Inspired by the advancements in foundation models for language-vision modeling, we explore the utilization of transformers and large-scale pretraining on biosignals. In this study, our aim is to design a general-purpose architecture for biosignals that can be easily trained on multiple modalities and can be adapted to new modalities or tasks with ease.
The proposed model is designed with three key features: (i) A frequency-aware architecture that can efficiently identify local and global information from biosignals by leveraging global filters in the frequency space. (ii) A channel-independent…Apple Machine Learning Research