Physiological-signal-based emotion recognition: An odyssey from methodology to philosophy
W Li, Z Zhang, A Song - Measurement, 2021 - Elsevier
Exploration on emotions continues from past to present. Nowadays, with the rapid
advancement of intelligent technology, computer-aided emotion recognition using …
advancement of intelligent technology, computer-aided emotion recognition using …
An improved similarity measure for generalized trapezoidal fuzzy numbers and its application in the classification of EEG signals
Z Qi - International Journal of Fuzzy Systems, 2021 - Springer
The classification of electroencephalogram (EEG) signals plays a key role in detecting brain
activities. Fuzzy methods are widely applied in decision-making problems because they are …
activities. Fuzzy methods are widely applied in decision-making problems because they are …
[PDF][PDF] Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA)
NIM Razi, AWA Rahman, N Kamarudin - Indonesian Journal of …, 2020 - academia.edu
Learning disability (LD) is a neurological processing disorder that causes impediment in
processing and understanding information. LD is not only affecting academic performance …
processing and understanding information. LD is not only affecting academic performance …
A Comparitive Study of Machine Learning Algorithms for Identifying Mental States from EEG Recordings
Machine learning for studying EEG data has been widely published. On sub-area of
research is the identification of mental states by applying machine learning to EEG …
research is the identification of mental states by applying machine learning to EEG …
Development of unified neuro-affective classification tool (UNACT)
Brain signals have been analysed to understand the affective state of different cognitive and
mental conditions. For example, through the analysis, we can visualize the changes of …
mental conditions. For example, through the analysis, we can visualize the changes of …
[PDF][PDF] An efficient distance estimation and centroid selection based on k-means clustering for small and large dataset
GG Ladha, RKS Pippal - International Journal of Advanced …, 2020 - academia.edu
In this paper an efficient distance estimation and centroid selection based on k-means
clustering for small and large dataset. Data pre-processing was performed first on the …
clustering for small and large dataset. Data pre-processing was performed first on the …
Exploring Emotional Responses of Design Styles using Electroencephalogram (EEG)
Emotion is a huge factor in creating immersive experience when playing a video game. It
can be stimulated by visual design elements. In particular, different levels of realism have an …
can be stimulated by visual design elements. In particular, different levels of realism have an …
[PDF][PDF] Dyslexia Diagnosis using the EEG Signal: A Machine Learning Approach
H Al-Barhamtoshy, DEM Motaweh - 2024 - preprints.org
Dyslexia is a learning disorder impacting reading, writing, calculation, memory, and spelling
abilities. It is a neurodevelopmental condition affecting approximately 5-10% of the …
abilities. It is a neurodevelopmental condition affecting approximately 5-10% of the …