Article
Publicly Available
Frontmatter
Published/Copyright:
November 23, 2020
Published Online: 2020-11-23
Published in Print: 2020-11-18
©2020 Walter de Gruyter GmbH, Berlin/Boston
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- A multi-source co-frequency stimulus method for electroencephalogram (EEG) enhancement
- Analysis of statistical coefficients and autoregressive parameters over intrinsic mode functions (IMFs) for epileptic seizure detection
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- A microelectromechanical system (MEMS) capacitive accelerometer-based microphone with enhanced sensitivity for fully implantable hearing aid: a novel analytical approach
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Articles in the same Issue
- Frontmatter
- Reviews
- A review of foot pose and trajectory estimation methods using inertial and auxiliary sensors for kinematic gait analysis
- EEG Source Imaging (ESI) utility in clinical practice
- Research articles
- A multi-source co-frequency stimulus method for electroencephalogram (EEG) enhancement
- Analysis of statistical coefficients and autoregressive parameters over intrinsic mode functions (IMFs) for epileptic seizure detection
- Scalp electroencephalography (sEEG) based advanced prediction of epileptic seizure time and identification of epileptogenic region
- A simple model to detect atrial fibrillation via visual imaging
- Insertion torque/time integral as a measure of primary implant stability
- A microelectromechanical system (MEMS) capacitive accelerometer-based microphone with enhanced sensitivity for fully implantable hearing aid: a novel analytical approach
- Integrating artificial neural network and scoring systems to increase the prediction accuracy of patient mortality and organ dysfunction
- Sparse-FCM and Deep Convolutional Neural Network for the segmentation and classification of acute lymphoblastic leukaemia
