Multimodal Integration of Gait, Balance, and Infrared Thermography Enhances Machine-Learning Classification of Knee Osteoarthritis: A Cross-Sectional Study.

OBJECTIVE: To investigate whether combining gait, balance, and infrared thermography improves discrimination between individuals with knee osteoarthritis (KOA) and healthy controls (HC) compared with single-domain models. DESIGN: Cross-sectional diagnostic study with supervised machine-learning analysis using repeated 10 × 5 cross-validation and paired ROC comparisons. SETTING: Instrumented assessment at Research Center on Motor Activities (CRAM) University of Catania, in collaboration with the Orthopaedics and Traumatology and the Physical Medicine and Rehabilitation Units of AOU Policlinico "Rodolico - San Marco," University of Catania. PARTICIPANTS: Fifty-five adults aged 45 to 80 years were included: 28 participants with clinically and radiographically confirmed KOA and 27 HC. KOA severity was graded using the Kellgren-Lawrence scale. HC had no history of knee pain, injury, or surgery. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE(S): Spatiotemporal gait parameters, postural stability measures, knee surface temperatures, and classification performance of gait-only, balance-only, movement-only, thermal-only, and multimodal SVM models, assessed by area under the curve (AUC), sensitivity, and specificity. RESULTS: Compared with HC, KOA participants showed slower walking speed (adjusted p = 0.030), reduced gait symmetry (adjusted p = 0.018), and larger sway ellipse area, especially under eyes-closed conditions (adjusted p = 0.003). Thermography showed consistently higher temperatures in KOA, particularly in the lower popliteal fossa (31.11 ± 0.99°C). Among the top-10 models, the thermal-only model achieved perfect discrimination (AUC = 1.000), whereas the multimodal model also showed excellent performance (AUC = 0.988; sensitivity = 0.937; specificity = 0.887). Paired ROC comparisons showed that the multimodal model significantly outperformed gait-only, balance-only, and movement-only models, while not differing from the thermal-only model. CONCLUSIONS: KOA is characterized by concurrent gait, balance, and thermal alterations. Although thermography alone showed the highest discriminative performance in this sample, multimodal integration provided a broader and clinically coherent framework for KOA classification.