Paper Info
Title
Experimental research on real-time acquisition and monitoring of wearable EEG based on TGAM module.
Abstract
Long-term sleep disorders can reduce the body’s immunity, induce various diseases, and seriously endanger human health Multi-conducting EEG (Electroencephalogram) sleep monitoring is the gold standard for evaluating the quality of sleep all night. However, this method is professional and complicated, and it is difficult to apply to daily sleep monitoring. This paper first designed a wearable EEG acquisition system based on TGAM module. ‘Through the parameter initialization setting of the TGAM module and the Bluetooth module and the analysis of the communication protocol between the modules, the wearable EEG acquisition system was successfully built. Secondly, the extraction of different rhythm waves of EEG signals is realized by several FIR (Finite Impulse Response) bandpass filters. Principal component analysis was used to screen feature quantities. The related experiments were carried out by collecting the EEG signals of several testers through the new sensor TGAM. Finally, event-related potential analysis and event-related simultaneous analysis were used to complete the treatment of EEG segments and normal EEG segments of sleep apnea events, and normalized EEG was identified by normalized standard deviation analysis and triple normalized standard deviation analysis. The results show that the technical requirements of wearable EEG equipment can be met in terms of algorithm calculation and result performance, which can provide theoretical support for sleep monitoring.
Year
DOI
Venue
2020
10.1016/j.comcom.2019.12.055
Computer Communications
Keywords
Field
DocType
Monitoring of wearable EEG,Sleep EEG signal,EEG acquisition,Sleep monitoring,TGAM module
Sleep apnea,Normalization (statistics),Computer science,Real-time computing,Initialization,Finite impulse response,Bluetooth,Electroencephalography,Principal component analysis,Communications protocol
Journal
Volume
ISSN
Citations 
151
0140-3664
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Liyong Yin100.34
Chao Zhang212.04
Zhijie Cui300.34