Digital biomarkers reveal fatigue across chronic diseases

A systematic review published in Digital Medicine (2025) evaluated how digital biomarkers, derived from wearable and mobile technologies, correlate with fatigue in chronic diseases. The analysis integrated data from 50 studies involving 5,573 participants across 15 conditions, including multiple sclerosis, rheumatoid arthritis, COPD, long COVID, cancer, and Parkinson’s disease.

The review identified physical activity metrics, particularly step count and moderate-to-vigorous physical activity (MVPA), as the most reliable indicators of fatigue severity. Individuals experiencing higher fatigue consistently demonstrated reduced movement, prolonged sedentary time, and lower activity intensity. Heart rate variability (HRV) emerged as another strong biomarker, reflecting autonomic dysfunction linked to fatigue across several diseases. Conversely, sleep parameters and gait features showed inconsistent associations, limited by small sample sizes and methodological diversity.

The authors emphasize that digital biomarkers offer objective, continuous, and ecologically valid tools for monitoring fatigue—addressing the limitations of self-reported assessments. Nevertheless, current evidence remains fragmented due to heterogeneous study designs, lack of longitudinal data, and limited cross-disease validation.

Integrating physical activity, HRV, and multimodal digital measures could revolutionize personalized fatigue management, enabling early detection of functional decline and tailored interventions for individuals living with chronic illness.