publication . Article . Other literature type . 2018

A New Regularized Matrix Discriminant Analysis (R-MDA) Enabled Human-Centered EEG Monitoring Systems

Jie Su; Linbo Qing; Xiaohai He; Hang Zhang; Jing Zhou; Yonghong Peng;
Open Access English
  • Published: 08 Feb 2018
  • Publisher: IEEE
  • Country: United Kingdom
The wider use of wearable devices for electroencephalogram (EEG) data capturing provides a very useful way for the monitoring and self-management of human health. However, the large volumes of data with high dimensions cause computational complexity in EEG data processing and pose a great challenge to the use of wearable EEG devices in healthcare. This paper proposes a new approach to extract the structural information of EEG data and tackle the curse of dimensionality of the EEG data. A set of methods for dimensionality reduction (DR)-like linear discriminant analysis (LDA) and their improved methods have been developed for EEG processing in the literature. How...
ACM Computing Classification System: ComputingMethodologies_PATTERNRECOGNITION
free text keywords: Data_Science, General Engineering, General Materials Science, General Computer Science, Distributed computing, Curse of dimensionality, Electroencephalography, medicine.diagnostic_test, medicine, Wearable technology, business.industry, business, Computational complexity theory, Computer science, Matrix decomposition, Pattern recognition, Artificial intelligence, Projection (linear algebra), Linear discriminant analysis, Dimensionality reduction
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