A Concise Temporal Data Representation Model for Prediction in Biomedical Wearable Devices.

Predictive analytics and event forecasting using deep learning techniques require processing long-term historical data which is infeasible in low-power wearable devices. Such devices are constrained in memory and computational power, and are pushed to their limits by resource hungry deep neural networks. Current techniques either ignore historical data, or convert temporal sequences to pattern seq...