A review on transfer learning in EEG signal analysis
Electroencephalogram (EEG) signal analysis, which is widely used for human-computer
interaction and neurological disease diagnosis, requires a large amount of labeled data for …
interaction and neurological disease diagnosis, requires a large amount of labeled data for …
Machine learning for predicting epileptic seizures using EEG signals: A review
With the advancement in artificial intelligence (AI) and machine learning (ML) techniques,
researchers are striving towards employing these techniques for advancing clinical practice …
researchers are striving towards employing these techniques for advancing clinical practice …
Unsupervised deep anomaly detection for multi-sensor time-series signals
Nowadays, multi-sensor technologies are applied in many fields, eg, Health Care (HC),
Human Activity Recognition (HAR), and Industrial Control System (ICS). These sensors can …
Human Activity Recognition (HAR), and Industrial Control System (ICS). These sensors can …
[HTML][HTML] EEG-based emotion recognition: Review of commercial EEG devices and machine learning techniques
Emotion recognition based on electroencephalography (EEG) signal features is now one of
the booming big data research areas. As the number of commercial EEG devices in the …
the booming big data research areas. As the number of commercial EEG devices in the …
Emotion recognition from EEG signal focusing on deep learning and shallow learning techniques
Recently, electroencephalogram-based emotion recognition has become crucial in enabling
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review
Mental disorders represent critical public health challenges as they are leading contributors
to the global burden of disease and intensely influence social and financial welfare of …
to the global burden of disease and intensely influence social and financial welfare of …
[HTML][HTML] Wearables for industrial work safety: A survey
Today, ensuring work safety is considered to be one of the top priorities for various
industries. Workplace injuries, illnesses, and deaths often entail substantial production and …
industries. Workplace injuries, illnesses, and deaths often entail substantial production and …
Human emotion recognition and analysis in response to audio music using brain signals
Human emotion recognition using brain signals is an active research topic in the field of
affective computing. Music is considered as a powerful tool for arousing emotions in human …
affective computing. Music is considered as a powerful tool for arousing emotions in human …
MAtt: A manifold attention network for EEG decoding
YT Pan, JL Chou, CS Wei - Advances in Neural Information …, 2022 - proceedings.neurips.cc
Recognition of electroencephalographic (EEG) signals highly affect the efficiency of non-
invasive brain-computer interfaces (BCIs). While recent advances of deep-learning (DL) …
invasive brain-computer interfaces (BCIs). While recent advances of deep-learning (DL) …
Mr. Wolf: An energy-precision scalable parallel ultra low power SoC for IoT edge processing
This paper presents Mr. Wolf, a parallel ultra-low power (PULP) system on chip (SoC)
featuring a hierarchical architecture with a small (12 kgates) microcontroller (MCU) class …
featuring a hierarchical architecture with a small (12 kgates) microcontroller (MCU) class …