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http://hdl.handle.net/10603/424624
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DC Field | Value | Language |
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dc.coverage.spatial | Muscle strength evaluation and grading using surface electromyogram signals for functional assessment of the musculoskeletal system | |
dc.date.accessioned | 2022-12-12T08:23:39Z | - |
dc.date.available | 2022-12-12T08:23:39Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/424624 | - |
dc.description.abstract | Muscle strength evaluation and grading is an important assessment of the neuro-muscular functions followed routinely for pre-clinical diagnosis or for post rehabilitative evaluation of patients. Worldwide, about 150 million people suffer from musculoskeletal disorders, forming the fourth largest contributor of global burden of disease. High BMI and physical inactivity are identified as the major reasons contributing to chronic conditions like diabetes, cardiovascular and musculoskeletal disorders (IHME -WHO, 2017). Muscle strength is defined as the inherent ability of the muscle to develop tension and consequently produce force against a resistive load offered by a tester in one maximal effort. The current methods of muscle strength testing involve Manual muscle testing (MMT), or dynamometry based methods where, the former grades muscle strength on a 0-5 point (Medical research council, MRC) ordinal scale while the latter quantifies muscle strength in terms of measured force. MMT is highly subjective and assigning grades greater than 3 (4-, 4, 4+ and 5) involves identifying fine variations in strength based on the amount of resistive force offered. Dynamometers in turn require the need for a large normative database, since force measurements are absolute with no direct reference to strength and weakness of muscles. The ambiguity in current muscle strength measurement techniques has led to the interest of researchers and healthcare practitioners to look for a more standard and reliable technique to evaluate muscle strength. newline | |
dc.format.extent | xx,193p. | |
dc.language | English | |
dc.relation | p.172-192 | |
dc.rights | university | |
dc.title | Muscle strength evaluation and grading using surface electromyogram signals for functional assessment of the musculoskeletal system | |
dc.title.alternative | ||
dc.creator.researcher | Saranya S | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering Electrical and Electronic | |
dc.subject.keyword | Muscle Strength | |
dc.subject.keyword | Muscle Strength Evaluation | |
dc.subject.keyword | Electromyogram Signal | |
dc.subject.keyword | Musculoskeletal System | |
dc.description.note | ||
dc.contributor.guide | Poonguzhali S | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2021 | |
dc.date.awarded | 2021 | |
dc.format.dimensions | 21cm | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 79.06 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.88 MB | Adobe PDF | View/Open | |
03_content.pdf | 96.82 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 87.78 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 936.14 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 337.12 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 649.41 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.42 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 790.88 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 861.02 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 1.23 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 151.08 kB | Adobe PDF | View/Open |
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