Exploring the landscape of ubiquitous in-home health monitoring: a comprehensive survey

F Pourpanah, A Etemad - ACM Transactions on Computing for …, 2024 - dl.acm.org
Ubiquitous in-home health monitoring systems have become popular in recent years due to
the rise of digital health technologies and the growing demand for remote health monitoring …

Physiological signal analysis using explainable artificial intelligence: A systematic review

J Shen, J Wu, H Liang, Z Zhao, K Li, K Zhu, K Wang… - Neurocomputing, 2024 - Elsevier
With the continuous development of wearable sensors, it has become increasingly
convenient to collect various physiological signals from the human body. The combination of …

EEG-based cognitive load classification using feature masked autoencoding and emotion transfer learning

D Pulver, P Angkan, P Hungler, A Etemad - Proceedings of the 25th …, 2023 - dl.acm.org
Cognitive load, the amount of mental effort required for task completion, plays an important
role in performance and decision-making outcomes, making its classification and analysis …

Mobile phone use driver distraction detection based on MSaE of multi-modality physiological signals

X Zuo, C Zhang, F Cong, J Zhao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Driver distraction, a major cause of traffic crashes, is reported to reduce driving performance
and be detected with vehicle behavioral features. It also induces physiological responses …

A spatiotemporal separable graph convolutional network for oddball paradigm classification under different cognitive-load scenarios

Y Li, K Li, S Wang, H Wu, P Li - Expert Systems with Applications, 2025 - Elsevier
The application of flight automation systems has increased the demand for detecting the
cognitive load of pilots. Event-related potentials (ERPs) based on electroencephalogram …

Cognitive Workload Estimation in Conditionally Automated Vehicles Using Transformer Networks Based on Physiological Signals

A Wang, J Wang, W Shi, D He - Transportation Research …, 2024 - journals.sagepub.com
Though driving automation promises to improve driving safety, drivers are still required to be
ready to retake control in conditionally automated vehicles, which are defined by the Society …

Classification of Driver Cognitive Load in Conditionally Automated Driving: Utilizing Electrocardiogram-Based Spectrogram with Lightweight Neural Network

W Shi, Z Wang, A Wang, D He - Transportation Research …, 2024 - journals.sagepub.com
With the development of conditionally automated driving, drivers will be allowed to perform
non-driving-related tasks. Under such circumstances, continuous monitoring of driver …

[PDF][PDF] Classification of Driver Cognitive Load in Conditionally Automated Driving: Utilizing ECG-based Spectrogram with Light-weight Neural Network

W Shi, Z Wang, A Wang - personal.hkust-gz.edu.cn
With the development of conditionally automated driving, drivers will be allowed to perform
non-drivingrelated tasks. Under such circumstances, continuous monitoring of driver …