Abstract
More and more people like to practice taiji for different purposes. Taiji has been proposed as a treatment for the knee osteoarthritis. But there have always been different opinions that Taiji can cause knee injuries. The information on an individual participant is often incomplete. When complementary information is integrated, a better profile of a participant’s knee can be built to explore the tension. This paper aims to investigate the effects of Taiji on knees. We introduce a method for buildting a mapping among Taiji participants and their knee healthcare. It consists of three key components: the first component identifies Taiji participants’ unique behavioral patterns; the second component constructs features due to these behavioral patterns; and the third component exploys machine learning for effective computing. We formally define the problem and show that our method is effective. This study paves the way for analysis and mining knee osteoarthritis prevention and treatment. It also facilitates the creation of novel healthcare services.
Supported by Key Disciplines of Software Engineering of Shanghai Polytechnic University under Grant No. XXKZD1604.
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Yan, J., Wu, L., Zhang, S., Liang, H., Lin, Q. (2020). Effects of Taiji on Participants’ Knees: A Behavioral-Modeling Approach. In: Zhang, Z., Li, W., Du, DZ. (eds) Algorithmic Aspects in Information and Management. AAIM 2020. Lecture Notes in Computer Science(), vol 12290. Springer, Cham. https://doi.org/10.1007/978-3-030-57602-8_55
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DOI: https://doi.org/10.1007/978-3-030-57602-8_55
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