Abstract
CTS is the most common occupational disease. It is a form of median nerve compression and is caused by prolonged or repetitive motions of the wrist. CTS led to numbness and tingling sensation in the hand. CTS hinder activities of daily life and therefore diagnosis in good time is very important. The conventional diagnosis of CTS involves manual examination through electrophysiological testing. Manual diagnosis is not only time consuming but it is also not a proactive approach. With the recent advancement in computer vision, imaging, and soft computing techniques, predictive diagnosis of CTS has become an important research field. The aim of this research paper is to review the state of art of early detection and prediction of CTS. Major methods and algorithms used in this context are reviewed with their advantages and limitations. The research paper also points out the research gap and recommends direction for future research.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
