Continuous Assessment of Function and Disability via Mobile Sensing: Real-World Data-Driven Feasibility Study.

Our findings show the feasibility of using machine learning-based methods to assess functional health solely from passively sensed mobile data. The feature selection step provides a set of interpretable features for each domain, ensuring better explainability to the models' decisions-an important aspect in clinical practice.