Emerging sensing and modeling technologies for wearable and cuffless blood pressure monitoring
Cardiovascular diseases (CVDs) are a leading cause of death worldwide. For early
diagnosis, intervention and management of CVDs, it is highly desirable to frequently monitor …
diagnosis, intervention and management of CVDs, it is highly desirable to frequently monitor …
Advancement in the cuffless and noninvasive measurement of blood pressure: A review of the literature and open challenges
MMR Khan Mamun, A Sherif - Bioengineering, 2022 - mdpi.com
Hypertension is a chronic condition that is one of the prominent reasons behind
cardiovascular disease, brain stroke, and organ failure. Left unnoticed and untreated, the …
cardiovascular disease, brain stroke, and organ failure. Left unnoticed and untreated, the …
A reinforcement learning based artificial bee colony algorithm with application in robot path planning
Y Cui, W Hu, A Rahmani - Expert Systems with Applications, 2022 - Elsevier
Artificial bee colony (ABC) algorithm is a popular optimization algorithm with excellent
exploration ability and various applications. Nevertheless, its effectiveness is limited by the …
exploration ability and various applications. Nevertheless, its effectiveness is limited by the …
A benchmark for machine-learning based non-invasive blood pressure estimation using photoplethysmogram
S González, WT Hsieh, TPC Chen - Scientific Data, 2023 - nature.com
Blood Pressure (BP) is an important cardiovascular health indicator. BP is usually monitored
non-invasively with a cuff-based device, which can be bulky and inconvenient. Thus …
non-invasively with a cuff-based device, which can be bulky and inconvenient. Thus …
Physics-informed neural networks for modeling physiological time series for cuffless blood pressure estimation
The bold vision of AI-driven pervasive physiological monitoring, through the proliferation of
off-the-shelf wearables that began a decade ago, has created immense opportunities to …
off-the-shelf wearables that began a decade ago, has created immense opportunities to …
An efficient hybrid LSTM-ANN joint classification-regression model for PPG based blood pressure monitoring
This paper investigates the importance of classification in optimizing the estimation accuracy
of blood pressure (BP) using photoplethysmography (PPG) signal features, with the aim of …
of blood pressure (BP) using photoplethysmography (PPG) signal features, with the aim of …
IMSF-Net: An improved multi-scale information fusion network for PPG-based blood pressure estimation
D Wang, Y Ye, B Zhang, J Sun, C Zhang - Biomedical Signal Processing …, 2024 - Elsevier
Recently, deep learning (DL) architectures have been widely used for PPG-based blood
pressure (BP) monitoring due to their powerful feature extraction ability. However, the DL …
pressure (BP) monitoring due to their powerful feature extraction ability. However, the DL …
[HTML][HTML] Diagnosis of Community-Acquired pneumonia in children using photoplethysmography and Machine learning-based classifier
This paper presents a novel approach for diagnosing Community-Acquired Pneumonia
(CAP) in children using single-channel photoplethysmography (PPG) using machine …
(CAP) in children using single-channel photoplethysmography (PPG) using machine …
Regression or Classification? Reflection on BP prediction from PPG data using Deep Neural Networks in the scope of practical applications
F Schrumpf, PR Serdack… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
Photoplethysmographic (PPG) signals offer diagnostic potential beyond heart rate analysis
or blood oxygen level monitoring. In the recent past, research focused extensively on non …
or blood oxygen level monitoring. In the recent past, research focused extensively on non …
Machine learning and deep learning for blood pressure prediction: a methodological review from multiple perspectives
K Qin, W Huang, T Zhang, S Tang - Artificial Intelligence Review, 2023 - Springer
Blood pressure (BP) estimation is one of the most popular and long-standing topics in health-
care monitoring area. The utilization of machine learning (ML) and deep learning (DL) for BP …
care monitoring area. The utilization of machine learning (ML) and deep learning (DL) for BP …