[HTML][HTML] A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues

S Shamshirband, M Fathi, A Dehzangi… - Journal of Biomedical …, 2021 - Elsevier
In the last few years, the application of Machine Learning approaches like Deep Neural
Network (DNN) models have become more attractive in the healthcare system given the …

Methods for evaluating emotions evoked by food experiences: A literature review

D Kaneko, A Toet, AM Brouwer, V Kallen… - Frontiers in …, 2018 - frontiersin.org
Besides sensory characteristics of food, food-evoked emotion is a crucial factor in predicting
consumer's food preference and therefore in developing new products. Many measures …

A review of methods for sleep arousal detection using polysomnographic signals

X Qian, Y Qiu, Q He, Y Lu, H Lin, F Xu, F Zhu, Z Liu… - Brain sciences, 2021 - mdpi.com
Multiple types of sleep arousal account for a large proportion of the causes of sleep
disorders. The detection of sleep arousals is very important for diagnosing sleep disorders …

A multichannel convolutional neural network architecture for the detection of the state of mind using physiological signals from wearable devices

S Chakraborty, S Aich, M Joo, M Sain… - Journal of healthcare …, 2019 - Wiley Online Library
Detection of the state of mind has increasingly grown into a much favored study in recent
years. After the advent of smart wearables in the market, each individual now expects to be …

Driver state and behavior detection through smart wearables

A Tavakoli, S Kumar, M Boukhechba… - 2021 IEEE Intelligent …, 2021 - ieeexplore.ieee.org
Integrating driver, in-cabin, and outside environ-ment's contextual cues into the vehicle's
decision making is the centerpiece of semi-automated vehicle safety. Multiple systems have …

Video-based abnormal driving behavior detection via deep learning fusions

W Huang, X Liu, M Luo, P Zhang, W Wang… - IEEE Access, 2019 - ieeexplore.ieee.org
Video-based abnormal driving behavior detection is becoming more and more popular for
the time being, as it is highly important in ensuring safeties of drivers and passengers in the …

A deep learning approach to recognize cognitive load using ppg signals

F Gasparini, A Grossi, S Bandini - Proceedings of the 14th PErvasive …, 2021 - dl.acm.org
Physiological data are nowadays frequently used to recognize the affective state of subjects
while performing different tasks. Automatic recognition of a stressful state as a consequence …

Real-time personalized physiologically based stress detection for hazardous operations

TT Finseth, MC Dorneich, S Vardeman, N Keren… - IEEE …, 2023 - ieeexplore.ieee.org
When training for hazardous operations, real-time stress detection is an asset for optimizing
task performance and reducing stress. Stress detection systems train a machine-learning …

Hybrid scattering-LSTM networks for automated detection of sleep arousals

PA Warrick, V Lostanlen… - Physiological …, 2019 - iopscience.iop.org
Objective: Early detection of sleep arousal in polysomnographic (PSG) signals is crucial for
monitoring or diagnosing sleep disorders and reducing the risk of further complications …

[PDF][PDF] Emotion recognition with short-period physiological signals using bimodal sparse autoencoders.

YK Lee, DS Pae, DK Hong, MT Lim… - Intelligent Automation & …, 2022 - cdn.techscience.cn
With the advancement of human-computer interaction and artificial intelligence, emotion
recognition has received significant research attention. The most commonly used technique …