Vision-based patient monitoring : a comprehensive review of algorithms and technologies
Vision-based monitoring for assisted living is gaining increasing attention, especially in multi-modal monitoring systems owing to the several advantages of vision-based sensors. In this paper, a detailed survey of some of the important vision-based patient monitoring applications is presented, name...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
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| Online Access: | https://hdl.handle.net/10356/141673 |
| _version_ | 1826114087213334528 |
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| author | Sathyanarayana, Supriya Satzoda, Ravi Kumar Sathyanarayana, Suchitra Thambipillai, Srikanthan |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Sathyanarayana, Supriya Satzoda, Ravi Kumar Sathyanarayana, Suchitra Thambipillai, Srikanthan |
| author_sort | Sathyanarayana, Supriya |
| collection | NTU |
| description | Vision-based monitoring for assisted living is gaining increasing attention, especially in multi-modal monitoring systems owing to the several advantages of vision-based sensors. In this paper, a detailed survey of some of the important vision-based patient monitoring applications is presented, namely (a) fall detection (b) action and activity monitoring (c) sleep monitoring (d) respiration and apnea monitoring (e) epilepsy monitoring (f) vital signs monitoring and (g) facial expression monitoring. The challenges and state-of-art technologies in each of these applications is presented. This is the first work to present such a comprehensive survey with the focus on a set of seven most common applications pertaining to patient monitoring. Potential future directions are presented while also considering practical large scale deployment of vision-based systems in patient monitoring. One of the important conclusions drawn is that rather than applying generic algorithms, use of the application context of patient monitoring can be a useful way to develop novel techniques that are robust and yet cost-effective. |
| first_indexed | 2024-10-01T03:33:46Z |
| format | Journal Article |
| id | ntu-10356/141673 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:33:46Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1416732020-06-10T02:29:19Z Vision-based patient monitoring : a comprehensive review of algorithms and technologies Sathyanarayana, Supriya Satzoda, Ravi Kumar Sathyanarayana, Suchitra Thambipillai, Srikanthan School of Computer Science and Engineering Engineering::Computer science and engineering Survey Patient Monitoring Vision-based monitoring for assisted living is gaining increasing attention, especially in multi-modal monitoring systems owing to the several advantages of vision-based sensors. In this paper, a detailed survey of some of the important vision-based patient monitoring applications is presented, namely (a) fall detection (b) action and activity monitoring (c) sleep monitoring (d) respiration and apnea monitoring (e) epilepsy monitoring (f) vital signs monitoring and (g) facial expression monitoring. The challenges and state-of-art technologies in each of these applications is presented. This is the first work to present such a comprehensive survey with the focus on a set of seven most common applications pertaining to patient monitoring. Potential future directions are presented while also considering practical large scale deployment of vision-based systems in patient monitoring. One of the important conclusions drawn is that rather than applying generic algorithms, use of the application context of patient monitoring can be a useful way to develop novel techniques that are robust and yet cost-effective. 2020-06-10T02:29:19Z 2020-06-10T02:29:19Z 2015 Journal Article Sathyanarayana, S., Satzoda, R. K., Sathyanarayana, S., & Thambipillai, S. (2018). Vision-based patient monitoring : a comprehensive review of algorithms and technologies. Journal of Ambient Intelligence and Humanized Computing, 9(2), 225-251. doi:10.1007/s12652-015-0328-1 1868-5137 https://hdl.handle.net/10356/141673 10.1007/s12652-015-0328-1 2-s2.0-85044944852 2 9 225 251 en Journal of Ambient Intelligence and Humanized Computing © 2015 Springer-Verlag Berlin Heidelberg. All rights reserved. |
| spellingShingle | Engineering::Computer science and engineering Survey Patient Monitoring Sathyanarayana, Supriya Satzoda, Ravi Kumar Sathyanarayana, Suchitra Thambipillai, Srikanthan Vision-based patient monitoring : a comprehensive review of algorithms and technologies |
| title | Vision-based patient monitoring : a comprehensive review of algorithms and technologies |
| title_full | Vision-based patient monitoring : a comprehensive review of algorithms and technologies |
| title_fullStr | Vision-based patient monitoring : a comprehensive review of algorithms and technologies |
| title_full_unstemmed | Vision-based patient monitoring : a comprehensive review of algorithms and technologies |
| title_short | Vision-based patient monitoring : a comprehensive review of algorithms and technologies |
| title_sort | vision based patient monitoring a comprehensive review of algorithms and technologies |
| topic | Engineering::Computer science and engineering Survey Patient Monitoring |
| url | https://hdl.handle.net/10356/141673 |
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