An interactive design solution for prenatal emotional nursing of pregnant women

Abstract

With the continuous development of interactive technology, informatization has begun to integrate into people's life[1].Having been neglected in history, postpartum depression reminds us that we need to pay attention to maternal emotional needs and prenatal care[2]. In the current situation, it is worth researching the interactive products for prenatal emotional care. According to the survey, it is not difficult to find that some speech emotion and facial expression recognition technologies in artificial intelligence are developing Which have large potential for extensive use.[3,4]. Therefore, it is necessary and feasible to design prenatal emotional diagnosis tools for pregnant women. This study has designed a product to care for pregnant women by identifying their emotional needs through AI recognition technologies. Appropriate prenatal intervention is conducive to the prevention of postpartum depression[5,6] . The use of artificial intelligence recognition technology can provide an appropriate emotional care plan. This can reduce the difficulty of training medical personnel and the difficulty of relatives caring for pregnant women. Therefore, the risk of postpartum depression can be reduced. QUESTIONCollecting opinions and information from previous studies is an important reference for this study. Therefore, this study needs to solve the following problems.1) How to design an artificial intelligence product that can accurately diagnose the emotion of pregnant women?2) How to integrate AI facial emotion recognition technology?3) How to help nurses and their families take care of users more professionally and easily through the information database?4) How to adapt the emotional care program provided by interactive products to different pregnant women? Methods:the research methods of this study are as follows:1) Observing the working process of artificial midwives and psychologists to find Which part can be assisted by machines[7].2) To understand the emotional needs of pregnant women through interview.3) To brainstorm according to the real data collected before and research findings, and then design interactive products that can practically solve the emotional care problems of pregnant women.4) Through the experiment of AI emotion recognition technologies, the feasibility of emotion recognition is verified. CONCLUSIONS:With the continuous development of artificial intelligence, more and more artificial intelligence products have entered our life [1]. This study is aimed to help pregnant women prevent prenatal and postpartum depression and maintain their health through artificial intelligence interaction technologies. This study is exploring the solution under the help of artificial intelligence after studying the problem that prenatal and postpartum emotion are neglected. This design is still in the conceptual design stage, but it seems only a matter of time before this design is applied in the future[8]. REFERENCES:[1]. Lee H S , Lee J . Applying Artificial Intelligence in Physical Education and Future Perspectives. 2021.[2]. Beck C T . Postpartum depression: it isn't just the blues.[J]. American Journal of Nursing, 2006, 106(5):40-50.[3].Ramakrishnan S , Emary I M M E . Speech emotion recognition approaches in human computer interaction[J]. Telecommunication Systems, 2013, 52(3):OnLine-First.[4]. Samara A , Galway L , Bond R , et al. Affective state detection via facial expression analysis within a human–computer interaction context[J]. Journal of Ambient Intelligence & Humanized Computing, 2017.[5]. Clatworthy J . The effectiveness of antenatal interventions to prevent postnatal depression in high-risk women[J]. Journal of Affective Disorders, 2012, 137(1-3):25-34.[6]. Ju C H , Hye K J , Jae L J . Antenatal Cognitive-behavioral Therapy for Prevention of Postpartum Depression: A Pilot Study[J]. Yonsei Medical Journal, 2008, 49(4):553-.[7]. Fletcher A , Murphy M , Leahy-Warren P . Midwives' experiences of caring for women's emotional and mental well-being during pregnancy[J]. Journal of Clinical Nursing, 2021.[8]. Jin X , Liu C , Xu T , et al. Artificial intelligence biosensors: Challenges and prospects[J]. Biosensors & Bioelectronics, 2020, 165:112412.

Keywords: emotion recognition, AI, humanization.

DOI: 10.54941/ahfe1001973