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DC Field | Value | Language |
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dc.contributor.author | Pornpreedawan P. | |
dc.contributor.author | Puengsiricharoen K. | |
dc.contributor.author | Tantisatirapong S. | |
dc.contributor.author | Taweerutchana R. | |
dc.contributor.author | Sueaseenak D. | |
dc.date.accessioned | 2022-12-14T03:17:18Z | - |
dc.date.available | 2022-12-14T03:17:18Z | - |
dc.date.issued | 2022 | |
dc.identifier.issn | 25869396 | |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130491470&doi=10.55003%2fcast.2022.03.22.011&partnerID=40&md5=d08674f5245b0fd30dde78b73304163a | |
dc.identifier.uri | https://ir.swu.ac.th/jspui/handle/123456789/27413 | - |
dc.description.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. © 2022, King Mongkut's Institute of Technology Ladkrabang. All rights reserved. | |
dc.language | en | |
dc.publisher | King Mongkut's Institute of Technology Ladkrabang | |
dc.subject | android mobile device | |
dc.subject | fall | |
dc.subject | finite state machine | |
dc.subject | ınternet of things | |
dc.subject | pressure and ultrasonic sensor | |
dc.title | A Bed-Fall Notification System Using Pressure and Ultrasonic Sensors | |
dc.type | Article | |
dc.rights.holder | Scopus | |
dc.identifier.bibliograpycitation | Current Applied Science and Technology. Vol 22, No.3 (2022) | |
dc.identifier.doi | 10.55003/cast.2022.03.22.011 | |
Appears in Collections: | Scopus 2022 |
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