Personalized blood pressure estimation using photoplethysmography: A transfer learning approach
In this paper, we present a personalized deep learning approach to estimate blood pressure
(BP) using the photoplethysmogram (PPG) signal. We propose a hybrid neural network …
(BP) using the photoplethysmogram (PPG) signal. We propose a hybrid neural network …
Wearable skin-like optoelectronic systems with suppression of motion artifacts for cuff-less continuous blood pressure monitor
According to the statistics of the World Health Organization, an estimated 17.9 million people
die from cardiovascular diseases each year, representing 31% of all global deaths …
die from cardiovascular diseases each year, representing 31% of all global deaths …
The internet of things [Guest Editorial]
J Zheng, D Simplot-Ryl, C Bisdikian… - IEEE Communications …, 2011 - ieeexplore.ieee.org
The Internet has experienced a tremendous growth in the past three decades, evolving from
a network of a few hundred hosts to a platform linking billions of" things" globally, including …
a network of a few hundred hosts to a platform linking billions of" things" globally, including …
Sparse learned kernels for interpretable and efficient medical time series processing
Rapid, reliable and accurate interpretation of medical time series signals is crucial for high-
stakes clinical decision-making. Deep learning methods offered unprecedented …
stakes clinical decision-making. Deep learning methods offered unprecedented …
Non-invasive classification of blood glucose level for early detection diabetes based on photoplethysmography signal
Monitoring systems for the early detection of diabetes are essential to avoid potential
expensive medical costs. Currently, only invasive monitoring methods are commercially …
expensive medical costs. Currently, only invasive monitoring methods are commercially …
Robust PPG motion artifact detection using a 1-D convolution neural network
Background and objectives Continuous monitoring of physiological parameters such as
photoplethysmography (PPG) has attracted increased interest due to advances in wearable …
photoplethysmography (PPG) has attracted increased interest due to advances in wearable …
A supervised machine learning semantic segmentation approach for detecting artifacts in plethysmography signals from wearables
Objective. Wearable devices equipped with plethysmography (PPG) sensors provided a low-
cost, long-term solution to early diagnosis and continuous screening of heart conditions …
cost, long-term solution to early diagnosis and continuous screening of heart conditions …
Uncertainties in the Analysis of Heart Rate Variability: A Systematic Review
Heart rate variability (HRV) is an important metric with a variety of applications in clinical
situations such as cardiovascular diseases, diabetes mellitus, and mental health. HRV data …
situations such as cardiovascular diseases, diabetes mellitus, and mental health. HRV data …
Noninvasive classification of blood pressure based on photoplethysmography signals using bidirectional long short-term memory and time-frequency analysis
The photoplethysmography (PPG) method for continuous noninvasive measurements of
blood pressure (BP) offers a more comfortable solution than conventional methods. The …
blood pressure (BP) offers a more comfortable solution than conventional methods. The …
A survey of photoplethysmography and imaging photoplethysmography quality assessment methods
T Desquins, F Bousefsaf, A Pruski, C Maaoui - Applied Sciences, 2022 - mdpi.com
Photoplethysmography is a method to visualize the variation in blood volume within tissues
with light. The signal obtained has been used for the monitoring of patients, interpretation for …
with light. The signal obtained has been used for the monitoring of patients, interpretation for …