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

ABSTRACT:

Background

Knee osteoarthritis (KOA) is an irreversible degenerative disease that characterized by pain and abnormal gait. Radiography is typically used to detect KOA but has limitations. This study aimed to identify changes in plantar pressure that are associated with radiological knee osteoarthritis (ROA) and to validate them using machine learning algorithms.

Methods

This study included 92 participants with variable degrees of KOA. A modified Kellgren-Lawrence scale was used to classify participants into non-ROA and ROA groups. The total feature set included 210 dynamic plantar pressure features captured by a wearable in-shoe system as well as age, gender, height, weight, and body mass index. Filter and wrapper methods identified the optimal features, which were used to t

SUBMITTER: Li G 

PROVIDER: S-EPMC10988837 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature