Design and Development of The Expert System for Prediction of Tennis Elbow Injury using an Artificial Intelligence Aprrocah

dc.contributor.guidePatel H K
dc.coverage.spatial
dc.creator.researcherPatel, Heena
dc.date.accessioned2025-10-09T10:46:43Z
dc.date.available2025-10-09T10:46:43Z
dc.date.awarded2025
dc.date.completed2025
dc.date.registered2020
dc.description.abstractv newlineAbstract newlineTennis Elbow, or lateral epicondylitis, is a prevalent musculoskeletal condition characterized newlineby pain and tenderness on the outer aspect of the elbow, commonly afflicting athletes newlineengaged in racket sports. Despite its name, Tennis Elbow extends beyond tennis players, newlineaffecting individuals across various activities involving repetitive arm motions. newlineUnderstanding the intricacies of this injury necessitates a thorough exploration of its newlinemultifactorial nature. Biomechanical factors such as grip strength and wrist extension, along newlinewith individual characteristics like age and training history, contribute to its etiology. newlineAdditionally, anatomical considerations and environmental factors, including playing newlinesurface and equipment, influence the risk and severity of Tennis Elbow. By unraveling these newlineparameters comprehensively, I have tried to discern their collective impact on the onset and newlineprogression of the condition. Delving deeper into the primary causes of Tennis Elbow and newlineanalyzing the effects of various parameters reveals a complex interplay of factors. While the newlineinjury stems from repetitive stress on the forearm extensor tendons, its manifestation and newlinetrajectory are influenced by an array of determinants. Research efforts must scrutinize how newlinethese parameters modulate injury risk across different phases, from initial symptoms to newlinechronicity and treatment response. By deciphering these causal mechanisms, researchers can newlinedevise targeted interventions to mitigate the impact of Tennis Elbow and optimize patient newlineoutcomes. The advancement of an expert system through an Artificial Intelligence (AI) newlineapproach offers a promising avenue for revolutionizing Tennis Elbow management. Expert newlinesystems, empowered by AI techniques such as machine learning and knowledge newlinerepresentation, have the capacity to replicate the decision-making abilities of human experts newlinein the realm of injury prevention and rehabilitation. By assimilating vast datasets newlineencompassing parameters relevant to Tennis Elbow injury, these systems can discern
dc.description.note
dc.format.accompanyingmaterialDVD
dc.format.dimensions
dc.format.extent
dc.identifier.researcherid0000-0002-6346-481X
dc.identifier.urihttp://hdl.handle.net/10603/667385
dc.languageEnglish
dc.publisher.institutionInstitute of Technology
dc.publisher.placeAhmedabad
dc.publisher.universityNirma University
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordArtificial Intelligence Aprrocah
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordInstruments and Instrumentation
dc.subject.keywordPrediction of Tennis Elbow Injury
dc.titleDesign and Development of The Expert System for Prediction of Tennis Elbow Injury using an Artificial Intelligence Aprrocah
dc.title.alternativeDesign and Development of The Expert System for Prediction of Tennis Elbow Injury using an Artificial Intelligence Aprrocah
dc.type.degreePh.D.

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