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Please use this identifier to cite or link to this item: http://dspace.cityu.edu.hk/handle/2031/6661
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dc.contributor.authorLai, Suet Manen_US
dc.date.accessioned2012-08-27T00:46:56Z
dc.date.accessioned2017-09-19T09:12:51Z
dc.date.accessioned2019-02-12T07:30:35Z-
dc.date.available2012-08-27T00:46:56Z
dc.date.available2017-09-19T09:12:51Z
dc.date.available2019-02-12T07:30:35Z-
dc.date.issued2012en_US
dc.identifier.other2012eelsm791en_US
dc.identifier.urihttp://144.214.8.231/handle/2031/6661-
dc.description.abstractFall is the leading causes of injury among the elderly people. A falling accidence can cause the elder get serious health threat such as fracture, head traumas, and even death. In this project, a detection fall system is designed to give a quick response to seek help if a fall is detected by using Smartphone. By taking the advantage of prevalence and convenience of Smartphone use, the design of detection sensors based on threshold-based tri-axial accelerometer fall detection algorithm. In order to increase the fall detection accuracy, two body tests are taken to define thresholds for different users; accelerator and orientation sensors inside Smartphone also are used to this project. An alarm will go off when a fall action is recognized. Afterwards, a series of alert actions are triggered. I.e. an automatic call service, SMS, GPS location is sent to the emergency contact person set by the user. These detecting and alarm services were examined and integrated into an Android application with user friendly interface. The results suggest that there is more or less some false alarms feedback when detecting fall. Also there is a concern about enabling application running in background and power consumption. A further fall study is highly recommended to define individual fall thresholds.en_US
dc.rightsThis work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner.en_US
dc.rightsAccess is restricted to CityU users.en_US
dc.titleFall detection for elderly using Android mobile phonesen_US
dc.contributor.departmentDepartment of Electronic Engineeringen_US
dc.description.supervisorSupervisor: Dr. Wong, Kwok Wo; Assessor: Dr. Leung, Andrew C Sen_US
Appears in Collections:Electrical Engineering - Undergraduate Final Year Projects 

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