Identifying changes in dynamic plantar pressure associated with radiological knee osteoarthritis based on machine learning and wearable devices

This study used dynamic plantar pressure data and machine learning to identify mechanical biomarkers associated with radiological knee osteoarthritis (ROA), achieving 82.61% accuracy with the random forest model for distinguishing ROA from non-ROA.

Educational Objectives

Educational Aim:

To explore the use of dynamic plantar pressure measurements as mechanical biomarkers for diagnosing radiological knee osteoarthritis (ROA), and to validate these biomarkers using machine learning models for better disease detection and management.

Educational Outcomes:
Upon completion of this module practitioners should have a clear understanding of:

1. Plantar pressure changes
2. Recognizing machine learning's role
3. Identifying non-invasive biomarkers

Instructions for this Module

• Read the supplied reading material and complete the quiz that follows;
• You have three attempts to pass the quiz;
• The pass grade is 70%;
• You need to pass the quiz to claim your CPD certificate;
• Please click on the CPD certificate link below to claim your CPD certificate and to update your CPD Manager.

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