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

Blood pressure from the optical Aktiia Bracelet: a 1-month validation study using an extended ISO81060-2 protocol adapted for a cuffless wrist device.

The objective of this study (NCT04027777) was to assess the accuracy and precision of the Aktiia Bracelet, a CE-marked noninvasive optical blood pressure (BP) monitor worn at the wrist, over a period of 1 month. In this study, participants aged between 21 and 65 years were recruited. The clinical investigation extended the ISO81060-2:2013 standard to the specificities of cuffless devices. Each BP assessment consisted of the simultaneous recording of optical signals with Aktiia Bracelet and double-blinded auscultation by two trained observers in the standard sitting position. The algorithms of Aktiia Bracelet further processed the recorded optical signals to perform a signal quality check and to calculate uncalibrated estimates of systolic BP (SBP) and diastolic BP (DBP). These estimates were transformed into mmHg using a subject-dependent calibration parameter, which was calculated using the first two available reference measurements per subject. Eighty-six participants were included in the analysis. The mean and SD of the differences between Aktiia Bracelet estimates and the reference (ISO81060-2 criterion 1) were 0.46 ± 7.75 mmHg for SBP and 0.39 ± 6.86 mmHg for DBP. The SD of the averaged paired difference per subject (ISO81060-2 criterion 2) were 3.9 mmHg for SBP and 3.6 mmHg for DBP. After initialization and during 1 month, the overall accuracy of Aktiia Bracelet satisfied validation criteria 1 and 2 of ISO81060-2 in the sitting position. The Aktiia Bracelet can be recommended for BP measurement in the adult population

Editorial: Non-invasive physiological measurements: from discovery to implementation

The goal of this Research Topic, developed by the American College of Sports Medicine Non-Invasive Physiology (ACSM-NIP) interest group, was to demystify and increase the accessibility of non-invasive physiological measurement tools and procedures. The nomenclature “noninvasive physiological measurement” typically conjures imagery of laboratory wizardry and blue-skies science (e.g., where real-world applications are not immediately apparent). However, compared to invasive measurements, noninvasive physiological measurements often reduce financial and time burdens, lower risk of harm, and provide greater accessibility. These benefits may extend beyond the research setting to the clinical setting. Non-invasive measurements are crucial to a myriad of study types and research questions with implications spanning the research-clinical spectrum. Broad examples of research types in which non-invasive physiological measurements are used or have important implications include: i) discovery (interpreting clinical signals to better understand systems physiology), ii) clinical and preclinical/subclinical (establishing efficacy and safety of techniques or interventions, iii) epidemiological: identifying the distribution of disease or track cohorts, and iv) implementation (medical system approaches for tracking patient health). We, via this Research Topic, were interested in all article types (e.g., original research, brief reports, etc.) including those focused on bioengineering, mathematical modelling, laboratory-studies, clinical studies, epidemiological studies, and implementation studies. We were also interested in articles with implications for diversity, equity, and inclusivity, including those addressing life-stage, sex, gender, race, ethnicity, and disabilities

Photoplethysmography technology use in smart devices for early diagnosis of arterial hypertension: a systematic review

Background: According to the World Health Organisation (WHO), 1 in 4 men and 1 in 5 women have arterial hypertension (AH). It is important to diagnose AH early and constantly monitor blood pressure (BP). We assess the diagnostic accuracy of AH detection using smart devices with photoplethysmography (PPG) and seek to provide guidance from current evidence to clinicians about the value and limitations of their potential use to early diagnose this chronic disease. Material and methods: This systematic review of Medline, Google Scholar, and PubMed databases was conducted according to the PRISMA guidelines. All publications examining any type of AH detection using PPG in smart devices were evaluated. Study quality was assessed using the QUADAS-2 risk of bias tool. Results: The search strategy identified a total of 705 publications, of which 9 studies were included in the systematic review. Of the 9 studies included, 2 used Samsung Galaxy smartphones, and 7 used wearable watch-like devices. A sphygmomanometer was used as a reference standard in all studies. Conclusion: The current evidence base consists of small, biased, and low-quality studies which are insufficient to advise clinicians on the true value of PPG devices for AH detection. Further research is required with reference standards, standardized validation, and transparent algorithms for PPG technology to be used as a valid tool for early AH diagnosis

Multimodal Photoplethysmography-Based Approaches for Improved Detection of Hypertension

Elevated blood pressure (BP) is a major cause of death, yet hypertension commonly goes undetected. Owing to its nature, it is typically asymptomatic until later in its progression when the vessel or organ structure has already been compromised. Therefore, noninvasive and continuous BP measurement methods are needed to ensure appropriate diagnosis and early management before hypertension leads to irreversible complications. Photoplethysmography (PPG) is a noninvasive technology with waveform morphologies similar to that of arterial BP waveforms, therefore attracting interest regarding its usability in BP estimation. In recent years, wearable devices incorporating PPG sensors have been proposed to improve the early diagnosis and management of hypertension. Additionally, the need for improved accuracy and convenience has led to the development of devices that incorporate multiple different biosignals with PPG. Through the addition of modalities such as an electrocardiogram, a final measure of the pulse wave velocity is derived, which has been proved to be inversely correlated to BP and to yield accurate estimations. This paper reviews and summarizes recent studies within the period 2010-2019 that combined PPG with other biosignals and offers perspectives on the strengths and weaknesses of current developments to guide future advancements in BP measurement. Our literature review reveals promising measurement accuracies and we comment on the effective combinations of modalities and success of this technology

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

A pervasive system for real-time blood pressure monitoring

Tese de Mestrado Integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201

A noninvasive and cuffless method for the measurements of blood pressure.

Chan Ka Wing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2002.Includes bibliographical references.Abstracts in English and Chinese.Chapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Objectives --- p.1Chapter 1.2 --- Definitions --- p.2Chapter 1.2.1 --- Definition of blood pressure --- p.2Chapter 1.2.2 --- Definition of hypertension --- p.3Chapter 1.3 --- Problems related to hypertension --- p.4Chapter 1.4 --- The importance of measuring blood pressure --- p.4Chapter 1.4.1 --- Self-measurement of blood pressure --- p.5Chapter 1.4.2 --- Ambulatory blood pressure measurement --- p.5Chapter 1.5 --- Review of blood pressure measurement techniques --- p.7Chapter 1.5.1 --- The invasive method --- p.7Chapter 1.5.2 --- Noninvasive methods --- p.8Chapter 1.6 --- Review of currently available blood pressure meters --- p.15Chapter 1.7 --- Prevalence of hypertension --- p.19Chapter 1.7.1 --- Hong Kong --- p.19Chapter 1.7.2 --- Worldwide --- p.20Chapter 1.8 --- The market for blood pressure meters --- p.21Chapter 1.9 --- Organization of the thesis --- p.22References --- p.24Chapter Chapter 2 --- Measurement of the ECG-PPG interval --- p.30Chapter 2.1 --- Introduction --- p.30Chapter 2.1.1 --- Pulse transit time (PTT) --- p.30Chapter 2.1.2 --- Electrocardiogram (ECG) --- p.36Chapter 2.1.2.1 --- Measurement of the ECG signal --- p.37Chapter 2.1.3 --- Photoplethysmography (PPG) --- p.38Chapter 2.1.3.1 --- Measurement of the PPG signal --- p.41Chapter 2.1.4 --- Measurement of blood pressure by ECG-PPG interval --- p.43Chapter 2.2 --- Source of errors for measurement of the ECG-PPG interval --- p.44Chapter 2.2.1 --- Effects of variability of ECG-PPG intervals --- p.44Chapter 2.2.2 --- Effects of bending the arm --- p.49Chapter 2.2.3 --- Effects of an external force --- p.54Chapter 2.3 --- Conclusion --- p.60References --- p.62Chapter Chapter 3 --- Cuffless and Noninvasive Measurement of Blood Pressure --- p.68Chapter 3.1 --- Introduction --- p.68Chapter 3.2 --- Effects of subject-dependent calibration --- p.74Chapter 3.3 --- Effects of different time intervals --- p.81Chapter 3.4 --- The impact of using different Q-P intervals --- p.96Chapter 3.5 --- Real-time measurement of blood pressure --- p.104Chapter 3.6 --- Conclusion --- p.108References --- p.110Chapter Chapter 4 --- Motion Artifact Reduction from PPG Recordings in Ambulatory Blood Pressure Measurement --- p.114Chapter 4.1 --- Introduction --- p.114Chapter 4.2 --- Previous works --- p.115Chapter 4.3 --- Theory --- p.116Chapter 4.3.1 --- The adaptive filter --- p.117Chapter 4.3.2 --- Variation of step-size parameters --- p.119Chapter 4.3.3 --- Effects of filter length --- p.120Chapter 4.4 --- Experiment --- p.121Chapter 4.5 --- Results --- p.123Chapter 4.6 --- Discussion --- p.131Chapter 4.7 --- Conclusion --- p.133References --- p.135Chapter Chapter 5 --- Measurement of Blood Pressure using the PPG signal --- p.138Chapter 5.1 --- Introduction --- p.138Chapter 5.2 --- Theory --- p.138Chapter 5.3 --- Experiment --- p.142Chapter 5.3.1 --- Multiple linear regression (MLR) --- p.142Chapter 5.3.2 --- Artificial neural networks (ANNs) --- p.146Chapter 5.3.3 --- Results --- p.149Chapter 5.3.4 --- Discussion --- p.152Chapter 5.4 --- The implementation of the Q-P interval --- p.153Chapter 5.4.1 --- Results --- p.154Chapter 5.4.2 --- Discussion --- p.156Chapter 5.5 --- Conclusion --- p.157References --- p.158Chapter Chapter 6 --- Conclusion and Future Studies --- p.160Chapter 6.1 --- Major contributions --- p.160Chapter 6.2 --- Future studies --- p.162References --- p.165Appendix I --- p.16

Blood Pressure Beyond the Clinic: Rethinking a Health Metric for Everyone

ABSTRACT Blood pressure (BP) is typically captured at irregular intervals, mostly in clinic environments. This approach treats BP as a static snapshot for health classification and largely ignores its value as a continuously fluctuating measure. Recognizing that consumers are increasingly capturing health metrics through wearable devices, we explored BP measurement in relation to everyday living through a two-week field study with 34 adults. Based on questionnaires, measurement logs, and interviews, we examined participants' perceptions and attitudes towards BP variability and their associations of BP with aspects of their lives. We found that participants modified their use of BP devices in response to BP variability, made associations with stress, food, and daily routines, and revealed challenges with the design of current BP devices for personal use. We present design recommendations for BP use in everyday contexts and describe strategies for re-framing BP capture and reporting