Skip navigation
Run Run Shaw Library City University of Hong KongRun Run Shaw Library

Please use this identifier to cite or link to this item: http://dspace.cityu.edu.hk/handle/2031/8746
Full metadata record
DC FieldValueLanguage
dc.contributor.authorYung, Yu Kwanen_US
dc.date.accessioned2017-03-08T06:23:32Z
dc.date.accessioned2017-09-19T09:15:52Z
dc.date.accessioned2019-02-12T07:34:47Z-
dc.date.available2017-03-08T06:23:32Z
dc.date.available2017-09-19T09:15:52Z
dc.date.available2019-02-12T07:34:47Z-
dc.date.issued2016en_US
dc.identifier.other2016eeyyk049en_US
dc.identifier.urihttp://144.214.8.231/handle/2031/8746-
dc.description.abstractIn daily life, falling is one of the major reasons to cause personal injury, especially for the elderly. If there is no any action to take care of the person who fell, it may become seriously physical damage and fatal. Therefore, it is necessary to develop a system to monitor walking status of people in our daily life. In the project, the normal walking gait and motionless (e.g. standing) is investigated. Based on the understanding of walking gait, a fall detection algorithm is then developed to determine whether fall accident is occurred. To collect the data of the motion, a 3-axis-accelerometer sensor is used, which can measure the accelerations due to gravity in 3 axis (X, Y, Z). An Android application is developed to make the algorithm able to apply in daily life better. To analyze collected data, some method are used. A moving window method is used to do calculation (e.g. mean) to analyze the walking gait. To improve the accuracy to compute period, a low pass filter is used to smooth data. Some advanced calculation is developed to get specific data, such as mean of minimum peak. In the algorithm, normal status and falling can be determined.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 Elderlyen_US
dc.contributor.departmentDepartment of Electronic Engineeringen_US
dc.description.supervisorSupervisor: Dr. Leung, Shu Hung; Assessor: Prof. Chen, Jieen_US
Appears in Collections:Electrical Engineering - Undergraduate Final Year Projects 

Files in This Item:
File SizeFormat 
fulltext.html146 BHTMLView/Open
Show simple item record


Items in Digital CityU Collections are protected by copyright, with all rights reserved, unless otherwise indicated.

Send feedback to Library Systems
Privacy Policy | Copyright | Disclaimer