Simon Föll, Martin Maritsch, Federica Spinola, Varun Mishra, Filipe Barata, Tobias Kowatsch, Elgar Fleisch, Felix Wortmann
BACKGROUND AND OBJECTIVE: Researchers use wearable sensing data and machine learning (ML) models to predict various health and behavioral outcomes. However, sensor data from commercial wearables are prone to noise, missing, or artifacts. Even with the recent interest in deploying commercial wearables for long-term studies, there does not exist a standardized way to process the raw sensor data and researchers often use highly specific functions to preprocess, clean, normalize, and compute features...
November 2021: Computer Methods and Programs in Biomedicine