Wearable Social Sentiment Analysis System Based On Pulse Signal

Social emotions are divided into two parts,one is social,which refers to a series of behaviors in which individuals establish and engage in positive interactions with others;the other is emotions,which help individuals to establish,maintain and change relationships with others.Good social and emotional abilities allow you to engage in social activities with others,and those who have problems with social emotions may not be welcomed by the family and the surrounding environment,while habitual social and emotional problems are difficult to change.It may become more serious.A study of individual social emotions will help them understand their own problems and thus change themselves.At present,some traditional methods based on physiological signal analysis of emotions usually achieve the purpose of identifying specific emotions by acquiring various physiological data of the experimental objects,and at the same time accurately collecting a variety of physiological data of the human body requires not only an ideal collection environment,Moreover,there are also high requirements for the collection equipment,which leads to such research methods often staying on the basis of experiments and difficult to apply to actual life.Such methods are not suitable for emotional analysis in social scenes.Pulse signal acquisition is convenient and has high signal quality.At the same time,pulse signal as an important physiological parameter provides a basis for emotional classification in traditional emotion analysis research.It has been proved that it is feasible to use pulse signal alone for emotion analysis.Wearable devices feature computable,portable,wireless transceivers and long battery life.To this end,a neural signal analysis system based on pulse signal,portable belt and wearable is designed.The system uses the photoelectric volume pulse wave tracing method to collect the human body pulse signal,and uses the emotion-induced method to obtain the human body in calm,happiness,sadness and fear.The pulse data of the four emotional states,combined with the random forest algorithm,resulted in calm-happy,calm-sad,calm-fear,sad-happy and calm-happy-sad-fear emotional models,and finally under the common social scenes of college students.Social sentiment analysis simulation test.The system uses ZigBee wireless communication technology to realize multi-node self-organizing network and pulse data transmission.The host computer graphical interface developed by QT integrates the wavelet transform algorithm to demodulate the pulse signal,and the upper computer calls the emotional model trained by Matlab.Realize the analysis of social emotions;develop the WeChat public number and social sentiment analysis background management system based on SSM framework,realize that users use terminal equipment to collect pulse data,and create,view and manage social sentiment analysis experience records on WeChat.