Publication:
Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor

dc.contributor.authorBunthit Watanapaen_US
dc.contributor.authorOrasa Patsaduen_US
dc.contributor.authorPiyapat Dajprathamen_US
dc.contributor.authorChakarida Nukoolkiten_US
dc.contributor.otherRajamangala University of Technology systemen_US
dc.contributor.otherFaculty of Medicine, Siriraj Hospital, Mahidol Universityen_US
dc.contributor.otherKing Mongkut s University of Technology Thonburien_US
dc.date.accessioned2019-08-23T10:59:27Z
dc.date.available2019-08-23T10:59:27Z
dc.date.issued2018-01-01en_US
dc.description.abstract© 2018 Bunthit Watanapa et al. This paper proposes a fall severity analytic and post-fall intelligence system with three interdependent modules. Module I is the analysis of fall severity based on factors extracted in the phases of during and after fall which include innovative measures of the sequence of body impact, level of impact, and duration of motionlessness. Module II is a timely autonomic notification to relevant persons with context-dependent fall severity alert via electronic communication channels (e.g., smartphone, tablet, or smart TV set). Lastly, Module III is the diagnostic support for caregivers and doctors to have information for making a well-informed decision of first aid or postcure with the chronologically traceable intelligence of information and knowledge found in Modules I and II. The system shall be beneficial to caregivers or doctors, in giving first aid/diagnosis/treatment to the subject, especially, in cases where the subject has lost consciousness and is unable to respond.en_US
dc.identifier.citationApplied Computational Intelligence and Soft Computing. Vol.2018, (2018)en_US
dc.identifier.doi10.1155/2018/5434897en_US
dc.identifier.issn16879732en_US
dc.identifier.issn16879724en_US
dc.identifier.other2-s2.0-85049104233en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/45686
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85049104233&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titlePost-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensoren_US
dc.typeArticleen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85049104233&origin=inwarden_US

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