Background. The purpose of this study is to review the current literature on knee joint biomechanical gait data analysis for knee\npathology classification. The review is prefaced by a presentation of the prerequisite knee joint biomechanics background and a\ndescription of biomechanical gait pattern recognition as a diagnostic tool. It is postfaced by discussions that highlight the\ncurrent research findings and future directions. Methods. The review is based on a literature search in PubMed, IEEE Xplore,\nScience Direct, and Google Scholar on April 2019. Inclusion criteria admitted articles, written in either English or French, on\nknee joint biomechanical gait data classification in general. We recorded the relevant information pertaining to the investigated\nknee joint pathologies, the participantsâ?? attributes, data acquisition, feature extraction, and selection used to represent the data,\nas well as the classification algorithms and validation of the results. Results. Thirty-one studies met the inclusion criteria for\nreview. Conclusions. The review reveals that the importance of medical applications of knee joint biomechanical gait data\nclassification and recent progress in data acquisition technology are fostering intense interest in the subject and giving a strong\nimpetus to research. The review also reveals that biomechanical data during locomotion carry essential information on knee\njoint conditions to infer an early diagnosis. This survey paper can serve as a useful informative reference for research on the subject.
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