Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/443083
Title: | Quantitative Analysis Of Neck Muscle Fatigue |
Researcher: | Shakya, Hemlata |
Guide(s): | Sharma, Shiru and Sharma, Neeraj |
Keywords: | Biology and Biochemistry Endocrinology and Metabolism tissue Life Sciences |
University: | Indian Institute of Technology IIT (BHU), Varanasi |
Completed Date: | 2019 |
Abstract: | newline In the present scenario, most of the world s population is suffering from muscle newlinefatigue that affects muscle strength. Muscle fatigue is defined as a state of newlinephysical or mental exhaustion that can be triggered by stress, medication, newlineoverwork, or mental and physical illness. newlineThe current study deals with the analysis of neck muscle fatigue by using newlineEMG data of various subjects suffering from neck pain recorded via wireless newlinesensors. Neck pain is a common problem which is found in the people of all age newlinegroup, and it mainly occurs due to poor posture, anxiety, depression, muscle newlinestrain, sporting activities, and other stressful situations. The patients suffering newlinefrom neck pain-related problems are normally prescribed cervical traction therapy newlineby medical experts. newlineEMG signal contains sufficient information regarding the contraction and newlinefatigue status of the muscle. EMG data for various patients suffering from neck newlinepain with radiculopathy, neck pain without radiculopathy, and spondylosis pain newlinewere acquired using wireless EMG sensors during cervical traction therapy and newlineprocessed for muscle fatigue analysis. The sensors were placed on the neck newlinemuscles of the subjects for recording their EMG data. The data were recorded for newlineeach subject during their course of traction treatment. |
Pagination: | |
URI: | http://hdl.handle.net/10603/443083 |
Appears in Departments: | Biomedical Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title page.pdf | Attached File | 213.12 kB | Adobe PDF | View/Open |
02_prelimanarily page.pdf | 328.7 kB | Adobe PDF | View/Open | |
03_content page.pdf | 467.68 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 156.44 kB | Adobe PDF | View/Open | |
05_chapter 01.pdf | 295.38 kB | Adobe PDF | View/Open | |
06_chapter 02.pdf | 552.92 kB | Adobe PDF | View/Open | |
07_chapter 03.pdf | 812.53 kB | Adobe PDF | View/Open | |
08_chapter 04.pdf | 572.13 kB | Adobe PDF | View/Open | |
09_chapter 05.pdf | 419.81 kB | Adobe PDF | View/Open | |
10_chapter 06.pdf | 581.92 kB | Adobe PDF | View/Open | |
11_chapter 07.pdf | 180.08 kB | Adobe PDF | View/Open | |
12_annexures.pdf | 918.27 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 392.78 kB | Adobe PDF | View/Open |
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