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EEG Signal Processing Techniques and Applications
Materialtyp:
ArtikelUtgivningsinformation: MDPI - Multidisciplinary Digital Publishing Institute 2024Beskrivning: 1 electronic resource (300 p.)Innehållstyp: - text
- computer
- online resource
- 9783725800810
- 9783725800827
- Technology, Engineering, Agriculture, Industrial processes
- Technology: general issues
- CHB-MIT dataset
- DWT
- EEG
- EEG feature extraction
- EEG preprocessing
- LSTM
- PSD
- SMOTE
- XLtek EEG
- arousal
- artifact detection
- artificial intelligence
- auditory steady-state response (ASSR)
- brain computer interfaces
- brain–computer interface
- center-out reaching
- circulant singular spectrum analysis (CiSSA)
- classification
- common spatial patterns (CSP)
- convolutional neural network (CNN)
- cross-domain transfer learning
- deep learning
- depth of anesthesia
- dry electrodes
- electrocardiography (ECG)
- electroencephalogram
- electroencephalography
- electroencephalography (EEG)
- electromyography
- emotion recognition
- ensemble learning
- epilepsy
- event-related desynchronization (ERD)
- event-related spectral perturbation (ERSP)
- feature engineering
- feature extraction
- frustration
- functional connectivity
- game design
- gamification
- heterogeneous data
- in degree and out degree
- individual gamma frequency (IGF)
- long short-term memory (LSTM)
- longitudinal bipolar montage (LB)
- machine learning
- manipulability
- mental states classification
- mental workload
- motor
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This Special Issue provides a forum for original high-quality research in Electroencephalography (EEG) signal pre-processing, modelling, and analysis in the time, space, frequency, or time–frequency domains. It focuses particularly on the utilization of machine learning and deep learning techniques. The range of applications covers healthcare, emotion, motor imagery, external stimulation, mental workload, and satisfaction.
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