Application of functional regression in biomechanical assessment of neck disability: Selection of clinically relevant variables.

ABSTRACT:

Background

The Neck Disability Index (NDI) is widely used to assess neck pain-related disability. It is commonly combined with objective measures, particularly range of motion and peak velocity, but these variables usually show weak correlations with patient-reported outcomes. Functional data analysis (FDA) makes it possible to analyze complete kinematic waveforms and provides tools to identify relevant motion features most related to disability.

Objective

This study aimed to examine whether scalar-on-function regression of cervical angular velocity curves can predict NDI scores in patients with nonspecific neck pain and which motion variables and sub-phases contribute most to the prediction.

Methods

We analyzed 56 recordings from 28 patients, each paired with an NDI

SUBMITTER: Aragon-Basanta E 

PROVIDER: S-EPMC12919803 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature