Human Movement Is Poised to Drive Real-World Biomarkers

In this edition of NEJM AI, Ruth and colleagues evaluate a novel machine learning–enabled movement analysis of individuals with neuromuscular disorders. The authors demonstrate the technology's ability to extract disease-specific signatures of movement for two diseases that have historically resisted outcome measures, thus opening the door to objectively tracking progression and treatment response. This editorial contextualizes the article by Ruth et al. within the broader emerging ecosystem of movement as a biomarker and describes how hurdles to real-world use are now transitioning from technological to operational.