☆ 4.7 Review

Emerging sensing and modeling technologies for wearable and cuffless blood pressure monitoring

NPJ DIGITAL MEDICINE (2023)

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Review Peripheral Vascular Disease

The Microsoft Research Aurora Project: Important Findings on Cuffless Blood Pressure Measurement

Ramakrishna Mukkamala et al.

Summary: Conventional blood pressure measurement devices only provide a limited view of continuous blood pressure profile. Wearable cuffless blood pressure devices utilizing pulse wave analysis and pulse arrival time have the potential to significantly improve the assessment and management of hypertension. The Aurora Project, conducted by Microsoft Research, evaluated the accuracy of various cuffless blood pressure devices and found negative results. This article discusses the emerging technologies, summarizes the Aurora Project, and highlights its implications, study methodology, and limitations.

HYPERTENSION (2023)

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Article Engineering, Biomedical

Photoplethysmography Fast Upstroke Time Intervals Can Be Useful Features for Cuff-Less Measurement of Blood Pressure Changes in Humans

Keerthana Natarajan et al.

Summary: This study aims to develop easy-to-understand models relating PPG waveform features to blood pressure changes and evaluate their value in blood pressure measurement accuracy. The study found that some PPG features combined with other indicators can improve the accuracy of cuff-less blood pressure trending.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2022)

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Article Health Care Sciences & Services

A Novel Clustering-Based Algorithm for Continuous and Noninvasive Cuff-Less Blood Pressure Estimation

Ali Farki et al.

Summary: This paper introduces a novel blood pressure estimation method with a clustering step to improve accuracy. By utilizing multiple signal features and machine learning algorithms to develop blood pressure estimation models, weighting the clustering results to enhance accuracy, significantly better results were achieved compared to methods without clustering.

JOURNAL OF HEALTHCARE ENGINEERING (2022)

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Article Computer Science, Information Systems

Personalized Blood Pressure Estimation Using Photoplethysmography: A Transfer Learning Approach

Jared Leitner et al.

Summary: This paper presents a personalized deep learning approach using the photoplethysmogram signal to estimate blood pressure. The approach employs a hybrid neural network architecture and transfer learning technique to address the problem of limited personal PPG and BP data. The results show that accurate personalized models can be trained with as little as 50 data samples per person.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2022)

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Article Computer Science, Information Systems

Neckband-Based Continuous Blood Pressure Monitoring Device With Offset-Tolerant ROIC

Kwangmuk Lee et al.

Summary: This study introduces a wearable neckband device for continuous cuffless blood pressure monitoring using electrocardiogram and impedance plethysmogram. By optimizing the composition and position of the sensing electrodes, as well as selecting the core parameter of impedance plethysmogram, the accuracy of blood pressure estimation is improved. A customized integrated circuit is developed to achieve noise tolerance and wireless transmission for real-time blood pressure monitoring.

IEEE ACCESS (2022)

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Review Engineering, Biomedical

Noninvasive Continuous Blood Pressure Estimation From Pulse Transit Time: A Review of the Calibration Models

Daniel Barvik et al.

Summary: Noninvasive continuous blood pressure estimation is a promising method for long-term and continuous blood pressure monitoring in ecological situations. The current estimation algorithm is based on pulse transit time measurement, but requires calibration to minimize error. Recent research focuses on simplified arterial properties, but there is a need for more complete calibration models.

IEEE REVIEWS IN BIOMEDICAL ENGINEERING (2022)

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Review Engineering, Biomedical

Cuffless Blood Pressure Measurement

Ramakrishna Mukkamala et al.

Summary: Cuffless blood pressure measurement is a popular research field driven by clinical need and technological opportunity. This review provides an overview of the development and application of cuffless BP measurement methods, including the principles of conventional BP measurement, the problems that cuffless methods can address, the technological advances that are driving the field, and the current evidence of various cuffless methods under investigation.

ANNUAL REVIEW OF BIOMEDICAL ENGINEERING (2022)

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Article Engineering, Multidisciplinary

A non-invasive heart rate and blood pressure monitoring system using piezoelectric and photoplethysmographic sensors

Piyawat Samartkit et al.

Summary: This work investigates a non-invasive heart rate and blood pressure monitoring system using a lead zirconate titanate piezoelectric and photoplethysmographic sensor. A modified pulse transit time method is utilized to obtain heart rate, systolic blood pressure, and diastolic blood pressure measurements. An engineering application software is also developed for real-time signal monitoring and processing. The results on 15 volunteers demonstrate that the system produces comparable measurements to a reference digital sphygmomanometer, with accuracy compliant with the AAMI-BHS Grade A standards. Therefore, this PZT and PPG-based monitoring system has the potential to develop accurate, non-invasive, and low-cost heart rate and blood pressure devices.

MEASUREMENT (2022)

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Article Engineering, Electrical & Electronic

Wavelet scattering transform and long short-term memory network-based noninvasive blood pressure estimation from photoplethysmograph signals

N. Jean Effil et al.

Summary: Measuring blood pressure using wearable PPG devices, extracting features through signal processing, and predicting blood pressure through trained models shows promising levels of accuracy in the proposed system. Comparisons with benchmark algorithms and prior studies exhibit the superiority and comparability of the proposed approach.

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Article Computer Science, Artificial Intelligence

A Comparison of Deep Learning Techniques for Arterial Blood Pressure Prediction

Annunziata Paviglianiti et al.

Summary: Continuous monitoring of arterial blood pressure (ABP) through non-intrusive, cuffless methods based on deep learning techniques using neural networks, particularly including photoplethysmogram (PPG) and electrocardiogram (ECG) signals, has shown improved performance. The combination of ResNet and LSTM layers yielded the best results, meeting the American National Standards for medical instrumentation. The study utilized data from the MIMIC database and was validated on a custom dataset at Neuronica Lab, Politecnico di Torino.

COGNITIVE COMPUTATION (2022)

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Article Computer Science, Information Systems

Improving Cuff-Less Continuous Blood Pressure Estimation with Linear Regression Analysis

Valeria Figini et al.

Summary: This work investigates the use of regression techniques to estimate continuous blood pressure through pulse transit time and heart rate without the need for a cuff. The continuous monitoring of hypertension can greatly improve the prevention of cardiovascular diseases and provide valuable tools for patient care. The study introduces innovative methods for pre-processing and feature research, paving the way for continuous non-invasive blood pressure monitoring.

ELECTRONICS (2022)

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Review Computer Science, Artificial Intelligence

A survey: From shallow to deep machine learning approaches for blood pressure estimation using biosensors

Sumbal Maqsood et al.

Summary: Machine learning systems have been widely used in the healthcare industry over the past two decades. Photoplethysmography (PPG) and Electrocardiography (ECG) are promising techniques for tracking cardiovascular health. This paper analyzes and summarizes the state-of-the-art machine learning-based blood pressure estimation methods using continuous, cuffless, and non-invasive PPG signals, and provides a comparison between PPG and ECG.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

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Article Multidisciplinary Sciences

Bioadhesive ultrasound for long-term continuous imaging of diverse organs

Chonghe Wang et al.

Summary: The BAUS device is a bioadhesive tool that provides continuous imaging of diverse internal organs for up to 48 hours. It has the potential for diagnosis and monitoring of various diseases.

SCIENCE (2022)

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Article Computer Science, Information Systems

A Comparison of Wearable Tonometry, Photoplethysmography, and Electrocardiography for Cuffless Measurement of Blood Pressure in an Ambulatory Setting

Rebecca Mieloszyk et al.

Summary: This study demonstrated the results of blood pressure estimation in both lab and daily life using different feature groups, with superior performance shown by the radial tonometry-derived feature group. The study emphasizes the need for diverse populations and challenging evaluation settings in blood pressure estimation research.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2022)

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Article Engineering, Electrical & Electronic

Dynamic Large Artery Stiffness Index for Cuffless Blood Pressure Estimation

Shresth Gupta et al.

Summary: Accurate blood pressure measurement is crucial for diagnosis and treatment of cardiovascular disease and hypertension. This letter proposes an enhanced index, the dynamic large artery stiffness index, for estimating blood pressure using the contour of the photoplethysmogram. The proposed index shows a good correlation with mean arterial pressure and pulse pressure and achieves excellent performance compared to the global standard benchmark for blood pressure estimation.

IEEE SENSORS LETTERS (2022)

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Article Engineering, Biomedical

Towards accurate estimation of cuffless and continuous blood pressure using multi-order derivative and multivariate photoplethysmogram features

Wan-Hua Lin et al.

Summary: This study investigated the efficiency and accuracy of using only PPG features for CC-BP estimation, demonstrating that using 65 PPG features resulted in significantly higher accuracy compared to using hybrid PAT and PPG indicators.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)

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Article Engineering, Electrical & Electronic

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

Sen Yang et al.

Summary: Conventional blood pressure measurement methods have drawbacks, prompting the development of a hybrid deep learning model that utilizes both raw signals and physical characteristics for accurate BP measurement, achieving optimal results.

OPTICAL AND QUANTUM ELECTRONICS (2021)

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Simultaneous Electrical Bio-Impedance Plethysmography at Different Body Parts: Continuous and Non-Invasive Monitoring of Pulse Wave Velocity

Kwonjoon Lee et al.

Summary: This study implemented a simultaneous and time-synchronized electrical bio-impedance plethysmography (BPG) sensor system for long-term, continuous, and non-invasive measurement of arterial pulse wave velocity (PWV). By optimizing layout and technical methods, long-term, continuous, and non-invasive PWV measurement was successfully achieved.

IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS (2021)

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Article Chemistry, Analytical

Non-Contact Measurements of Electrocardiogram and Cough-Associated Electromyogram from the Neck Using In-Pillow Common Cloth Electrodes: A Proof-of-Concept Study

Akira Takano et al.

Summary: A non-contact system for monitoring heart rate and cough using cloth electrodes under a pillowcase was proposed and evaluated in a laboratory experiment. The system showed promising results for unobtrusive detection over a prolonged period of time, although further improvements are needed in practical use.

SENSORS (2021)

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Review Chemistry, Physical

Recent Progress in Flexible Microstructural Pressure Sensors toward Human-Machine Interaction and Healthcare Applications

Faliang He et al.

Summary: This article introduces the research status and application prospects of flexible microstructural pressure sensors in the context of rapid development of artificial intelligence, focusing on their microstructure design, preparation strategies, and material selection. The potential applications in the fields of medical health and human-machine interaction are emphasized.

SMALL METHODS (2021)

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Article Engineering, Biomedical

Deep learning models for cuffless blood pressure monitoring from PPG signals using attention mechanism

C. El-Hajj et al.

Summary: A study proposed recurrent neural network models utilizing Photoplethysmogram signals with bidirectional connections and attention mechanism to accurately estimate systolic and diastolic blood pressure. Experimental results showed that these models could capture the non-linear relationship and outperformed traditional machine learning methods on datasets, meeting global standards.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)

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Article Engineering, Electrical & Electronic

Noninvasive and Nonocclusive Blood Pressure Monitoring via a Flexible Piezo-Composite Ultrasonic Sensor

Chang Peng et al.

Summary: This study introduced a flexible piezo-composite ultrasonic sensor for continuous blood pressure monitoring, which demonstrated adequate sensitivity and bandwidth for daily use. Experimental results showed that the flexible sensor successfully conducted blood pressure measurement and continuously monitored blood pressure waveforms during cardiac cycles.

IEEE SENSORS JOURNAL (2021)

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Article Biophysics

Cuffless blood pressure estimation methods: physiological model parameters versus machine-learned features

Jamal Esmaelpoor et al.

Summary: This paper investigates critical aspects of blood pressure monitoring using PPG and ECG, highlighting the importance of ECG waveform for accuracy improvement and the superiority of machine-learned features in performance. The study also reveals that the combination of feature sets does not provide additional information.

PHYSIOLOGICAL MEASUREMENT (2021)

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Article Chemistry, Analytical

An Estimation Method of Continuous Non-Invasive Arterial Blood Pressure Waveform Using Photoplethysmography: A U-Net Architecture-Based Approach

Tasbiraha Athaya et al.

Summary: The study proposes a method using deep learning architecture for blood pressure monitoring, estimating non-invasively with fingertip PPG signals. The results demonstrate the effectiveness of directly estimating ABP waveform and achieving blood pressure indicators within acceptable error ranges according to standards.

SENSORS (2021)

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Article Chemistry, Physical

A flexible ultra-sensitive triboelectric tactile sensor of wrinkled PDMS/MXene composite films for E-skin

Ya-Wei Cai et al.

Summary: The study constructed a flexible TENG as a self-powered tactile sensor using a simple method, achieving high sensitivity and showing good application prospects in monitoring complex physiological signals and simulating human touch sensation.

NANO ENERGY (2021)

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Review Materials Science, Multidisciplinary

Recent Progress on Flexible Capacitive Pressure Sensors: From Design and Materials to Applications

Rishabh B. Mishra et al.

Summary: The revolutionary design and fabrication methods of flexible capacitive pressure sensors have greatly improved the field of flexible and wearable electronics. Mathematical modeling, finite element simulations, and unique fabrication strategies are utilized to create diverse shapes and functions for these sensors. By detecting changes in capacitance due to pressure-induced deformation, these sensors have found applications in various industries and have promising future prospects.

ADVANCED MATERIALS TECHNOLOGIES (2021)

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Article Engineering, Biomedical

An epidermal patch for the simultaneous monitoring of haemodynamic and metabolic biomarkers

Juliane R. Sempionatto et al.

Summary: This study presents a smart skin-worn device that can monitor blood pressure, heart rate, and various biomarkers, allowing for the capture of physiological effects of food intake and exercise.

NATURE BIOMEDICAL ENGINEERING (2021)

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A clinical set-up for noninvasive blood pressure monitoring using two photoplethysmograms and based on convolutional neural networks

Jamal Esmaelpoor et al.

Summary: This study proposes a clinical set-up using photoplethysmogram signals for continuous blood pressure estimation, achieving better performance with toe PPG compared to earlobe PPG. The algorithm accuracy improves when both signals are applied together. The method provides high estimation consistency and may serve as a possible alternative for inconvenient invasive blood pressure monitoring in clinical environments.

BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK (2021)

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Article Chemistry, Analytical

Continuous Blood Pressure Estimation Using Exclusively Photopletysmography by LSTM-Based Signal-to-Signal Translation

Latifa Nabila Harfiya et al.

Summary: This study introduces a novel deep learning model for signal-to-signal translation from PPG to ABP, achieving continuous blood pressure estimation with high accuracy. The model meets the standards set by AAMI and BHS for SBP and DBP prediction, showcasing the potential for accurate continuous BP estimation without complex feature engineering.

SENSORS (2021)

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Article Chemistry, Analytical

Blood Pressure Morphology Assessment from Photoplethysmogram and Demographic Information Using Deep Learning with Attention Mechanism

Nicolas Aguirre et al.

Summary: Arterial blood pressure (ABP) is an important vital sign for diagnosing cardiovascular diseases, and routine control is recommended. This paper proposes a cuff-free method to estimate the morphology of the average ABP pulse based on a deep learning model, which shows better results when subject demographic information is integrated. The methodology has the potential to be useful in times when wireless devices are becoming more popular.

SENSORS (2021)

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Article Engineering, Electrical & Electronic

Research progress of flexible capacitive pressure sensor for sensitivity enhancement approaches

Ruiqing Li et al.

Summary: This paper reviews a large number of research outputs on sensitivity improvement of flexible capacitive pressure sensors and discusses methods and trends for enhancing the sensitivity of pressure sensors.

SENSORS AND ACTUATORS A-PHYSICAL (2021)

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Review Engineering, Biomedical

Flexible Wearable Sensors for Cardiovascular Health Monitoring

Shuwen Chen et al.

Summary: This paper outlines and discusses advanced flexible wearable sensors for monitoring cardiovascular vital signals, highlighting functional materials, configurations, mechanisms, and recent advances, as well as discussing challenges, possible strategies, and future directions. With rapid development, these flexible wearable sensors have the potential to be applied for both medical diagnosis and daily healthcare use in addressing cardiovascular diseases.

ADVANCED HEALTHCARE MATERIALS (2021)

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Article Computer Science, Information Systems

Estimation and Validation of Arterial Blood Pressure Using Photoplethysmogram Morphology Features in Conjunction With Pulse Arrival Time in Large Open Databases

Seungman Yang et al.

Summary: This study presents and validates a blood pressure estimation method through analysis of a large amount of bio-signal data from surgical patients, indicating that this method can achieve ubiquitous non-invasive continuous blood pressure monitoring.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2021)

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Article Multidisciplinary Sciences

A Continuous Cuffless Blood Pressure Estimation Using Tree-Based Pipeline Optimization Tool

Suliman Mohamed Fati et al.

Summary: This study aims to estimate blood pressure using machine learning from cuff-based monitoring by automating the machine learning pipeline to select the best regression models. The proposed approach was trained and tested using the PhysioNet global dataset, showing superior results compared to related works.

SYMMETRY-BASEL (2021)

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Article Chemistry, Multidisciplinary

Novel Data Augmentation Employing Multivariate Gaussian Distribution for Neural Network-Based Blood Pressure Estimation

Kwangsub Song et al.

Summary: This paper presents a novel data augmentation technique utilizing multivariate Gaussian distribution for neural network-based blood pressure estimation. By incorporating the relationship between features in a multi-dimensional feature vector, the proposed algorithm outperforms conventional algorithms in describing correlated real-valued random variables and achieving lower errors in BP estimation.

APPLIED SCIENCES-BASEL (2021)

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Article Chemistry, Analytical

A Novel Wearable Flexible Dry Electrode Based on Cowhide for ECG Measurement

Yiping Huang et al.

Summary: Wearable flexible silver electrodes based on cowhide were prepared and tested for their waveform transmission and impedance. The results showed that these electrodes were comparable to standard gel electrodes when the skin is moist enough, and had higher signal-to-noise ratios than the standard electrodes in the standing posture.

BIOSENSORS-BASEL (2021)

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Article Engineering, Biomedical

Cuffless blood pressure estimation based on composite neural network and graphics information

Ye Qiu et al.

Summary: This study proposed a hybrid neural network architecture for blood pressure estimation, which can effectively predict dynamic blood pressure by using the combined input of PPG and ECG signals. The model performed well in evaluating the performance of two datasets, demonstrating stable and reliable results.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)

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Article Engineering, Biomedical

Deep generative model with domain adversarial training for predicting arterial blood pressure waveform from photoplethysmogram signal

Keke Qin et al.

Summary: A novel continuous, non-invasive and cuff-less approach is presented for generating ABP waveform using only raw photoplethysmogram (PPG) signal. Both domain adversarial training and calibration improve the performance in varying degrees.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)

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Article Engineering, Biomedical

A multi-type features fusion neural network for blood pressure prediction based on photoplethysmography

Meng Rong et al.

Summary: The proposed multi-type features fusion (MTFF) neural network model based on photoplethysmography (PPG) accurately predicts blood pressure by automatically extracting PPG signal features through deep learning, avoiding tedious calculations, and training and fusing multiple features to improve prediction accuracy.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)

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Article Engineering, Biomedical

Cuffless blood pressure estimation from PPG signals and its derivatives using deep learning models

C. El-Hajj et al.

Summary: The research explores the use of deep learning models for continuous cuffless blood pressure monitoring, which performs well and meets international standards.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)

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Article Computer Science, Interdisciplinary Applications

A hybrid neural network for continuous and non-invasive estimation of blood pressure from raw electrocardiogram and photoplethysmogram waveforms

Stephanie Baker et al.

Summary: The study proposes a hybrid neural network for accurate blood pressure estimation using only non-invasive ECG and PPG waveforms. The network combines temporal convolutional layers with LSTM layers and achieves low mean absolute errors for SBP, DBP, and MAP. It outperforms current state-of-the-art schemes and meets standards set by BHS and AAMI.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2021)

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Article Biology

Prediction of arterial blood pressure waveforms from photoplethysmogram signals via fully convolutional neural networks

Juan Cheng et al.

Summary: This paper introduces a deep learning model called ABP-Net, which transforms PPG signals into ABP waveforms containing vital physiological information related to cardiovascular systems. The proposed model shows superior performance in subject-dependent and subject-independent experiments on the MIMIC II database.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

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Review Peripheral Vascular Disease

Evaluation of the Accuracy of Cuffless Blood Pressure Measurement Devices: Challenges and Proposals

Ramakrishna Mukkamala et al.

Summary: Novel cuffless wearable devices and smartphone applications claiming to measure blood pressure have gained popularity among healthcare professionals and patients, despite serious concerns about their accuracy and validation challenges. Existing standards for automated BP measurement devices are not suitable for cuffless devices, leading to potentially misleading conclusions in published data. Further research is needed to evaluate the capabilities and limitations of these emerging technologies.

HYPERTENSION (2021)

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Roll-to-roll graphene films for non-disposable electrocardiogram electrodes

Xiaoshi Li et al.

Summary: Graphene exhibits excellent electrical properties, flexibility, and transparency, making it an ideal material for monitoring ECG signals. A roll-to-roll method was demonstrated to transfer graphene onto an EVA/PET substrate, producing electrodes with lower electrode-skin impedance and good washability compared to commercial electrodes. This work shows great potential for long-term and real-time healthcare monitoring systems.

JOURNAL OF PHYSICS D-APPLIED PHYSICS (2021)

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Article Chemistry, Analytical

Assessment of Non-Invasive Blood Pressure Prediction from PPG and rPPG Signals Using Deep Learning

Fabian Schrumpf et al.

Summary: Using photoplethysmography signals for non-invasive blood pressure measurement is interesting for various reasons, and machine learning techniques are commonly used with performances evaluated based on mean average error. Careful dataset assignment is crucial, and personalization techniques can significantly reduce prediction errors.

SENSORS (2021)

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Article Multidisciplinary Sciences

Imputation of the continuous arterial line blood pressure waveform from non-invasive measurements using deep learning

Brian L. Hill et al.

Summary: This study developed a novel approach to impute the continuous ABP waveform non-invasively using ECG and PPG waveforms, demonstrating highly accurate prediction. This method has the potential to continuously and non-invasively measure blood pressure for all patients in the acute care setting without the need for additional instrumentation.

SCIENTIFIC REPORTS (2021)

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Article Materials Science, Multidisciplinary

Facile Fabrication of Robust and Reusable PDMS Supported Graphene Dry Electrodes for Wearable Electrocardiogram Monitoring

Jie Yang et al.

Summary: Graphene-based epidermal dry electrodes offer a promising solution for timely monitoring of cardiovascular diseases through ECG. However, challenges such as poor stability and integration have hindered their widespread use in healthcare. This study demonstrates the fabrication of robust, reusable, and patterned graphene-based dry electrodes using laser writing technology, supported by PDMS layers, showing excellent stability and reusability for ECG recording. Through careful design and analysis, the staff-shape graphene electrode exhibits sensitivity and reliability comparable to wet Ag/AgCl electrodes, making it suitable for long-term ECG monitoring and wearable 12-lead ECG recording.

ADVANCED MATERIALS TECHNOLOGIES (2021)

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Article Engineering, Biomedical

Continuous monitoring of deep-tissue haemodynamics with stretchable ultrasonic phased arrays

Chonghe Wang et al.

Summary: The development and testing of a prototype skin-conformal ultrasonic phased array for monitoring haemodynamic signals from tissues up to 14 cm beneath the skin are reported. This device allows for active focusing and steering of ultrasound beams to target regions of interest, opening up opportunities for wearable diagnostics. In healthy volunteers, the phased array has shown promising results in monitoring Doppler spectra from cardiac tissues and estimating central and cerebral blood flows in real time.

NATURE BIOMEDICAL ENGINEERING (2021)

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Article Computer Science, Information Systems

A Benchmark Study of Machine Learning for Analysis of Signal Feature Extraction Techniques for Blood Pressure Estimation Using Photoplethysmography (PPG)

Sumbal Maqsood et al.

Summary: This paper conducted a comprehensive analysis of feature extraction techniques for blood pressure estimation using PPG signals. It found that time-domain features were the most reliable for blood pressure estimation, and deep learning models outperformed traditional machine learning methods. The GRU model and Bi-LSTM achieved the best performance for blood pressure estimation using time-domain features.

IEEE ACCESS (2021)

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Article Engineering, Electrical & Electronic

Fabrication of GNR Electrode for ECG Signal Acquisition

Anitha S. Prasad et al.

Summary: The graphene nanoribbon (GNR) electrode was fabricated using composite polyvinyl alcohol-GNR (PVA/GNR) for real-time electrocardiogram (ECG) signal acquisition. The results showed that the GNR electrode with 1% GNR in PVA matrix was ideal for the ECG signal acquisition system, demonstrating high sensitivity and good signal-to-noise ratio.

IEEE SENSORS LETTERS (2021)

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Article Computer Science, Information Systems

Beats-to-Beats Estimation of Blood Pressure During Supine Cycling Exercise Using a Probabilistic Nonparametric Method

Qing Liu et al.

Summary: This study proposed and evaluated novel cuffless frameworks for continuously estimating SBP and DBP averages during dynamic exercise in a general elderly population using multiple biosensors and machine learning algorithms. The Gaussian process regression model showed the lowest mean absolute error among the five models tested, indicating promising results for estimating 10-beat averages of SBP and DBP without a cuff.

IEEE ACCESS (2021)

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Review Chemistry, Multidisciplinary

Wearable sensors and devices for real-time cardiovascular disease monitoring

Jian Lin et al.

Summary: This article reviews the latest developments in the surveillance of various physiological signals of flexible sensors for cardiovascular diseases, covering monitoring signals and discussing different mechanisms. The focus is on monitoring pulse signals and flexible sensor technologies for electrocardiogram (ECG), phonocardiogram (PCG), seismocardiogram/ballistocardiogram (SCG/BCG), and apexcardiogram (ACG) signals. Proposed future research directions based on the current research landscape.

CELL REPORTS PHYSICAL SCIENCE (2021)

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Article Engineering, Electrical & Electronic

Single-Channel Bioimpedance Measurement for Wearable Continuous Blood Pressure Monitoring

Ting-Wei Wang et al.

Summary: This study developed a single-channel wrist-worn impedance plethysmography (IPG) system for wearable continuous blood pressure measurement, with a two-step calibration for an IPG-based blood pressure mathematical model. The system achieved high-resolution IPG measurement by optimizing injection current frequency and electrode arrangement to capture the impedance difference between systolic and diastolic blood pressure, showing promising accuracy results for blood pressure estimation.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)

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Review Chemistry, Physical

Advances in self-powered triboelectric pressure sensors

Hao Lei et al.

Summary: Self-powered pressure sensors based on triboelectric nanogenerator have gained attention for their potential applications in the Internet of Things. These sensors optimize power consumption and performance. Efforts are ongoing to improve sensing performance to meet practical demands.

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Key Feature Selection and Model Analysis for Blood Pressure Estimation From Electrocardiogram, Ballistocardiogram and Photoplethysmogram

Yandong Zhang et al.

Summary: This study introduces a new blood pressure estimation model that combines features from ECG, BCG, and PPG. The combination model shows promising results in young healthy subjects, outperforming other existing estimation models.

IEEE ACCESS (2021)

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Facile Fabrication of a Stretchable and Flexible Nanofiber Carbon Film-Sensing Electrode by Electrospinning and Its Application in Smart Clothing for ECG and EMG Monitoring

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Summary: This study successfully developed a nanofiber carbon electrode with high electrical conductivity, mechanical durability, and a hydrophobic surface, suitable for long-term biological signal recording and integration into wearable systems for healthcare monitoring.

ACS APPLIED ELECTRONIC MATERIALS (2021)

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Article Engineering, Electrical & Electronic

Photoplethysmography-Based Blood Pressure Estimation Combining Filter-Wrapper Collaborated Feature Selection With LASSO-LSTM Model

Dingliang Wang et al.

Summary: This study proposed a novel noninvasive blood pressure estimation method using single-channel PPG signals, demonstrating improved accuracy compared to previous methods. The approach effectively rejected weak or redundant features and learned complex nonlinear relationships.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)

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Article Engineering, Multidisciplinary

Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2020)

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European Society of Cardiology: Cardiovascular Disease Statistics 2019

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Blood pressure estimation with complexity features from electrocardiogram and photoplethysmogram signals

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Article Biophysics

Investigating the physiological mechanisms of the photoplethysmogram features for blood pressure estimation

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PHYSIOLOGICAL MEASUREMENT (2020)

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Article Multidisciplinary Sciences

Graded intrafillable architecture-based iontronic pressure sensor with ultra-broad-range high sensitivity

Ningning Bai et al.

NATURE COMMUNICATIONS (2020)

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