Validation of the optical Aktiia bracelet in different body positions for the persistent monitoring of blood pressure.

The diagnosis of hypertension and the adjustment of antihypertensive drugs are evolving from isolated measurements performed at the physician offices to the full phenotyping of patients in real-life conditions. Indeed, the strongest predictor of cardiovascular risk comes from night measurements. The aim of this study was to demonstrate that a wearable device (the Aktiia Bracelet) can accurately estimate BP in the most common body positions of daily life and thus become a candidate solution for the BP phenotyping of patients. We recruited 91 patients with BP ranging from low to hypertensive levels and compared BP values from the Aktiia Bracelet against auscultatory reference values for 4 weeks according to an extended ISO 81060-2 protocol. After initializing on day one, the observed means and standard deviations of differences for systolic BP were of 0.46 ± 7.75 mmHg in the sitting position, - 2.44 ± 10.15 mmHg in the lying, - 3.02 ± 6.10 mmHg in the sitting with the device on the lap, and - 0.62 ± 12.51 mmHg in the standing position. Differences for diastolic BP readings were respectively of 0.39 ± 6.86 mmHg, - 1.93 ± 7.65 mmHg, - 4.22 ± 6.56 mmHg and - 4.85 ± 9.11 mmHg. This study demonstrates that a wearable device can accurately estimate BP in the most common body positions compared to auscultation, although precision varies across positions. While wearable persistent BP monitors have the potential to facilitate the identification of individual BP phenotypes at scale, their prognostic value for cardiovascular events and its association with target organ damage will need cross-sectional and longitudinal studies. Deploying this technology at a community level may be also useful to drive public health interventions against the epidemy of hypertension

Validation of the optical Aktiia bracelet in different body positions for the persistent monitoring of blood pressure.

The diagnosis of hypertension and the adjustment of antihypertensive drugs are evolving from isolated measurements performed at the physician offices to the full phenotyping of patients in real-life conditions. Indeed, the strongest predictor of cardiovascular risk comes from night measurements. The aim of this study was to demonstrate that a wearable device (the Aktiia Bracelet) can accurately estimate BP in the most common body positions of daily life and thus become a candidate solution for the BP phenotyping of patients. We recruited 91 patients with BP ranging from low to hypertensive levels and compared BP values from the Aktiia Bracelet against auscultatory reference values for 4 weeks according to an extended ISO 81060-2 protocol. After initializing on day one, the observed means and standard deviations of differences for systolic BP were of 0.46 ± 7.75 mmHg in the sitting position, - 2.44 ± 10.15 mmHg in the lying, - 3.02 ± 6.10 mmHg in the sitting with the device on the lap, and - 0.62 ± 12.51 mmHg in the standing position. Differences for diastolic BP readings were respectively of 0.39 ± 6.86 mmHg, - 1.93 ± 7.65 mmHg, - 4.22 ± 6.56 mmHg and - 4.85 ± 9.11 mmHg. This study demonstrates that a wearable device can accurately estimate BP in the most common body positions compared to auscultation, although precision varies across positions. While wearable persistent BP monitors have the potential to facilitate the identification of individual BP phenotypes at scale, their prognostic value for cardiovascular events and its association with target organ damage will need cross-sectional and longitudinal studies. Deploying this technology at a community level may be also useful to drive public health interventions against the epidemy of hypertension

Wireless Chest Wearable Vital Sign Monitoring Platform for Hypertension

Hypertension, a silent killer, is the biggest challenge of the 21 st century in public health agencies worldwide. World Health Organization (WHO) statistic shows that the mortality rate of hypertension is 9.4 million per year and causes 55.3% of total deaths in cardiovascular (CV) patients. Early detection and prevention of hypertension can significantly reduce the CV mortality. We are presenting a wireless chest wearable vital sign monitoring platform. It measures Electrocardiogram (ECG), Photoplethsmogram (PPG) and Ballistocardiogram (BCG) signals and sends data over Bluetooth low energy (BLE) to mobile phone-acts as a gateway. A custom android application relays the data to thingspeak server where MATLAB based offline analysis estimates the blood pressure. A server reacts on the health of subject to friends and family on the social media - twitter. The chest provides a natural position for the sensor to capture legitimate signals for hypertension condition. We have done a clinical technical evaluation of prototypes on 11 normotensive subjects, 9 males 2 females

A model-based calibration method for the design of wearable and cuffless devices measuring arterial blood pressure.

Liu, Yinbo.Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.Includes bibliographical references (leaves 74-79).Abstracts in English and Chinese.Abstract --- p.iList of Figures --- p.ivList of Tables --- p.viiiIntroduction --- p.1Chapter 1.1 --- Current status of Blood Pressure Management --- p.1Chapter 1.2 --- Current Status of Noninvasive Blood Pressure Measurement Techniques --- p.4Chapter 1.3 --- Motivations and Objectives of This Thesis --- p.9Chapter 1.4 --- Organization of This Thesis --- p.9Backgrounds --- p.11Chapter 2.1 --- Principle of the Pulse Transit Time-based Approach for BP Measurement --- p.11Chapter 2.1.1 --- General Descriptions --- p.11Chapter 2.1.2 --- Pressure Wave Propagation in Cylindrical Arteries --- p.13Chapter 2.1.3 --- Determining the PTT for BP Measurement --- p.14Chapter 2.2 --- Backgrounds for Pressure Related Elastic Properties of Artery --- p.17Chapter 2.2.1 --- Transmural Pressure and Its Components --- p.17Chapter 2.2.2 --- Volume-pressure Models --- p.19Chapter 2.2.3 --- Types and Structure of the Artery and Its Properties --- p.20Chapter 2.3 --- Literature Review on the Calibration Methods for Cuffless Blood Pressure Measurements --- p.22Chapter 2.4 --- Section Summary --- p.25Investigations on Factors Affecting PTT or BP --- p.26Chapter 3.1 --- The Effects of External Pressure --- p.26Chapter 3.1.1 --- Background --- p.26Chapter 3.1.2 --- Experimental protocol --- p.28Chapter 3.1.3 --- Analysis for the Effects of External Pressure on PTT --- p.30Chapter 3.1.4 --- Section Discussions --- p.31Chapter 3.2 --- The Effects of Hydrostatic Pressure --- p.32Chapter 3.2.1 --- Experimental protocol --- p.33Chapter 3.2.2 --- Analysis for the Effects of Hydrostatic Pressure on PTT --- p.34Chapter 3.2.3 --- Section Discussions --- p.37Chapter 3.2.4 --- Section Summary --- p.38Modeling the Effect of Hydrostatic Pressure on PTT for A Calibration Method --- p.39Chapter 4.1 --- Current Status of Hydrostatic Calibration Approaches --- p.39Chapter 4.2. --- Modeling Pulse Transit Time under the Effects of Hydrostatic Pressure for A Hydrostatic Calibration Method: --- p.40Chapter 4.2.1 --- Basic BP-PTT model --- p.40Chapter 4.2.2 --- V-P relationship Represented by a Sigmoid Curve --- p.40Chapter 4.2.3 --- Relating PTT with Hydrostatic Pressure --- p.41Chapter 4.2.4 --- Implementing the Hydrostatic Calibration Method for BP Estimation --- p.43Chapter 4.3. --- Preliminary Experiment --- p.44Chapter 4.3.1. --- Experimental Protocol and Methodology --- p.44Chapter 4.3.2. --- Experimental Analysis --- p.46Chapter 4.4. --- Section Discussions --- p.48Chapter 4.5. --- A Novel Implementation Algorithm of Hydrostatic Calibration Method for Cuffless BP Estimation --- p.49Chapter 4.6. --- Section Summary --- p.50Experimental Studies for the Hydrostatic Calibration Approach --- p.51Chapter 5.1 --- Experimental Analysis --- p.51Chapter 5.1.1 --- Experimental Protocol --- p.51Chapter 5.1.2 --- Methodology --- p.53Chapter 5.1.3 --- Preparations --- p.54Chapter 5.1.4 --- Experimental Results --- p.56Chapter 5.2 --- Section Discussions --- p.63Chapter 5.3 --- Section Summary --- p.70Conclusions and Suggestions for Future Works --- p.71Chapter 6.1 --- Conclusions --- p.71Chapter 6.2 --- Suggestions for Future Works --- p.72Reference --- p.7

Cuffless calibration and estimation of continuous arterial blood pressure.

Gu, Wenbo.Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.Includes bibliographical references.Abstract also in Chinese.Acknowledgment --- p.iAbstract --- p.ii摘要 --- p.iiiList of Figures --- p.viList of Tables --- p.viiList of Abbreviations --- p.viiiContents --- p.ixChapter 1. --- Introduction --- p.1Chapter 1.1. --- Arterial blood pressure and its importance --- p.1Chapter 1.2. --- Current methods for non-invasive blood pressure measurement --- p.4Chapter 1.2.1. --- The auscultatory method (mercury sphygmomanometer) --- p.4Chapter 1.2.2. --- The oscillometric method --- p.5Chapter 1.2.3. --- The tonometric method --- p.7Chapter 1.2.4. --- The volume-clamp method --- p.7Chapter 1.3. --- Blood pressure estimation based on pulse arrival time --- p.8Chapter 1.4. --- Objectives and structures of this thesis --- p.10Chapter 2. --- Hemodynamic models: relationship between PAT and BP --- p.14Chapter 2.1. --- The generation of arterial pulsation --- p.14Chapter 2.2. --- Pulse wave velocity along the arterial wall --- p.15Chapter 2.2.1. --- Moens-Korteweg equation --- p.15Chapter 2.2.2. --- Bergel wave velocity --- p.18Chapter 2.3. --- Relationship between PWV and BP --- p.19Chapter 2.3.1. --- Bramwell-Hill´ةs model --- p.20Chapter 2.3.2. --- Volume-pressure relationship --- p.20Chapter 2.3.3. --- Hughes' model --- p.22Chapter 2.4. --- The theoretical expression of PAT-BP relationship --- p.23Chapter 3. --- Estimation and calibration of arterial BP based on PAT --- p.25Chapter 3.1. --- PAT measurement --- p.25Chapter 3.1.1. --- Principle of ECG measurement --- p.25Chapter 3.1.2. --- Principle of PPG measurement --- p.26Chapter 3.1.3. --- Calculation of PAT --- p.28Chapter 3.2. --- Calibration methods for PAT-BP estimation --- p.29Chapter 3.2.1. --- Calibration based on cuff BP readings --- p.30Chapter 3.2.2. --- Calibration by hydrostatic pressure changes --- p.31Chapter 3.2.3. --- Calibration by multiple regression --- p.33Chapter 3.3. --- Model-based calibration with PPG waveform parameters --- p.34Chapter 3.3.1. --- Model-based equation with parameters from PPG waveform --- p.34Chapter 3.3.2. --- Selection of parameters from PPG waveform --- p.36Chapter 4. --- Cuffless calibration approach using PPG waveform parameter for PAT-BP estimation --- p.43Chapter 4.1. --- Introduction --- p.43Chapter 4.2. --- Experiment I: young group in sitting position including rest and after exercise states --- p.43Chapter 4.2.1. --- Experiment protocol --- p.43Chapter 4.2.2. --- Data Analysis --- p.44Chapter 4.2.3. --- Experiment results --- p.46Chapter 4.3. --- Experiment II: over-month observation using wearable device in sitting position --- p.48Chapter 4.3.1. --- Body sensor network for blood pressure estimation --- p.49Chapter 4.3.2. --- Experiment protocol and data collection --- p.50Chapter 4.3.3. --- Experiment results --- p.50Chapter 4.4. --- Experiment III: contactless monitoring in supine position --- p.51Chapter 4.4.1. --- The design of the contactless system --- p.52Chapter 4.4.2. --- Experiment protocol and data collection --- p.53Chapter 4.4.3. --- Experiment results --- p.53Chapter 4.5. --- Discussion --- p.55Chapter 4.5.1. --- Discussion of Experiments I and II --- p.55Chapter 4.5.2. --- Discussion of Experiments II and III --- p.57Chapter 4.5.3. --- Conclusion --- p.58Chapter 5. --- Cuff-based calibration approach for BP estimation in supine position --- p.61Chapter 5.1. --- Introduction --- p.61Chapter 5.2. --- Experiment protocol --- p.61Chapter 5.2.1. --- Experiment IV: exercise experiment in supine position in lab --- p.61Chapter 5.2.2. --- Experiment V: exercise experiment in supine position in PWH --- p.63Chapter 5.3. --- Data analysis --- p.65Chapter 5.3.1. --- Partition of signal trials and selection of datasets --- p.65Chapter 5.3.2. --- PPG waveform processing --- p.66Chapter 5.4. --- Experiment results --- p.68Chapter 5.4.1. --- Range and variation of reference SBP --- p.68Chapter 5.4.2. --- PAT-BP individual best regression --- p.69Chapter 5.4.3. --- Multiple regression using ZX and arm length --- p.72Chapter 5.4.4. --- One-cuff calibration improved by PPG waveform parameter --- p.72Chapter 5.5. --- Discussion --- p.74Chapter 6. --- Conclusion --- p.7

Measurement of Blood Pressure Using an Arterial Pulsimeter Equipped with a Hall Device

To measure precise blood pressure (BP) and pulse rate without using a cuff, we have developed an arterial pulsimeter consisting of a small, portable apparatus incorporating a Hall device. Regression analysis of the pulse wave measured during testing of the arterial pulsimeter was conducted using two equations of the BP algorithm. The estimated values of BP obtained by the cuffless arterial pulsimeter over 5 s were compared with values obtained using electronic or liquid mercury BP meters. The standard deviation between the estimated values and the measured values for systolic and diastolic BP were 8.3 and 4.9, respectively, which are close to the range of values of the BP International Standard. Detailed analysis of the pulse wave measured by the cuffless radial artery pulsimeter by detecting changes in the magnetic field can be used to develop a new diagnostic algorithm for BP, which can be applied to new medical apparatus such as the radial artery pulsimeter

Evaluation of pulse transit time for different sensing methodologies of arterial waveforms.

We perform a novel comparative analysis between optically and mechanically derived pulse transit time (PTT), which is a universally employed technique for cuffless blood pressure (BP) estimation. Two inline photoplethysmogram (PPG) sensors were placed at the distal and proximal phalanxes of the index finger, and two finger ballistocardiogram (BPP) sensors were wrapped on top of the PPG sensors fixture around the phalanxes of the index finger. The stacking of the BPP sensor over the PPG sensor provided vertical spatial alignment for same location acquisition of the blood flow waveform through the radial artery. The analysis of variance (ANOVA) between PTT derived from the PPG and BPP sensors resulted in a statistically significant difference at p < 0.05. The PTT derived from the BPP sensors showed higher values (17.8 milliseconds on average) than the PTT derived from the PPG sensors. Higher accuracy PTT values will improve the estimation of cuffless BP and thus has the potential to revolutionize the technology

커프리스 방식의 착용형 연속 혈압 모니터링 시스템에 관한 연구

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 협동과정 바이오엔지니어링전공, 2019. 2. 김희찬.고혈압의 조기 진단과 고혈압 환자의 혈압 관리를 위해서는 일상생활에서의 지속적인 혈압 모니터링이 중요하다. 맥파전달시간 (Pulse transit time, PTT) 기반의 혈압 추정 방식이 이를 가능케 하는 방법으로 가장 각광 받고 있지만, 맥파전달시간을 측정하기 위해서는 여러 측정 장치들이 필요하여 일상 생활에서의 사용에 제약이 있으며, 또한 맥파전달시간 만을 이용한 수축기 혈압(Systolic blood pressure, SBP) 추정 능력은 부족함이 있는 것으로 알려져 있다. 본 학위 논문의 첫 번째 목적은 맥파전달시간 측정 시스템을 착용형으로 개발하여 간편하게 맥파전달시간을 측정할 수 있도록 함으로써 일상 생활 중 맥파전달시간을 이용한 연속적인 혈압 모니터링이 가능케 하는 것이다. 이를 위해 광용적맥파 (Photoplethysmogram, PPG) 와 심진도 (Seismocardiogram, SCG)를 동시에 측정하는 가슴 착용형 단일 장치를 개발하여, 심진도로부터 대동맥 판막의 열리는 시점을, 광용적맥파로부터 맥파의 도착 시점을 특정하여 맥파 전달 시간을 측정하였다. 개발된 시스템은 낮은 전력 소모와 소형의 간편한 디자인을 통해 24시간 동안 연속적으로 사용할 수 있도록 설계되었다. 측정된 생체신호로부터 추출된 맥파전달시간 및 기타 혈압 관련 변수들이 기기의 반복 착용에도 변하지 않음을 급간내상관계수(Intra-class correlation, ICC) 분석을 통해 확인하였고 (ICC >0.8), 또한 본 시스템에서 사용된 심진도가 대동맥 판막의 열리는 시점의 레퍼런스가 될 수 있는지도 심저항신호(Impedancecardiogram, ICG)와의 비교를 통해 검증하였다(r=0.79±0.14). 둘째로, 개발된 시스템을 이용하여 기존의 맥파 전달 시간만을 이용한 혈압 추정 방식을 보완하여 수축기 혈압의 추정 능력이 향상된 알고리즘을 개발하였다. 이를 위해, 심진도의 진폭과 맥파 전달 시간을 같이 사용하는 다변수 모델을 수축기 혈압 추정을 위해 제안하였고, 다양한 방법으로 유도된 혈압 변화 상황에서, 기존의 맥파전달시간 혹은 맥파도달시간 (Pulse arrival time, PAT) 만을 이용한 모델과 그 성능을 비교하였다. 또한, 제안된 모델이 간단한 교정절차를 통해 여러 사람에게 적용될 수 있는 가능성을 살펴보았고 더 나아가 일상 생활에서의 사용 가능성에 대해서도 검증하였다. 그 결과로 제안된 모델은 (1) 기존의 맥파전달시간 혹은 맥파도달시간 만을 이용한 모델보다 수축기 혈압 추정 능력 측면에서 더 우수하였고, (각각의 평균절대오차는 4.57, 6.01, 6,11 mmHg 였다.) (2) 간단한 교정절차만을 통해서 여러 사람에게 적용 되었을 때의 추정 능력이 국제 기준에 부합하였으며, (3) 일상 생활에서도 사용자의 아무런 개입이나 제약 없이 지속적인 혈압 모니터링이 가능함을 확인하였다. 결론적으로 본 연구에서 제안하는 착용형 연속 혈압 측정 시스템은 가슴에 부착하는 단일 기기 형태로 그 사용이 간편할 뿐 아니라 일상생활 중에서 맥파전달시간과 심진도의 진폭을 이용하여 향상된 수준의 연속 혈압 모니터링 성능을 제공하였는바, 이를 이용한 모바일 헬스케어 서비스의 가능성을 확인하였다.Continuous blood pressure (BP) monitoring is needed in daily life to enable early detection of hypertension and improve control of BP for hypertensive patients. Although the pulse transit time (PTT)-based BP estimation represents one of most promising approaches, its use in daily life is limited owing to the requirement of multi systems to measure PTT, and its performance in systolic blood pressure (SBP) estimation is not yet satisfactory. The first goal of this study is to develop a wearable system providing convenient measurement of the PTT, which facilitates continuous BP monitoring based on PTT in daily life. A single chest-worn device was developed measuring a photoplethysmogram (PPG) and a seismocardiogram (SCG) simultaneously, thereby obtaining PTT by using the SCG as timing reference of the aortic valve opening and the PPG as timing reference of pulse arrival. The presented device was designed to be compact and convenient to use, and to last for 24h by reducing power consumption of the system. The consistency of BP related parameters extracted from the system including PTT between repetitive measurements was verified by an intra-class correlation analysis, and it was over 0.8 for all parameters. In addition, the use of SCG as timing reference of the aortic valve opening was verified by comparing it with an impedance cardiogram (r = 0.79 ± 0.14). Secondly, the algorithm improving the performance of the SBP estimation was developed by using the presented system. A multivariate model using SCG amplitude (SA) in conjunction with PTT was proposed for SBP estimation, and was compared with conventional models using only PTT or pulse arrival time (PAT) in various interventions inducing BP changes. Furthermore, we validated the proposed model against the general population with a simple calibration process and verified its potential for daily use. The results suggested that (1) the proposed model, which employed SA in conjunction with PTT for SBP estimation, outperformed the conventional univariate model using PTT or PAT (the mean absolute errors were of 4.57, 6.01, and 6.11 for the proposed, PTT, and PAT models, respectively)(2) for practical use, the proposed model showed potential to be generalized with a simple calibrationand (3) the proposed model and system demonstrated the potential for continuous BP monitoring in daily life without any intervention of users or regulations. In conclusion, the presented system provides an improved performance of continuous BP monitoring in daily life by using a combination of PTT and SA with a convenient and compact single chest-worn device, and thus, it can contribute to mobile healthcare services.CONTENTS Abstract i Contents v List of Tables ix List of Figures xi List of Abbreviations xvi Chapter 1 1 General Introduction 1.1. Blood pressure 2 1.2. Pulse transit time 6 1.3. Thesis objective 12 Chapter 2 14 Development of the Wearable Blood Pressure Monitoring System 2.1. Introduction 15 2.2. System overview 17 2.3. Bio-signal instrumentation 21 2.4. Power management 24 2.5. PCB and case design 25 2.6. Software Design 27 2.7. Signal Processing 30 2.8. Experimental setup 34 2.8.1. Repeatability test 34 2.8.2. Verification of SCG-based PEP 35 2.9. Results and Discussion 38 2.9.1. Repeatability test 38 2.9.2. Verification of SCG-based PEP 40 Chapter 3 43 Enhancement of PTT based BP estimation 3.1. Introduction 44 3.2. Method 47 3.2.1. Principle of BP estimation 47 3.2.2. Subjects 49 3.2.3. Study protocol 50 3.2.4. Data collection 56 3.2.5. Data analysis 60 3.2.6. Evaluation standard 64 3.3. Results 67 3.4. Discussion 96 Chapter 4 113 Conclusion 4.1. Thesis Summary and Contributions 114 4.2. Future Direction 116 Bibliography 118 Abstract in Korean 128Docto

A Novel smart jacket for blood pressure measurement based on shape memory alloys

Smart textiles with medical applications offer the possibility of continuous and non-invasively monitoring which benefit patients and doctors. To measure blood pressure in premature infants a miniature actuator that can be sewn to the fabric is required. For this reason, an actuator based on shape memory alloys has been designed so that it compresses as a conventional air cuff but with 3.5W power consumption and can be controlled by applying different Pulse-Width Modulation (PWM) signals, thus offering several levels of compression. In addition, the first concept prototype of the smart jacket is achieved; made of a natural fiber fabric that incorporates: an optical sensor, a capacitive pressure sensor with great accuracy, the force actuator and a Lilypad Simblee control board which can be sewn to the fabric, is washable and has a Low Energy Bluetooh module (BBE) to connect to other devices. All this allows the systolic, diastolic and cardiac pressure to be measured for the first time in the world with the smart jacket by a semi-occlusive method. Altogether with a mobile application which allows doctors to monitor the patient at every moment, perform remote control, data measurement and recording in a comfortable and intuitive way that satisfies the necessity for a better clinical management to the growing number of patients and is a source of savings for the clinical services