著者

小橋 昌司 諸岡 孝俊 奥野 真起子 森本 雅和 吉矢 晋一 相河 聡

出版者

公益社団法人 日本生体医工学会

雑誌

生体医工学 (ISSN:1347443X)

巻号頁・発行日

vol.54Annual, no.26PM-Abstract, pp.S123-S123, 2016 (Released:2016-11-19)

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Total knee Arthroscopy (TKA) is an operation which replaces the damaged knee with an artificial knee implant. There are some kinds of TKA procedures, and various kinds of prosthesis. Thus, it becomes a tough work for surgeons to select an appropriate procedure and prosthesis for individual patients. This study proposes a prediction method of post-operative implanted knee kinematics. It predicts the post-operative kinematics from only pre-operative kinematics using a machine learning method with clinical big data. In 46 TKA subjects, the method predicts the post-operative anterior-posterior translation with a correlation coefficient of 0.77 and a root-mean-squared error of 0.7mm.