Design and development of a fall analyzer

Date of Publication

4-2018

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Electronics and Communications Engineering

Subject Categories

Electrical and Computer Engineering

College

Gokongwei College of Engineering

Department/Unit

Electronics and Communications Engineering

Thesis Adviser

Alexander C. Abad

Defense Panel Chair

Noriel C. Mallari

Defense Panel Member

John Anthony Jose
Roy Francis R. Navea

Abstract/Summary

Accidents is the 4th leading cause of death for all ages in the Philippines. One of the top five leading causes of death due to accidents in the Philippines for all ages is accidental falls. From worldwide statistics, 138 children, aged 0 to 18 years die daily due to falls. This translates to around 50,000 children dying each year due to accidental falls. It counts as the fifth leading cause of unintentional deaths of children below 14 years old in the Philippines. Falls were also found to be the leading cause of morbidity and lifelong disability among children. [Cri, 2014] The goal of this project is to design and develop a device that can detect motion of user such as standing, sitting, lying, walking and falling with direction detection of fall whether the fall is in forward, sideward or backward motion. This project produced the said device and was successfully developed with 95% of the devices accuracy of detection. When falling motion was established, the notification system of the device was activated, and message was sent to the recorded responder/s with details such as location of fall, time of fall, name of user who has fallen and the date of fall.The use of two accelerometers located at the hip and thigh resulted as a good component in making a motion detection device with 92.22% reliability. The development of falling device that can recognize direction of fall with the use of the same two modules resulted with 92.22% of accuracy. Motion detection such as standing, sitting, walking and lying that are sub-feature of this device was successfully detected with 97.5% overall accuracy rate. In general view of the devices performance, the design and development of fall analyzer with specific motion detection which can be personalized with the function of send notification message to recorded responder/s during the fall was achieved with above 80% acceptable accuracy rate.

Abstract Format

html

Note

Aenon Cunanan is under Bachelor of Science in Computer Engineering (BS-CpE) program

Language

English

Format

Print

Accession Number

TU17354; CDTU017354

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

xiv, 131 leaves : illustrations (some color) ; 28 cm + 1 computer disc ; 4 3/4 in.

Keywords

Falls (Accidents); Falls (Accidents)--Investigation; Accidents

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Embargo Period

5-13-2026

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