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...
| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2022
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| Online Access: | http://umpir.ump.edu.my/id/eprint/39410/ 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 |
| _version_ | 1848825761759232000 |
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| 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 |
| building | UMP Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T03:34:04Z |
| format | Conference or Workshop Item |
| id | ump-39410 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:34:04Z |
| publishDate | 2022 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-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 (Published) https://doi.org/10.1109/ICSSA54161.2022.9870974 |
| 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 |
| title | 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_short | Real-time threshold-based fall detection system using wearable IoT |
| title_sort | real-time threshold-based fall detection system using wearable iot |
| topic | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) |
| url | http://umpir.ump.edu.my/id/eprint/39410/ http://umpir.ump.edu.my/id/eprint/39410/ 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 |