ◽  
Patient Specific ◽  
Peak Time ◽  
Simultaneous Prediction ◽  
Deep Cnn ◽  
Pressure Estimation ◽  
The Difference ◽  
Blood Pressure Estimation ◽  
Continuous Blood Pressure

AbstractThe pulse arrival time (PAT), the difference between the R-peak time of electrocardiogram (ECG) signal and the systolic peak of photoplethysmography (PPG) signal, is an indicator that enables noninvasive and continuous blood pressure estimation. However, it is difficult to accurately measure PAT from ECG and PPG signals because they have inconsistent shapes owing to patient-specific physical characteristics, pathological conditions, and movements. Accordingly, complex preprocessing is required to estimate blood pressure based on PAT. In this paper, as an alternative solution, we propose a noninvasive continuous algorithm using the difference between ECG and PPG as a new feature that can include PAT information. The proposed algorithm is a deep CNN–LSTM-based multitasking machine learning model that outputs simultaneous prediction results of systolic (SBP) and diastolic blood pressures (DBP). We used a total of 48 patients on the PhysioNet website by splitting them into 38 patients for training and 10 patients for testing. The prediction accuracies of SBP and DBP were 0.0 ± 1.6 mmHg and 0.2 ± 1.3 mmHg, respectively. Even though the proposed model was assessed with only 10 patients, this result was satisfied with three guidelines, which are the BHS, AAMI, and IEEE standards for blood pressure measurement devices.

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