Study on classification and identification of depressed patients and healthy people among adolescents based on optimization of brain characteristics of network / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1037-1044, 2020.
Article
in Chinese
| WPRIM
| ID: wpr-879234
ABSTRACT
To enhance the accuracy of computer-aided diagnosis of adolescent depression based on electroencephalogram signals, this study collected signals of 32 female adolescents (16 depressed and 16 healthy, age 16.3 ± 1.3) with eyes colsed for 4 min in a resting state. First, based on the phase synchronization between the signals, the phase-locked value (PLV) method was used to calculate brain functional connectivity in the θ and α frequency bands, respectively. Then based on the graph theory method, the network parameters, such as strength of the weighted network, average characteristic path length, and average clustering coefficient, were calculated separately (
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Brain
/
Diagnosis, Computer-Assisted
/
Electroencephalography
/
Support Vector Machine
Type of study:
Diagnostic study
/
Prognostic study
Limits:
Adolescent
/
Female
/
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2020
Type:
Article
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