The evidence for biomechanical and physiological parameters as biomarkers to discriminate between individuals with and without non-specific neck pain using sensor devices: A systematic review with meta-analysis.

Abstract

Neck pain is among the most prevalent musculoskeletal conditions worldwide. The underlying cause mostly remains unidentified, classified as non-specific neck pain. Pain can alter movement patterns and physiological responses, suggesting that certain biomechanical and physiological changes may serve as objective biomarkers for non-specific neck pain. In recent years, growing interest in sensor technologies has enabled accurate and objective measurement of these changes. This is the first review to systematically summarise current evidence on the capability of biomechanical and physiological parameters, measured via sensors, to differentiate individuals with non-specific neck pain from asymptomatic controls, and evaluate their discriminative performance. Comprehensive searches of six databases (CINAHL, MEDLINE, EMBASE, AMED, IEEE Xplore, PEDro), grey literature, and reference lists (inception to August 20, 2025) yielded 53 observational studies for qualitative synthesis, with meta-analysis on 27. Meta-analysis indicates robust evidence linking non-specific neck pain with reduced neck range of motion, impaired joint position error, decreased step length and gait speed, reduced sway area, increased electromyographic activity of the sternocleidomastoid muscle, and reduced heart rate variability. Narrative findings reported altered neck movement speed, acceleration, and smoothness during functional tasks (e.g., reach and lifting). Classification studies showed high discriminative performance using machine learning and statistical techniques, with accuracies of 71.9-90%, sensitivities of 76.3-100%, and specificities of 77.6-90%, especially for gait and electromyography parameters. The findings highlight biomechanical and physiological alterations in non-specific neck pain that can serve as objective biomarkers. Clinically, these insights could offer support to enhance assessment and inform rehabilitation strategies. PERSPECTIVE: This comprehensive review synthesises current evidence on physiological and biomechanical parameters as biomarkers in non-specific neck pain. While these parameters show promise for pain classification, their utility as biomarkers requires further evaluation and validation of their discriminative power for improved assessment and inform rehabilitation strategies.