Please use this identifier to cite or link to this item:
http://repository.psa.edu.my/handle/123456789/3928
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | WAN NUR SAFIAH HANIS WAN MAMAT ZUKUNAIN | - |
dc.contributor.author | DR. SITI ANIZAH MUHAMED | - |
dc.date.accessioned | 2023-01-12T07:47:55Z | - |
dc.date.available | 2023-01-12T07:47:55Z | - |
dc.date.issued | 2022-07 | - |
dc.identifier.isbn | e-ISBN: 978-967-2258-97-1 | - |
dc.identifier.uri | http://repository.psa.edu.my/handle/123456789/3928 | - |
dc.description.abstract | Malaysia will become an ageing country by 2030. Data show that number of elders aged above 60 is increasing, while the percentage of young people aged 14 and below declined over the years. The rising number of elders results in socioeconomic issues including healthcare costs and social support from family members, community, and policymakers in terms of living arrangements. Especially for elders living alone, falling is a serious health problem, and it can lead to serious injuries such as hip fractures. When a person is immobilised due to an injury or unconsciousness, they are unable to aid themselves. Not being found for hours after a fall is fairly prevalent among the elderly who live alone, which dramatically raises the severity of fall-related injuries. Wearable fall detection systems have gotten a lot of interest in academia and business. Some monitoring gadgets, however, are difficult for older persons to wear or singularly only detect falls without monitoring vital signs. This project combines real-time vital signs monitoring system with a fall detection alert function by using wearable sensors and IoT technology. The system has proven able to detect all falls in FIVE (5) varieties of common falling patterns among the elderly | en_US |
dc.language.iso | en | en_US |
dc.publisher | POLITEKNIK TUANKU SYED SIRAJUDDIN (PTSS) | en_US |
dc.subject | fall detection | en_US |
dc.subject | variable sensor | en_US |
dc.subject | elderly people | en_US |
dc.subject | prevention | en_US |
dc.subject | automatic | en_US |
dc.subject | wireless | en_US |
dc.title | REAL-TIME FALL DETECTION AND VITAL SIGNS MONITORING SYSTEM FOR ELDERLY LIVING ALONE USING WEARABLE SENSOR | en_US |
dc.title.alternative | NCTS: 2nd National Conference on TVET Undergraduate Students | en_US |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
NCTS 2022 36.SAFIAH HANIS.pdf | 956.93 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.