Abstract
The main procedures of attention-deficit hyperactivity disorder (ADHD) assessment are interviews with the subject, his or her parents and teacher, observation of the subject, and self-screening questionnaires. However, these traditional medical assessments have serious problems. Interviews may be efficient to an adult subject; however, adolescent subjects are not familiar to express their emotion and mental status precisely. Observation and self-screening questionnaires require a long period of time to be finished, being easily forged by an observer or a subject. To resolve these obstacles, we propose a virtual reality (VR)-based ADHD diagnosis model, in which the VR contents close to reality (such as a school environment) diagnose whether a subject is suspected ADHD or not by various sensors in VR and responses in the VR contents based on the ADHD categorization. We implement the VR contents to diagnose ADHD by using the Unity, which finds major ADHD characteristics by the ADHD categorization based on the Diagnostic and Statistical Manual of mental disorders (DSM-5). We present the medical data engineering and security features in our diagnosis method to protect a patient’s information.
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Acknowledgements
This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2020-0-00990, Platform Development and Proof of High Trust & Low Latency Processing for Heterogeneous\(\cdot \)Atypical\(\cdot \)Large Scaled Data in 5G-IoT Environment).
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Ryu, S.H., Oh, S., Lee, S., Chung, TM. (2020). A Novel Approach to Diagnose ADHD Using Virtual Reality. In: Dang, T.K., Küng, J., Takizawa, M., Chung, T.M. (eds) Future Data and Security Engineering. FDSE 2020. Lecture Notes in Computer Science(), vol 12466. Springer, Cham. https://doi.org/10.1007/978-3-030-63924-2_15
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DOI: https://doi.org/10.1007/978-3-030-63924-2_15
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