Beyond Surgical Precision: Innovating with Artificial Intelligence to Prevent WMSDs and Promote Global Health Equity

Abstract

Work-Related Musculoskeletal Disorders (WMSDs) represent a major occupational health issue among surgeons in the context of global health [1, 2]. Prolonged static postures, repetitive movements, and visual strain inherent in surgical work expose practitioners to neck, back, and upper limb pain, which can impair their quality of life and professional longevity [3]. A meta analysis estimated the prevalence of neck pain at 60% and that of back pain at 49% over a 12-month period among surgeons and interventional physicians [4]. More recently, a systematic review and meta-analysis reported a prevalence of WMSDs in the neck of 41% and in the back of 37.7% among surgeons not using video-assisted or robotic techniques [5]. In head and neck surgery, similar studies focused on otolaryngology estimated the prevalence of neck pain at 54% (95% CI: 40-67%) and back pain at 49% (95% CI: 40-59%) [6]. Furthermore, a study of 76 oral and maxillofacial surgeons identified the neck, shoulders, and lower back as among the most affected areas [7]. This research demonstrates that preventing WMSDs is a major challenge for the sustainability of surgical practices. Although these estimates vary depending on the population, assessment methods, and surgical settings, they nevertheless highlight the magnitude of the problem. In head and neck surgery, these findings reinforce the value of ergonomic innovations and artificial intelligence in identifying risky postures, supporting prevention, and protecting practitioners’ health.

Artificial Intelligence (AI) and technological innovation are opening up new avenues for transforming the prevention of WMSDs [8, 9]. Computer vision, machine learning, and deep learning algorithms enable the automation of posture recognition and the identification of ergonomic risk factors, thereby offering opportunities for more objective and continuous assessment of biomechanical stresses [10, 11]. Furthermore, integrating AI with wearable sensors - particularly inertial measurement units and electromyographic sensors - could facilitate the quantification of strain-inducing postures, repetitive movements, and muscle load in work settings [12, 13]. In the healthcare sector, wearable technologies hold potential for assessing healthcare professionals’ exposure to physical risk factors and guiding ergonomic interventions [13]. These approaches could complement existing innovations, such as surgical assistance systems and visualization devices, by contributing to the individualized adaptation of the operating environment. Nevertheless, despite promising results in posture recognition and risk assessment, the available data remains inconsistent, and validation under real-world conditions is still necessary. Longitudinal and interventional studies are therefore essential to determine whether these technologies can effectively reduce exposure to ergonomic risks, the incidence of WMSDs, and musculoskeletal symptoms [11].

Citation

Philippe Gorce. Beyond Surgical Precision: Innovating with Artificial Intelligence to Prevent WMSDs and Promote Global Health Equity. WebLog J Head Neck Surg. wjhns.2026.j2903. https://doi.org/10.5281/zenodo.23912495