Artículo de revista
EEG Classification during Scene Free-Viewing for Schizophrenia Detection
Fecha
2019Registro en:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Volumen 27, Issue 6, 2019, Pages 1193-1199
15580210
15344320
10.1109/TNSRE.2019.2913799
Autor
Devia, Christ
Mayol Troncoso, Rocío
Parrini, Javiera
Orellana, Gricel
Ruiz, Aida
Maldonado Arbogast, Pedro
Egana, Jose Ignacio
Institución
Resumen
Currently, the diagnosis of schizophrenia is made solely based on interviews and behavioral observations by a trained psychiatrist. Technologies such as electroencephalography (EEG) are used for differential diagnosis and not to support the psychiatrist's positive diagnosis. Here, we show the potential of EEG recordings as biomarkers of the schizophrenia syndrome. We recorded EEG while schizophrenia patients freely viewed natural scenes, and we analyzed the average EEG activity locked to the image onset. We found significant differences between patients and healthy controls in occipital areas approximately 500 ms after image onset. These differences were used to train a classifier to discriminate the schizophrenia patients from the controls. The best classifier had 81% sensitivity for the detection of patients and specificity of 59% for the detection of controls, with an overall accuracy of 71%. These results indicate that EEG signals from a free-viewing paradigm discriminate patients from healthy controls and have the potential to become a tool for the psychiatrist to support the positive diagnosis of schizophrenia.