The invention discloses a brain electric features based emotional
state recognition method. The method comprises the following steps of:
data acquisition stage: under the condition of international emotional picture induction, extracting 64 brain electric data which is tested under the induction of different-happiness-level pictures; data pretreatment stage: carrying out four stages of reference
electric potential variation, down sampling, band-pass filtering, electro-oculogram removal on the collected 64 brain electric data;
feature extraction stage: extracting
time domain features after signals after pretreatment are filtered by a
common space model
algorithm; and
feature recognition: recognizing the features by using a
support vector machine classifier, and differentiating different emotional states. According to the method, an OVR (one versus rest)
common space model
algorithm is used for removing the interference of background signals, and is used for the
signal intensification of multiple types of emotion induced brain
electricity; after the background signals are removed, the differences among different types of emotional brain
electricity are intensified, the recognition accurate ratio of subjects is relatively ideal when the recognition is carried out by the
time domain variance features, and the emotions of different happiness can be differentiated accurately.