Research And Design Of Emotional Concern System Of Elderly Based On Deep Learning

With the rapid development of China's economy,China is also rapidly entering the aging society,the problems brought about by aging are more and more prominent,not only the quality of life of the elderly,mental health problems have become increasingly prominent Mental health factors,the daily mood is a measure of an elderly mental health is one of the important indicators.This topic is based on the market demand,the current situation of the elderly living in the face of practical problems,in order to medical and psychological and other traditional research methods and other issues,with innovative methods designed a set of elderly emotional care system,more To solve the practical problems of the elderly.In the product and service,the system from the daily mood of the elderly to study,the elderly and their families tied together,managers and their families through the computer PC and mobile phone APP real-time view of the elderly and other emotions,and can view Different periods of emotional statistics,if the abnormal mood to a certain threshold,the system will automatically prompt the warning,in the current Internet era and the rise of the mobile Internet background,the system can make the family better and more convenient care and greetings for the elderly,The use of the system scenes,including nursing homes or elderly resident gathering points and so on.In the core technology to achieve,the use of deep learning methods and techniques to achieve the overall structure of the system to achieve the functions include face image acquisition,face emotion recognition,face recognition module,human detection,PC-side monitoring and data analysis,mobile APP-side data analysis and other functions.At the same time,this paper introduces the realization of the human body detection function based on the depth learning,uses the depth learning technology and adopts the different data sets to realize the depth learning network model,and finally achieves the system requirement in the accuracy rate and the detection speed.