###### 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 kinesography 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 (nl). 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 1 and nl 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. 3D kinematics; decision trees; knee osteoarthritis; physical exercises +
Footnote †: journal: Medicalrheumatologist) after a musculoskeletal evaluation that can be combined with an imaging assessment (X-ray). Radiographic examinations collect information on the integrity of knee structures but because they are performed in a static condition, they do not provide information on the knee's functional status. Although such examinations allow to assess the impact of an injury on anatomical structures, they do not provide clinicians with information to support whether a conservative treatment, such as physical exercises, should be prescribed or not. In this context, a dynamic functional evaluation of the knee provides valuable clinical information (e.g., misalignments during gait) [5]. This evaluation can be completed with a knee kinesography exam which measures the three-dimensional rotation angles (3D kinematics) during gait, allowing to identify mechanical biomarkers directly related to the progression of the disease and the patient's symptoms. This objective assessment allows clinicians to recommend personalized exercises targeting the previously identified mechanical biomarkers. This type of evaluation can easily be performed in a clinical setting using the KneeKGTM system (EMOVI Inc., Montreal, QC, Canada; Figure 1). This system consists of passive motion sensors fixed on the knee harness, an infrared motion capture system and a computer equipped with an acquisition software. The harness is fixed quasi-rigidly on the thigh and calf to measure tibial and femoral rotation [6]. Several studies have demonstrated the accuracy, validity and reproducibility of 3D knee movements measured with this technology [6; 7; 8]. Exercises are among the non-surgical treatment options with the most research evidence supporting their effectiveness [9]. Overall, they aim to strengthen muscles and improve flexibility and balance in order to alleviate symptoms and improve joint function [10]. However, the factors that could predict which patients would be more likely to respond to such a treatment have yet to be determined.