Search Results for author:
Found 2 papers, 0 papers with code
End-To-End Prediction of Emotion From Heartbeat Data Collected by a Consumer Fitness Tracker
We present here a Bayesian deep learning model for end-to-end classification of emotional valence, using only the unimodal heartbeat time series collected by a consumer fitness tracker (Garmin V\'ivosmart 3).
A Bayesian Deep Learning Framework for End-To-End Prediction of Emotion from Heartbeat
However, in practice, collection of physiological data `in the wild' is currently limited to heartbeat time series of the kind generated by affordable wearable heart monitors.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
