A study on an energy consumption model correlated to abnormal behavior by contactless method

Zhi Ren Tsai, Han-Wei Zhang, Chin-Teng Lin

Research output: Contribution to journalArticlepeer-review


The anxiety disorders, major depressive illness, substance use disorder, false beliefs, confused thinking, reduced social engagement, reduced emotional expression, a lack of motivation, and refusing to accept the wearable medical devices have happened in schizophrenia patients. Of course, a methodological critique of wearable medical devices towards a behavior model is suffering from a refusing action of schizophrenia patient. Hence, a novel real-time and robust application on correlation of stereo vision and abnormal behavior in schizophrenia is proposed in this paper. A robust image process is key to further exploring the behavior of schizophrenia patient by contactless surveillance, and from any view of patient to predict the abnormal sign of patient. This abnormal sign of energies consumption may be caused by inappropriate prescription or other medical negligence. An indicator for this abnormal sign of single specific patient should be designed by comparing with the past normal records of this patient. This study aims to provide a predictive diagnosis of patient. This diagnosis is obtained by this indicator to inform the hospital workers to make the preventing medical treatment. It enhances the secure healthcare, and will be proof in the Chang Bing Show Chwan Memorial hospital since first author has completed training and submitted proof with Institutional Review Board (IRB) in Taiwan in the past. (C) 2017 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)53-62
Number of pages10
JournalComputers in Human Behavior
StatePublished - Sep 2017


  • Schizophrenia; Energy consumption recognition; Abnormal human behavior; Predictive diagnosis; Institutional review board

Fingerprint Dive into the research topics of 'A study on an energy consumption model correlated to abnormal behavior by contactless method'. Together they form a unique fingerprint.

Cite this