Development and Clinical Application of Digital Biomarkers for Sarcopenia

Sarcopenia, the age-related decline in skeletal muscle mass and function, has become a recognized disease entity with serious health implications. However, traditional diagnostic methods relying on handgrip strength, walking speed, and dual energy X-ray absorptiometry-based muscle mass assessment are limited by subjective components, irregular measurement intervals, and inability to capture muscle quality. This paper comprehensively reviews how digital biomarker technologies including smart watch, smart insoles, surface electromyography, and markerless motion analysis via OpenPose enable objective, continuous, real-world monitoring of sarcopenia. These technologies provide multidimensional insights into muscle strength, physical performance, daily activity patterns, coordination, and fatigue that single-modality assessments cannot achieve. Integration of medical imaging with artificial intelligence-based automatic segmentation models and machine learning-driven multimodal sensor fusion enables construction of personalized digital twin models for surgical planning and rehabilitation optimization. As the Asian Working Group for Sarcopenia 2025 expands the focus to include a lifecourse muscle health framework, there is growing clinical interest in digital biomarkers for their potential to detect early functional changes in real-life settings. While the integration of digital biomarkers as supplementary indicators for sarcopenia is a promising frontier, their formal inclusion in diagnostic criteria will require further standardization of protocols and large-scale clinical validation. While significant challenges remain including lack of standardized protocols, sensor interoperability issues, elderly patient usability concerns, and data security considerations, digital biomarkers hold the potential to transform sarcopenia management from episodic clinical assessment toward continuous, proactive, data-driven personalized care, provided that clinical validation is further established.