Research On Depression Monitoring Service Product Based On Value Co-creation

With the continuous development of social economy,modern people deal with the pressure of study,work and life gradually increasing,and the number of patients suffering from mental diseases is rising year by year.However,there are still great shortcomings in the research on depression.In terms of the diagnosis of depression,the most commonly used method is to judge the depression level according to the self-rated depression scales such as Hamilton and PHQ-9 filled in by patients.This method is highly subjective,and the patient’s own situation and the doctor’s experience level may become the cause of inaccurate diagnosis.In addition,with the popularity and development of smart products,more and more smart watches and wristbands are equipped with the function of pressure monitoring,which uses heart rate variability data for pressure monitoring and can warn depression to a certain extent.However,smart wristbands and wristwatches use photoelectric frequency multiplier technology for heart rate variability monitoring,and the monitoring accuracy is low.Secondly,with the advent of the post-epidemic era,monitoring and early warning of depression at home has become a new trend,but the current patients have insufficient knowledge of depression and diagnosis process,lack of products specifically for depression,and poor user experience.Therefore,this paper uses the heart rate belt to collect the heart rate variability data,so as to monitor and warn depression.Because the heart rate belt uses the ECG method to collect the ECG signals,the collected data is more accurate.Meanwhile,the RBF neural network depression early warning model was constructed in this paper.By comparing a large number of experimental data,the heart rate variability feature vectors such as SDANN and RMSSD were selected as the basis for depression monitoring and early warning,and the effectiveness of the system for depression early warning was verified through experiments.Secondly,in order to provide patients with depression with more convenient and efficient experience of diagnosis and treatment service,the user experience of diagnosis and treatment service for depression is optimized by using the value co-creation theory.The whole process model of home monitoring,early warning and rehabilitation stage for patients with depression is established horizontally from the process of value co-creation,and the five elements of user experience are established vertically.Investigate and analyze depression-related products and the needs of depressed people,summarize the behavior habits,lifestyle and interests of depressed patients of different ages,and analyze their own subjective and external objective needs,so as to guide the final design practice.Based on the existing theoretical research and technical achievements,this paper applies the concept of user experience and value co-creation to build a service platform for depression monitoring and treatment,establish connections for patients,family members and medical institutions,and build a bridge of communication between patients and family members,patients and doctors,and patients and patients.This paper hopes that the study of interaction design can provide some guidance and reference for solving other similar medical service problems.