Biokinetic Profiles in Patellofemoral Pain Patients During a Step-Down Task: An Unsupervised Machine Learning Approach.

ABSTRACT:

Background

There is a lack of consensus regarding the optimal identification of motion-based subgroups (biokinetic profiles) of patients with patellofemoral pain (PFP) to guide effective management strategies.

Purpose

To investigate different biokinetic profiles among patients with PFP during a step-down task and compare their clinical and physical characteristics.

Study design

Descriptive laboratory study.

Methods

A total of 49 patients with PFP had their 3-dimensional kinematics assessed during a step-down task using an optoelectronic system. The variables analyzed were trunk and lower limb joint angles. Self-organizing maps and K-means clustering techniques were used to identify distinct biokinetic profiles. Clinical characteristics compared among profiles w

SUBMITTER: Metsavaht L 

PROVIDER: S-EPMC12441261 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature