Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor
Joint Authors
Watanapa, Bunthit
Patsadu, Orasa
Dajpratham, Piyapat
Nukoolkit, Chakarida
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-06-03
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Watanapa, Bunthit& Patsadu, Orasa& Dajpratham, Piyapat& Nukoolkit, Chakarida. 2018. Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor. Applied Computational Intelligence and Soft Computing،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1117051
Modern Language Association (MLA)
Watanapa, Bunthit…[et al.]. Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor. Applied Computational Intelligence and Soft Computing No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1117051
American Medical Association (AMA)
Watanapa, Bunthit& Patsadu, Orasa& Dajpratham, Piyapat& Nukoolkit, Chakarida. Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor. Applied Computational Intelligence and Soft Computing. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1117051
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1117051