eTherapist – AI based automatic depression severity assessment APP

• Main Authors: Yun-Nien Huang, 黃韻年
• Other Authors: 陳家麟
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/uufw24

碩士 === 國立臺灣大學 === 企業管理碩士專班 === 107 === Depression is a common but serious mental illness that affects the ability to think, and daily activities causing patients to suffer every day, and even committing suicide. From the statistics at World Health Organization, depression affected 350 million people worldwide, and WHO listed depression as the fourth most significant cause of suffering and disability worldwide [1]. Over 800,000 suicide every year, making it the second leading cause of death in 15-29 years old. In Taiwan alone, 2 million people had suffered from depression, and 1.27 million people now are taking long-term antidepressants by statistics of Taiwan Ministry of Health and Welfare [2]. Depression accounts for the biggest share of the world’s burden of disease, measured by years lost to disability (YLD): healthy years ‘lost’ because they are lived with a physical or mental disability. When ranked by disability and death combined, depression comes ninth behind prolific killers such as heart disease, stroke and HIV. Depression is caused by combination of genetics, biological, environment and psychological factors, and is treatable even for the most severe depression. Yet depression is widely undiagnosed and untreated because of social stigma, unawareness of the disease and lack of mental health resources [3]. To further explore the problems of insufficient of treatment of depression, we conduct interviews with depressed patients and therapists in Taiwan. From the interviews, we conclude that the reasons behind are high cost of mental treatment, low treatment availability, patients unaware of their depression severity level, and social stigma. Lack of assessment and awareness of depression result in insufficient and ineffective care for the disease despite the effective psychological and pharmacological treatments for depression. With the advance of 5G, the smartphones combined with cloud computing break through the limited computational power in smartphones. The raise of awareness of mental health in millennials results in prevalence of metal health APPs. We therefore propose a solution to diagnose depression with the help of facial recognition, speech processing, and natural language processing utilizing artificial intelligence. With the interface of mobile phone APP, our solution could easily access to everyone. This goal is to detect depression in the early stage to prevent further loss in financial and personal life, and urge our customers to go to professional clinics or hospitals for further help if diagnosed as severe or moderate depression. Automatic detection of depressive symptoms would potentially increase the rate of diagnostic visit, and patients’ awareness of their own depression severity levels, leading to faster intervention. In the research paper conducted by Professor Fei-Fei Li at Stanford University, automatic AI based depression severity test could achieve both accuracy and efficiency utilizing artificial intelligence [4]. The automatic detection algorithms identify facial traits and voices characteristics could help provide a universal and low-cost way of spotting the early signs of depression with smartphones. In practice, clinicians identify depression in patients by first measuring the severity of depressive symptoms during in-person clinical interviews. During these interviews, clinicians assess both verbal and non-verbal indicators of depressive symptoms including monotone pitch, reduced articulation rate, lower speaking volumes, fewer gestures, and more downward gazes [4]. If such symptoms persist for two weeks, the patient is considered to have a major or severe depressive episode. Structured questionnaires such as DSM-IV [5] and PHQ-9 [6] have been developed and validated in clinical populations to assess the severity of depressive symptoms. The major purpose of our APP is to serve potential patients with convenient diagnosis to increase their self-awareness of their own depression severity levels in an accessible, affordable, and effective way. Also, the therapists and psychiatrists could use the App to monitor their patients and it serves as marketing channels for related fields such as hospitals, clinics, pharmaceutical companies, medical device companies, gaming, recreational, entertainment, and exercising App companies.