Implementation of data analytics and generation of algorithms for non-intrusive healthcare monitoring system of vulnerable elderlies
Over the years, Singapore has experienced a demographic shift of an overwhelming aging population. Due to higher life expectancy rates and lower birth rates, the repercussions on the country’s healthcare needs are more profound as the rapidly aging population proves to be a national concern. Vulnera...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/159174 |
| _version_ | 1811687689911533568 |
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| author | Tan, Brennon Joo Liang |
| author2 | Ng Teng Yong |
| author_facet | Ng Teng Yong Tan, Brennon Joo Liang |
| author_sort | Tan, Brennon Joo Liang |
| collection | NTU |
| description | Over the years, Singapore has experienced a demographic shift of an overwhelming aging population. Due to higher life expectancy rates and lower birth rates, the repercussions on the country’s healthcare needs are more profound as the rapidly aging population proves to be a national concern. Vulnerable elderlies who live alone and have little to no contact with healthcare workers may be exposed to underlying hazards such as falls and certain personal health complications. This would be challenging for them to contact emergency services if an incident occurs. Additionally, the recent pandemic has placed an enormous strain on the entire healthcare system, and coupling it with the shortage of staff, could potentially lead to slower response times when there is an emergency. To aid this problem, a non-intrusive means of monitoring the vulnerable elderly with a 3-Dimensional (3D) solid-state Light Detection and Ranging (LiDAR) sensor is used to detect falls and track the day-to-day activity level of the individual in real space and time. As the world moves into the 4th industrial revolution, LiDAR sensors have seen enhanced usage in numerous automotive and healthcare industries due to their limitless application. The focus of this project implements this 3D solid-state LiDAR combined with the usage of the Robot Operating System (ROS), Point Cloud Libraries (PCL), and a Raspberry Pi 4 (Miniature Computer), to generate reliable algorithms for fall detection and object tracking coupled with exploring real-time programming of the surrounding environment. |
| first_indexed | 2024-10-01T05:20:19Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/159174 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:20:19Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1591742023-03-04T20:13:19Z Implementation of data analytics and generation of algorithms for non-intrusive healthcare monitoring system of vulnerable elderlies Tan, Brennon Joo Liang Ng Teng Yong School of Mechanical and Aerospace Engineering Government Technology Agency (GovTech) MTYNg@ntu.edu.sg Engineering::Mechanical engineering::Assistive technology Over the years, Singapore has experienced a demographic shift of an overwhelming aging population. Due to higher life expectancy rates and lower birth rates, the repercussions on the country’s healthcare needs are more profound as the rapidly aging population proves to be a national concern. Vulnerable elderlies who live alone and have little to no contact with healthcare workers may be exposed to underlying hazards such as falls and certain personal health complications. This would be challenging for them to contact emergency services if an incident occurs. Additionally, the recent pandemic has placed an enormous strain on the entire healthcare system, and coupling it with the shortage of staff, could potentially lead to slower response times when there is an emergency. To aid this problem, a non-intrusive means of monitoring the vulnerable elderly with a 3-Dimensional (3D) solid-state Light Detection and Ranging (LiDAR) sensor is used to detect falls and track the day-to-day activity level of the individual in real space and time. As the world moves into the 4th industrial revolution, LiDAR sensors have seen enhanced usage in numerous automotive and healthcare industries due to their limitless application. The focus of this project implements this 3D solid-state LiDAR combined with the usage of the Robot Operating System (ROS), Point Cloud Libraries (PCL), and a Raspberry Pi 4 (Miniature Computer), to generate reliable algorithms for fall detection and object tracking coupled with exploring real-time programming of the surrounding environment. Bachelor of Engineering (Mechanical Engineering) 2022-06-11T11:01:39Z 2022-06-11T11:01:39Z 2022 Final Year Project (FYP) Tan, B. J. L. (2022). Implementation of data analytics and generation of algorithms for non-intrusive healthcare monitoring system of vulnerable elderlies. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/159174 https://hdl.handle.net/10356/159174 en A230 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Mechanical engineering::Assistive technology Tan, Brennon Joo Liang Implementation of data analytics and generation of algorithms for non-intrusive healthcare monitoring system of vulnerable elderlies |
| title | Implementation of data analytics and generation of algorithms for non-intrusive healthcare monitoring system of vulnerable elderlies |
| title_full | Implementation of data analytics and generation of algorithms for non-intrusive healthcare monitoring system of vulnerable elderlies |
| title_fullStr | Implementation of data analytics and generation of algorithms for non-intrusive healthcare monitoring system of vulnerable elderlies |
| title_full_unstemmed | Implementation of data analytics and generation of algorithms for non-intrusive healthcare monitoring system of vulnerable elderlies |
| title_short | Implementation of data analytics and generation of algorithms for non-intrusive healthcare monitoring system of vulnerable elderlies |
| title_sort | implementation of data analytics and generation of algorithms for non intrusive healthcare monitoring system of vulnerable elderlies |
| topic | Engineering::Mechanical engineering::Assistive technology |
| url | https://hdl.handle.net/10356/159174 |
| work_keys_str_mv | AT tanbrennonjooliang implementationofdataanalyticsandgenerationofalgorithmsfornonintrusivehealthcaremonitoringsystemofvulnerableelderlies |