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

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

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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.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: ADXL 335; Fall Detection System; IoT; Wearable device
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Faculty/Division: College of Engineering
Faculty of Computing
Depositing User: Mr Muhamad Firdaus Janih@Jaini
Date Deposited: 28 Nov 2023 04:41
Last Modified: 28 Nov 2023 04:41
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