A masked-autoencoder foundation model for arbitrary multivariate wearable signals, using wavelet scalograms and channel-aware fusion, is shown to transfer to 18 health tasks with competitive average performance.
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Toward Foundation Model for Multivariate Wearable Sensing of Physiological Signals
A masked-autoencoder foundation model for arbitrary multivariate wearable signals, using wavelet scalograms and channel-aware fusion, is shown to transfer to 18 health tasks with competitive average performance.