Publication: Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor
Issued Date
2018-01-01
Resource Type
ISSN
16879732
16879724
16879724
Other identifier(s)
2-s2.0-85049104233
Rights
Mahidol University
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SCOPUS
Bibliographic Citation
Applied Computational Intelligence and Soft Computing. Vol.2018, (2018)
Suggested Citation
Bunthit Watanapa, Orasa Patsadu, Piyapat Dajpratham, Chakarida Nukoolkit Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor. Applied Computational Intelligence and Soft Computing. Vol.2018, (2018). doi:10.1155/2018/5434897 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/45686
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Title
Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor
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.