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3D kinematics and decision trees to predict the impact of a physical exercise program on knee osteoarthritis patients [r-libre/2846]

Mezghani, Marwa; Hagemeister, Nicola; Ouakrim, Youssef; Cagnin, Alix; Fuentes, Alexandre, & Mezghani, Neila (2021). 3D kinematics and decision trees to predict the impact of a physical exercise program on knee osteoarthritis patients. Applied Sciences, 11 (2), 834. https://doi.org/10.3390/app11020834

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Content : Published Version
License : Creative Commons Attribution.
Item Type: Journal Articles
Refereed: Yes
Status: Published
Abstract: Measuring knee biomechanics provides valuable clinical information for defining patient-specific treatment options, including patient-oriented physical exercise programs. It can be done by a knee kinesiography test measuring the three-dimensional rotation angles (3D kinematics) during walking, thus providing objective knowledge about knee function in dynamic and weight-bearing conditions. The purpose of this study was to assess whether 3D kinematics can be efficiently used to predict the impact of a physical exercise program on the condition of knee osteoarthritis (OA) patients. The prediction was based on 3D knee kinematic data, namely flexion/extension, adduction/abduction and external/internal rotation angles collected during a treadmill walking session at baseline. These measurements are quantifiable information suitable to develop automatic and objective methods for personalized computer-aided treatment systems. The dataset included 221 patients who followed a personalized therapeutic physical exercise program for 6 months and were then assigned to one of two classes, Improved condition (I) and not-Improved condition (nI). A 10% improvement in pain was needed at the 6-month follow-up compared to baseline to be in the improved group. The developed model was able to predict I and nI with 84.4% accuracy for men and 75.5% for women using a decision tree classifier trained with 3D knee kinematic data taken at baseline and a 10-fold validation procedure. The models showed that men with an impaired control of their varus thrust and a higher pain level at baseline, and women with a greater amplitude of internal tibia rotation were more likely to report improvements in their pain level after 6 months of exercises. Results support the effectiveness of decision trees and the relevance of 3D kinematic data to objectively predict knee OA patients’ response to a treatment consisting of a physical exercise program.
Official URL: https://www.mdpi.com/2076-3417/11/2/834
Depositor: Ayena, Johannes
Owner / Manager: Johannes Ayena
Deposited: 12 Jan 2023 21:28
Last Modified: 12 Jan 2023 21:28

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