Interpretable machine learning models for classifying low back pain status using functional physiological variables

摘要

Purpose To evaluate the predictive performance of statistical models which distinguishes different low back pain (LBP) sub-types and healthy controls, using as input predictors the time-varying signals of electromyographic and kinematic variables, collected during low-load lifting.