Objective Artificial Intelligence-based Physiotherapeutic Assessment of Upper Cross Syndrome in Healthcare Professionals: A Cross-sectional Study
Sanjana Pammannavar, Santosh MetgudBackground:
Upper cross syndrome (UCS) is a postural disorder associated with muscle imbalance, altered cervical biomechanics, and neck-related disability. Healthcare professionals across multiple disciplines, including physicians, nurses, physiotherapists, dentists, pharmacists, and mental health professionals, are at increased risk due to sustained static postures and high ergonomic demands.
Objectives:
To determine the prevalence of UCS among healthcare professionals using artificial intelligence (AI)-based postural assessment and to examine associated functional disability, cervical range of motion (ROM), and muscle length alterations.
Methods:
This cross-sectional study included 184 healthcare professionals aged between 24 and 50 years. UCS was assessed using the AI-based Advanced Postural Evaluation and Correction System (APECS). Functional disability was evaluated using the Modified Oswestry Neck Disability Index (MONDI). Cervical ROM was measured using a universal goniometer. Muscle length was assessed using standardized clinical tests, including the pectoralis minor length test, along with goniometric evaluation of cervical movements. Group differences were analyzed using Chi-square and Kruskal–Wallis tests, and correlations were examined using Spearman’s rank correlation.
Results:
UCS prevalence ranged from 60.0% to 85.7% across healthcare professions and differed significantly by professional category (
Conclusion:
UCS is highly prevalent among healthcare professionals and is associated with objective postural deviations and functional impairment. AI-based postural assessment may support early detection and preventive strategies.