Results 81 to 90 of about 2,785,850 (195)

Application of a parametric supermatrix multi-task multimodal deep learning model based on electroencephalogram and peripheral physiological signal fusion in emotion recognition

Frontiers in Neuroscience
Accurate emotion recognition under limited computational resources remains challenging in applications such as healthcare, human–computer interaction, and intelligent systems.
Xue Li, Xue Li, Piqiang Gong, Chuantao Li, Xiaohan Ding, Fuming Chen   +5 more
doaj   +1 more source

Personalized Classification of Scenario-Derived Operational Driver-State Classes from Non-Intrusive Wearable Signals in Real-World SAE Level 2 Automated Driving

Sensors
At SAE Level 2 automation, the human driver retains full supervisory responsibility, making unobtrusive monitoring relevant for maintaining supervision under real-world driving conditions.
Raul Fernandez-Matellan, David Puertas-Ramirez, David Martin Gomez, Jesus G. Boticario   +3 more
doaj   +1 more source

A Domain Generalization and Residual Network-Based Emotion Recognition from Physiological Signals

Cyborg and Bionic Systems
Emotion recognition from physiological signals (ERPS) has drawn tremendous attention and can be potentially applied to numerous fields. Since physiological signals are nonstationary time series with high sampling frequency, it is challenging to directly ...
Junnan Li, Jiang Li, Xiaoping Wang, Xin Zhan, Zhigang Zeng   +4 more
doaj   +1 more source

Replication Data for: PySiology: a Python Package for Physiological Feature Extraction

, 2019
Physiological signals have been widely used to measure continuous data from the autonomic nervous system in the fields of Computer Science, Psychology and Human-Computer Interaction.
Gabrieli, Giulio, Esposito, Gianluca
core   +1 more source

Emotion recognition based on multimodal physiological electrical signals

Frontiers in Neuroscience
With the increasing severity of mental health problems, the application of emotion recognition techniques in mental health diagnosis and intervention has gradually received widespread attention.
Zhuozheng Wang, Yihan Wang
doaj   +1 more source

A Systematic Literature Review of Machine Learning-Based Personality Trait Detection Using Electroencephalographic Data

IEEE Access
Traditional self-report personality assessments, such as detecting Big Five personality traits through the NEO-Five-Factor-Inventory, are personnel-, time- and cost-intensive approaches that are prone to bias, whereas electroencephalography provides a ...
Celina Rieck, Pascal Penava, Ricardo Buettner   +2 more
doaj   +1 more source

Classification of Physiological Sensor Signals Using Artificial Neural Networks

, 2015
Physiological signals have certain prominent characteristics that distinguish them from other types of physiological signals which are familiar to experts and assessed by inspection.
Gedeon, Tamas (Tom), Sharma, Nandita
core   +1 more source

Evaluation of Mental Stress Using Physiological Signals

, 2013
This research aims at the detection of mental stress using electroencephalogram (EEG) and electrocardiogram (ECG) signals. The proposed scheme works by evaluating physiological variability that occurs in mentally stress and control environments.
SUBHANI, AHMAD RAUF
core  

Monitoring Physiological Signals Using Camera [PDF]

, 2016
: Monitoring vital physiological signals, such as heart rate, blood pressure and breathing pattern, are basic requirements in the diagnosis and management of various diseases.

core  

Mitochondrial signalling, physiology and pathophysiology [PDF]

Pflügers Archiv - European Journal of Physiology, 2018
openaire   +2 more sources