Anterior Cruciate Ligament Knee Injury Detection of Sports Persons using Machine Learning Techniques
Jaskaran Kaur1, Sandeep Sharma2
1Jaskaran Kaur*, Dept. of Computer Engineering and Technology, Guru Nanak Dev University, Amritsar, Punjab, India.
2Dr. Sandeep Sharma, Dept. of Computer Engineering and Technology, Guru Nanak Dev University, Amritsar, Punjab, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on April 10, 2020. | PP: 2189-2193 | Volume-9 Issue-6, April 2020. | Retrieval Number: F4194049620/2020©BEIESP | DOI: 10.35940/ijitee.F4194.049620
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: ACL is one of most common knee injury in sports person which increases as the participation in sports increases. People participating in basketball, football, hockey and athletics generally faces more weight bearing on hip, knee and ankle which is directly breaking of muscular tissues of ACL. After this it is mandatory to rehabilitate and back to the field for sport person at same pre-injury stage. But it requires mental and physical strength to recover from ACL tear and proper treatment needs health management. In a growing age of Information Technology the use of computer and its applications are extensively used in almost all areas. The main objective of this paper is to check the use of expert system or the use of any computerized equipment while diagnosis Anterior Cruciate Ligament injury. There are many techniques and machines to predict the knee injury grade like MRI but to check the accuracy level computer expert system Machine learning techniques are best for the results.
Keywords: Anterior Cruciate Ligament, Rehabilitation, Knee Injury, Expert System, Treatment.
Scope of the Article: Machine Learning