Shodhganga : a reservoir of Indian theses @ INFLIBNET
The Shodhganga@INFLIBNET Centre provides a platform for research students to deposit their Ph.D. theses and make it available to the entire scholarly community in open access.
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/470475
| Title: | Data driven approaches to assess acute pain intensity level using physiological and behavioural data |
| Researcher: | Saranya Devi, S |
| Guide(s): | Brindha, D |
| Keywords: | Engineering and Technology Engineering Engineering Electrical and Electronic Acute pain Machine learning Biomedical signals |
| University: | Anna University |
| Completed Date: | 2021 |
| Pagination: | xxiii,154p. |
| URI: | http://hdl.handle.net/10603/470475 |
| Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 01_title.pdf | Attached File | 18.59 kB | Adobe PDF | View/Open |
| 02_prelim pages.pdf | 1.72 MB | Adobe PDF | View/Open | |
| 03_content.pdf | 101.71 kB | Adobe PDF | View/Open | |
| 04_abstract.pdf | 317.82 kB | Adobe PDF | View/Open | |
| 05_chapter 1.pdf | 417.01 kB | Adobe PDF | View/Open | |
| 06_chapter 2.pdf | 166.75 kB | Adobe PDF | View/Open | |
| 07_chapter 3.pdf | 917.17 kB | Adobe PDF | View/Open | |
| 08_chapter 4.pdf | 741.9 kB | Adobe PDF | View/Open | |
| 09_chapter 5.pdf | 316.25 kB | Adobe PDF | View/Open | |
| 10_chapter 6.pdf | 392.53 kB | Adobe PDF | View/Open | |
| 11_chapter 7.pdf | 271.86 kB | Adobe PDF | View/Open | |
| 12_annexures.pdf | 1.49 MB | Adobe PDF | View/Open | |
| 80_recommendation.pdf | 87.99 kB | Adobe PDF | View/Open |
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