transfall
Transfer Learning for Activity Recognition in Mobile Health
Ma, Yuchao, Campbell, Andrew T., Cook, Diane J., Lach, John, Patel, Shwetak N., Ploetz, Thomas, Sarrafzadeh, Majid, Spruijt-Metz, Donna, Ghasemzadeh, Hassan
While activity recognition from inertial sensors holds potential for mobile health, differences in sensing platforms and user movement patterns cause performance degradation. Aiming to address these challenges, we propose a transfer learning framework, TransFall, for sensor-based activity recognition. TransFall's design contains a two-tier data transformation, a label estimation layer, and a model generation layer to recognize activities for the new scenario. We validate TransFall analytically and empirically.