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

A review of machine learning techniques in photoplethysmography for the non-invasive cuff-less measurement of blood pressure

(2020) C. El-Hajj et al.   Biomedical Signal Processing and Control

A multistage deep neural network model for blood pressure estimation using photoplethysmogram signals

(2020) Jamal Esmaelpoor et al.   COMPUTERS IN BIOLOGY AND MEDICINE

End-To-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism

(2020) Heesang Eom et al.   SENSORS

Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques

(2020) Moajjem Hossain Chowdhury et al.   SENSORS

Continuous blood pressure measurement from one-channel electrocardiogram signal using deep-learning techniques

(2020) Fen Miao et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

PP-Net: A Deep Learning Framework for PPG-Based Blood Pressure and Heart Rate Estimation

(2020) Madhuri Panwar et al.   IEEE SENSORS JOURNAL

Predicting Systolic Blood Pressure in Real-Time Using Streaming Data and Deep Learning

(2020) Hager Saleh et al.   MOBILE NETWORKS & APPLICATIONS

Real-Time Cuffless Continuous Blood Pressure Estimation Using Deep Learning Model

(2020) Yung-Hui Li et al.   SENSORS

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

(2020) Wan-Hua Lin et al.   Biomedical Signal Processing and Control

Beat-to-Beat Continuous Blood Pressure Estimation Using Bidirectional Long Short-Term Memory Network

(2020) Dongseok Lee et al.   SENSORS

A Non-Invasive Continuous Blood Pressure Estimation Approach Based on Machine Learning

(2019) Shuo Chen et al.   SENSORS

Blood Pressure Estimation from Photoplethysmogram Using a Spectro-Temporal Deep Neural Network

(2019) Gašper Slapničar et al.   SENSORS

Analysis of Pulse Arrival Time as an Indicator of Blood Pressure in a Large Surgical Biosignal Database: Recommendations for Developing Ubiquitous Blood Pressure Monitoring Methods

(2019) Joonnyong Lee et al.   Journal of Clinical Medicine

Multi-level information fusion for learning a blood pressure predictive model using sensor data

(2019) Monika Simjanoska et al.   Information Fusion

Deep learning for healthcare applications based on physiological signals: A review

(2018) Oliver Faust et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Optimal approximation of piecewise smooth functions using deep ReLU neural networks

(2018) Philipp Petersen et al.   NEURAL NETWORKS

Continuous Cuff-Less Blood Pressure Estimation Based on Combined Information Using Deep Learning Approach

(2018) Dan Wu et al.   Journal of Medical Imaging and Health Informatics

Multi-Scaled Fusion of Deep Convolutional Neural Networks for Screening Atrial Fibrillation from Single Lead Short ECG Recordings

(2018) Xiaomao Fan et al.   IEEE Journal of Biomedical and Health Informatics

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network

(2018) Awni Y. Hannun et al.   NATURE MEDICINE

Cuff-less continuous measurement of blood pressure using wrist and fingertip photo-plethysmograms: Evaluation and feature analysis

(2018) Ahmadreza Attarpour et al.   Biomedical Signal Processing and Control

Cuffless Blood Pressure Estimation Algorithms for Continuous Health-Care Monitoring

(2017) Mohammad Kachuee et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Oscillometric Blood Pressure Estimation Based on Deep Learning

(2017) Soojeong Lee et al.   IEEE Transactions on Industrial Informatics

Deep Belief Networks Ensemble for Blood Pressure Estimation

(2017) Soojeong Lee et al.   IEEE Access

A review of methods for non-invasive and continuous blood pressure monitoring: Pulse transit time method is promising?

(2014) L. Peter et al.   IRBM

Noninvasive cuffless blood pressure estimation using pulse transit time and Hilbert–Huang transform

(2012) Younhee Choi et al.   COMPUTERS & ELECTRICAL ENGINEERING