BACKGROUND: The field of contactless health monitoring has witnessed significant advancements with the advent of piezoelectric sensing technology, which enables the monitoring of vital signs such as heart rate and respiration without requiring direct...
Accurate and efficient analysis of Electroencephalogram (EEG) signals is crucial for applications like neurological diagnosis and Brain-Computer Interfaces (BCI). Traditional methods often fall short in capturing the intricate temporal dynamics inher...
OBJECTIVES: Tinnitus affects millions globally, yet its clinical assessment relies on subjective reports, limiting diagnostic accuracy and treatment development. This study aimed to identify objective, tinnitus-related features within ensemble sponta...
Detecting driver drowsiness through electroencephalogram (EEG) poses challenges due to the complexity and variability of brain activity across different subjects. This study proposes a feature extraction pipeline combined with a Long Short-Term Memor...
A crucial part of brain-computer interfaces is the use of electroencephalogram (EEG) signals for human emotion identification, which analyzes patterns of brain activity to determine the emotional state. This field of study is becoming increasingly im...
. Sleep apnea is a common sleep disorder associated with severe health risks, necessitating accurate and efficient detection methods.. This study proposes ModelS4Apnea, a deep learning framework for sleep apnea detection from electrocardiogram (ECG) ...
Electroencephalography (EEG) preprocessing varies widely between studies, but its impact on classification performance remains poorly understood. To address this gap, we analyzed seven experiments with 40 participants drawn from the public ERP CORE d...
. Air trapping is a major symptom of respiratory diseases like chronic obstructive pulmonary disease and asthma, and has always been a significant problem in treating patients using mechanical ventilation. If not handled timely, it can pose risk of s...
Traditional cuffless blood pressure (BP) estimation methods often require collecting physiological signals, such as electrocardiogram (ECG) and photoplethysmography (PPG), from two distinct body sites to compute metrics like pulse transit time (PTT) ...
The success of AI-assisted decision-making systems over traditional methods has driven extensive research across various real-world applications. In the past decade, the application of AI systems for analysing physiological signals, particularly elec...
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