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

Tsai, ZR; Zhang, HW; Lin, CT

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

Tsai, ZR Zhang, HW Lin, CT

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Publication Type:: Journal Article
Citation:: Computers in Human Behavior, 2017, 74 pp. 53 - 62
Issue Date:: 2017-09-01

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Field	Value	Language
dc.contributor.author	Tsai, ZR	en_US
dc.contributor.author	Zhang, HW	en_US
dc.contributor.author	Lin, CT https://orcid.org/0000-0001-8371-8197	en_US
dc.date.issued	2017-09-01	en_US
dc.identifier.citation	Computers in Human Behavior, 2017, 74 pp. 53 - 62	en_US
dc.identifier.issn	0747-5632	en_US
dc.identifier.uri	http://hdl.handle.net/10453/123350
dc.description.abstract	© 2017 Elsevier Ltd 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.	en_US
dc.relation.ispartof	Computers in Human Behavior	en_US
dc.relation.isbasedon	10.1016/j.chb.2017.04.028	en_US
dc.subject.classification	Education	en_US
dc.title	A study on an energy consumption model correlated to abnormal behavior by contactless method	en_US
dc.type	Journal Article
utslib.citation.volume	74	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	1701 Psychology	en_US
utslib.for	1702 Cognitive Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	74	en_US

Abstract:

© 2017 Elsevier Ltd 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.

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http://hdl.handle.net/10453/123350