Electronic healthcare system: Mental disorder assessment and intervention with self-treatment using rule-based techniques

Zamri, Dr. Nurnadiah (2021) Electronic healthcare system: Mental disorder assessment and intervention with self-treatment using rule-based techniques. In: Signals and Communication Technology. Springer, pp. 453-479. ISBN 18604862

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Abstract

Almost one million people worldwide die by suicide each year. One of the main reasons is due to depression. Life stresses, high depressions, and anxiety are commonly prevalent in mental health problems. Early detection and recognition are in need to allow better treatment and prevention on mental disorders as well as other complications. However, some patients skip their checkup routine due to multiple hospital procedures and long-waiting process. Motivated with the fog computing as a recent technological advancement, this chapter aims to facilitate a new version of an online system on electronic Mental Assessment and Self-Treatment System (e-MAST) for all patients. This system provides patients with stress questionnaires, anxiety questionnaires, and depressive symptoms questionnaires generated using rule-based techniques. Besides, the sum of answers from the patients will be calculated using weighted sum method. This system offers life stress controls and self-treatment techniques while awaiting professional help. This system helps to increase the scientific community’s awareness of mental health and creates an opportunity to embrace a healthy generation of people. Also, this system can be used at all times, anywhere, and can be benefited by all toward smart hospital ideas. © Springer Nature Switzerland AG 2021.

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