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A Bed-Fall Notification System Using Pressure and Ultrasonic Sensors

A Bed-Fall Notification System Using Pressure and Ultrasonic Sensors

Original Research ArticleSep 22, 2021Vol. 22 No. 3 (2022) https://doi.org/10.55003/cast.2022.03.22.011

Abstract

Falls are a major cause of unintentional injury and mortality in the senior population. Therefore, early fall notification can prevent any undesirable damage. This paper aims to present a mobile electronic device-based bed-fall notification using the combination of six thin-film pressure sensors and six ultrasonic sensors. The proposed system monitors movements, detects a bed-fall, and sends an alarm to caregivers. The Finite State Machine (FSM) is used to classify 3 states of movement patterns: the lying, sitting, and falling states. The Internet of Things (IoT) system is adopted to transmit the movement status to the application on an android mobile device. The proposed bed-fall classification system yielded promising results for accuracy, sensitivity, and specificity: 86.67%, 73.33%, and 100%, respectively. In future work, the proposed system can be improved by increasing the number of thin-film pressure sensors, modifying circuit, and applying machine learning models. Accreditation of the system is expected to benefit young and elderly patients in nursing homes, hospitals, and residential areas.

Keywords: android mobile device; fall; finite state machine; ınternet of things; pressure and ultrasonic sensor

*Corresponding author: Tel.: (+66) 864400578

                                             E-mail: direks@g.swu.ac.th

How to Cite

Pornpreedawan, P. undefined. ., Puengsiricharoen, K. undefined. ., Tantisatirapong, S. undefined. ., Taweerutchana, R. undefined. ., & Sueaseenak*, D. undefined. . (2021). A Bed-Fall Notification System Using Pressure and Ultrasonic Sensors. CURRENT APPLIED SCIENCE AND TECHNOLOGY, DOI: 10.55003/cast.2022.03.22.011 (13 pages). https://doi.org/10.55003/cast.2022.03.22.011

References

  • United Nation, 2019. World Population Ageing 2019. [online] Available at: . https://www.un.org/en/development/desa/population/publications/pdf/ageing/WorldPopulationAgeing2019-Highlights.pdf
  • Department of Disease Control Ministry of Public Health, 2016. Forecast of Falls of the Elderly (Aged 60 and over) in Thailand Year 2017-2021. [online] Available at: . http://www.thaincd.com/2016/mission/documents-detail.php?id=12095&tid=&gid=1-027
  • Lu, C., Huang, J., Lan, Z. and Wang, Q., 2016. Bed exiting monitoring system with fall detection for the elderly living alone. Proceedings of 2016 IEEE International Conference on Advanced Robotics and Mechatronics (ICARM), Macau, China, August 18-20, 2016, pp. 59-64.
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  • Colón, C.J.P., Molina-Vicenty, I.L., Frontera-Rodríguez, M., García-Ferré, A., Rivera, B.P., Cintrón-Vélez, G. and Frontera-Rodríguez, S., 2018. Muscle and bone mass loss in the elderly population: Advances in diagnosis and treatment. Journal of Biomedicine, 3, 40-49.

Author Information

Pisut Pornpreedawan

Department of Biomedical Engineering, Srinakharinwirot University, Nakhon Nayok, Thailand

Kanut Puengsiricharoen

Department of Biomedical Engineering, Srinakharinwirot University, Nakhon Nayok, Thailand

Suchada Tantisatirapong

Department of Biomedical Engineering, Srinakharinwirot University, Nakhon Nayok, Thailand

Rutchaporn Taweerutchana

Faculty of Medicine, Srinakharinwirot University, Nakhonnayok, Thailand

Direk Sueaseenak*

Department of Biomedical Engineering, Srinakharinwirot University, Nakhon Nayok, Thailand

About this Article

Journal

Vol. 22 No. 3 (2022)

Type of Manuscript

Original Research Article

Keywords

android mobile device;
fall;
finite state machine;
ınternet of things;
pressure and ultrasonic sensor

Published

22 September 2021