Predicting Knee Joint Contact Force Peaks During Gait Using a Video Camera or Wearable Sensors.

ABSTRACT:

Purpose

Estimating loading of the knee joint may be helpful in managing degenerative joint diseases. Contemporary methods to estimate loading involve calculating knee joint contact forces using musculoskeletal modeling and simulation from motion capture (MOCAP) data, which must be collected in a specialized environment and analyzed by a trained expert. To make the estimation of knee joint loading more accessible, simple input predictors should be used for predicting knee joint loading using artificial neural networks.

Methods

We trained feedforward artificial neural networks (ANNs) to predict knee joint loading peaks from the mass, height, age, sex, walking speed, and knee flexion angle (KFA) of subjects using their existing MOCAP data. We also collected an independent MOCAP

SUBMITTER: Lavikainen J 

PROVIDER: S-EPMC11561138 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature