Photoplethysmography is a key sensing technology which is used in wearable devices such
as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to …

According to the Pan American Health Organization, cardiovascular disease is the leading
cause of death worldwide, claiming an estimated 17.9 million lives each year. This paper …

The feature selection problem is one of the pre-processing mechanisms to find the optimal
subset of features from a dataset. The search space of the problem will exponentially grow …

Anesthesia drug overdose hazards and lack of gold standards in anesthesia monitoring lead
to an urgent need for accurate anesthesia drug detection. To investigate the PPG waveform …

The degraded quality of the electrocardiogram (ECG) signals is the main source of false
alarms in critical care units. Therefore, a preliminary analysis of the ECG signal is required to …

Objective: This study aimed to develop a robust and data driven automatic motion artifacts
(MA) removal technique from electrodermal activity (EDA) signal. Methods: we proposed a …

Photoplethysmography (PPG) signals collected by wearables have been shown to be
effective in accurate detection of atrial fibrillation (AF), provided that the data are devoid of …

Remote photoplethysmogram (rPPG) is a low-cost method to extract blood volume pulse
(BVP). Some crucial vital signs, such as heart rate (HR) and respiratory rate (RR) etc. can be …

Photoplethysmography is now widely utilised by clinical devices such as pulse oximeters,
and wearable devices such as smartwatches. It holds great promise for health monitoring in …

Noninvasive blood glucose (BG) measurement could significantly improve the prevention
and management of diabetes. In this paper, we present a robust novel paradigm based on …