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Real-time threshold-based fall detection system using wearable IoT

This paper presents a Real-Time Fall Detection System (FDS) in the form of a wearable device integrating an ADXL335 accelerometer as a fall detection sensor, and classify the falling condition based on the threshold method. This system detects the wearer's movements and analyses the result in b...

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Main Authors: Nur Izdihar, Muhd Amir, Rudzidatul Akmam, Dziyauddin, Norliza, Mohamed, Nor Syahidatul Nadiah, Ismail, Nor Saradatul Akmar, Zulkifli, Norashidah, Md Din
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://umpir.ump.edu.my/id/eprint/39410/1/Real-Time%20Threshold-Based%20Fall%20Detection%20System%20Using%20Wearable%20IoT.pdf
http://umpir.ump.edu.my/id/eprint/39410/2/Real-time%20threshold-based%20fall%20detection%20system%20using%20wearable%20IoT_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39410/
https://doi.org/10.1109/ICSSA54161.2022.9870974
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spelling my.ump.umpir.394102023-11-28T04:41:08Z http://umpir.ump.edu.my/id/eprint/39410/ Real-time threshold-based fall detection system using wearable IoT Nur Izdihar, Muhd Amir Rudzidatul Akmam, Dziyauddin Norliza, Mohamed Nor Syahidatul Nadiah, Ismail Nor Saradatul Akmar, Zulkifli Norashidah, Md Din QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) This paper presents a Real-Time Fall Detection System (FDS) in the form of a wearable device integrating an ADXL335 accelerometer as a fall detection sensor, and classify the falling condition based on the threshold method. This system detects the wearer's movements and analyses the result in binary output conditions of 'Fall' for any fall occurrence or 'Normal' for other activities. The transmitter or FDS-Tx which is attached to the user's garment will constantly transmit data reading to the receiver or FDS-Rx via XBee module for data analysis. Raspberry Pi as the processor in FDS-Rx provides computational resources for immediate output analysis, by using threshold method, the computed results are sent to the cloud utilizing the Wi-Fi to display the user's condition on the authority's dashboard for further action. The working conditions of the systems are validated through an experiment of 10 volunteers whose perform several activities including fall events. Based on the threshold proposed, the results showed 97% sensitivity, 69% specificity and 83% accuracy from the experiment. Thus, this system fulfilled the real-Time working condition integrating (IoT) as accordingly. Institute of Electrical and Electronics Engineers Inc. 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39410/1/Real-Time%20Threshold-Based%20Fall%20Detection%20System%20Using%20Wearable%20IoT.pdf pdf en http://umpir.ump.edu.my/id/eprint/39410/2/Real-time%20threshold-based%20fall%20detection%20system%20using%20wearable%20IoT_ABS.pdf Nur Izdihar, Muhd Amir and Rudzidatul Akmam, Dziyauddin and Norliza, Mohamed and Nor Syahidatul Nadiah, Ismail and Nor Saradatul Akmar, Zulkifli and Norashidah, Md Din (2022) Real-time threshold-based fall detection system using wearable IoT. In: 4th International Conference on Smart Sensors and Application: Digitalization for Societal Well-Being, ICSSA 2022, 26-28 July 2022 , Kuala Lumpur. pp. 173-178. (182554). ISBN 978-166549981-1 https://doi.org/10.1109/ICSSA54161.2022.9870974
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Nur Izdihar, Muhd Amir
Rudzidatul Akmam, Dziyauddin
Norliza, Mohamed
Nor Syahidatul Nadiah, Ismail
Nor Saradatul Akmar, Zulkifli
Norashidah, Md Din
Real-time threshold-based fall detection system using wearable IoT
description This paper presents a Real-Time Fall Detection System (FDS) in the form of a wearable device integrating an ADXL335 accelerometer as a fall detection sensor, and classify the falling condition based on the threshold method. This system detects the wearer's movements and analyses the result in binary output conditions of 'Fall' for any fall occurrence or 'Normal' for other activities. The transmitter or FDS-Tx which is attached to the user's garment will constantly transmit data reading to the receiver or FDS-Rx via XBee module for data analysis. Raspberry Pi as the processor in FDS-Rx provides computational resources for immediate output analysis, by using threshold method, the computed results are sent to the cloud utilizing the Wi-Fi to display the user's condition on the authority's dashboard for further action. The working conditions of the systems are validated through an experiment of 10 volunteers whose perform several activities including fall events. Based on the threshold proposed, the results showed 97% sensitivity, 69% specificity and 83% accuracy from the experiment. Thus, this system fulfilled the real-Time working condition integrating (IoT) as accordingly.
format Conference or Workshop Item
author Nur Izdihar, Muhd Amir
Rudzidatul Akmam, Dziyauddin
Norliza, Mohamed
Nor Syahidatul Nadiah, Ismail
Nor Saradatul Akmar, Zulkifli
Norashidah, Md Din
author_facet Nur Izdihar, Muhd Amir
Rudzidatul Akmam, Dziyauddin
Norliza, Mohamed
Nor Syahidatul Nadiah, Ismail
Nor Saradatul Akmar, Zulkifli
Norashidah, Md Din
author_sort Nur Izdihar, Muhd Amir
title Real-time threshold-based fall detection system using wearable IoT
title_short Real-time threshold-based fall detection system using wearable IoT
title_full Real-time threshold-based fall detection system using wearable IoT
title_fullStr Real-time threshold-based fall detection system using wearable IoT
title_full_unstemmed Real-time threshold-based fall detection system using wearable IoT
title_sort real-time threshold-based fall detection system using wearable iot
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/39410/1/Real-Time%20Threshold-Based%20Fall%20Detection%20System%20Using%20Wearable%20IoT.pdf
http://umpir.ump.edu.my/id/eprint/39410/2/Real-time%20threshold-based%20fall%20detection%20system%20using%20wearable%20IoT_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39410/
https://doi.org/10.1109/ICSSA54161.2022.9870974
_version_ 1822923871676792832
score 13.235362

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