Development of a Drawing Application to Evaluate Hand and Wrist Function: A Pilot Study.

Introduction: We developed a custom digital drawing application to assess hand function. We conducted an initial validation study of this technique to (1) assess which drawing features are associated with hand function, (2) differentiate patients from control subjects for both dominant and nondominant hands, and (3) assess the correlation of drawing features with previously validated patient-reported outcome measures (PROMs).

Methods: In this prospective study, participants were asked to draw shapes on an Apple iPad with a digital pen using a custom app.

A Systematic Review of Time Series Classification Techniques Used in Biomedical Applications.

Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, and ingestible and implantable sensors are increasingly used by individuals and clinicians to capture the health outcomes or behavioral and physiological characteristics of individuals. Time series classification (TSC) is very commonly used for modeling digital clinical measures. While deep learning models for TSC are very common and powerful, there exist some fundamental challenges.