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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 …
Integrating machine learning and biosensors in microfluidic devices: a review.
Microfluidic devices are increasingly widespread in the literature, being applied to numerous
exciting applications, from chemical research to Point-of-Care devices, passing through drug …
exciting applications, from chemical research to Point-of-Care devices, passing through drug …
A benchmark for machine-learning based non-invasive blood pressure estimation using photoplethysmogram
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 …
A reinforcement learning based artificial bee colony algorithm with application in robot path planning
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 …
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 …
Revolutionizing cardiology through artificial intelligence—Big data from proactive prevention to precise diagnostics and cutting-edge treatment—A comprehensive …
Background: Artificial intelligence (AI) can radically change almost every aspect of the
human experience. In the medical field, there are numerous applications of AI and …
human experience. In the medical field, there are numerous applications of AI and …
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 …
Advancement in the cuffless and noninvasive measurement of blood pressure: A review of the literature and open challenges
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 …
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 …
A review of deep learning methods for photoplethysmography data
Photoplethysmography (PPG) is a highly promising device due to its advantages in
portability, user-friendly operation, and non-invasive capabilities to measure a wide range of …
portability, user-friendly operation, and non-invasive capabilities to measure a wide range of …