Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor

Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor

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 imp...

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Main Authors: Bunthit Watanapa, Orasa Patsadu, Piyapat Dajpratham, Chakarida Nukoolkit
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Applied Computational Intelligence and Soft Computing
Online Access:http://dx.doi.org/10.1155/2018/5434897
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spelling doaj-d04fc3e63a50401a925caadc85b56c382020-11-24T21:05:36ZengHindawi LimitedApplied Computational Intelligence and Soft Computing1687-97241687-97322018-01-01201810.1155/2018/54348975434897Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect SensorBunthit Watanapa0Orasa Patsadu1Piyapat Dajpratham2Chakarida Nukoolkit3School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, ThailandFaculty of Science and Technology, Rajamangala University of Technology Krungthep, Bangkok, ThailandFaculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, ThailandSchool of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, ThailandThis 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.http://dx.doi.org/10.1155/2018/5434897
collection DOAJ
language English
format Article
sources DOAJ
author Bunthit Watanapa
Orasa Patsadu
Piyapat Dajpratham
Chakarida Nukoolkit
spellingShingle Bunthit Watanapa
Orasa Patsadu
Piyapat Dajpratham
Chakarida Nukoolkit
Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor
Applied Computational Intelligence and Soft Computing
author_facet Bunthit Watanapa
Orasa Patsadu
Piyapat Dajpratham
Chakarida Nukoolkit
author_sort Bunthit Watanapa
title Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor
title_short Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor
title_full Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor
title_fullStr Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor
title_full_unstemmed Post-Fall Intelligence Supporting Fall Severity Diagnosis Using Kinect Sensor
title_sort post-fall intelligence supporting fall severity diagnosis using kinect sensor
publisher Hindawi Limited
series Applied Computational Intelligence and Soft Computing
issn 1687-9724
1687-9732
publishDate 2018-01-01
description 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.
url http://dx.doi.org/10.1155/2018/5434897
work_keys_str_mv AT bunthitwatanapa postfallintelligencesupportingfallseveritydiagnosisusingkinectsensor
AT orasapatsadu postfallintelligencesupportingfallseveritydiagnosisusingkinectsensor
AT piyapatdajpratham postfallintelligencesupportingfallseveritydiagnosisusingkinectsensor
AT chakaridanukoolkit postfallintelligencesupportingfallseveritydiagnosisusingkinectsensor
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