Developments of Pain Medicine with the Support of Clinical Engineering: A Narrative Review

Pain medicine is undergoing a paradigm shift, shaped not only by advances in biomedical research but also by the rapid integration of engineering innovations into clinical practice. The subjective nature of pain, long regarded as an obstacle to accurate diagnosis and effective treatment, is increasingly being addressed through objective, technology-driven approaches. Clinical engineering, a multidisciplinary field that merges biomedical engineering, informatics, and clinical sciences, has become a pivotal force in this transformation. Recent years have witnessed the emergence of sophisticated wearable sensors, capable of continuously tracking biomechanical, electrophysiological, and autonomic signals to capture the dynamic profile of pain in real-world contexts. In parallel, breakthroughs in neuroimaging and neurophysiological monitoring are unveiling objective biomarkers of nociceptive and neuropathic processes, providing unprecedented insights into the pathophysiology of pain chronification. On the therapeutic front, innovations in neuromodulation, including adaptive spinal cord stimulation, dorsal root ganglion stimulation, and non-invasive brain stimulation, have been empowered by closed-loop engineering designs and miniaturized devices that enhance precision and patient comfort. Rehabilitation robotics and nanotechnology-based drug delivery systems further expand the therapeutic armamentarium, integrating personalized feedback and targeted interventions. Beyond devices, artificial intelligence and machine learning now occupy a central role in predictive modeling and decision support, enabling clinicians to tailor interventions, anticipate treatment responses, and stratify risk with greater accuracy. This convergence of engineering and medicine is reshaping pain care into a more mechanistic, personalized, and proactive discipline. This review synthesizes these advances, while critically examining ethical, regulatory, and translational challenges that must be addressed to ensure equitable and sustainable implementation.