Personalized Blood Pressure Estimation Using Photoplethysmography: A Transfer Learning Approach
In this paper, we present a personalized deep learning approach to estimate blood pressure (BP) using the photoplethysmogram (PPG) signal. We propose a hybrid neural network architecture consisting of convolutional, recurrent, and fully connected…
Motion Prediction and Pre-Rendering at the Edge to Enable Ultra-Low Latency Mobile 6DoF Experiences
As virtual reality (VR) applications become popular, the desire to enable high-quality, lightweight, and mobile VR can potentially be achieved by performing the VR rendering and encoding computations at the edge and streaming the rendered video to…
State of Energy Prediction in Renewable Energy-driven Mobile Edge Computing using CNN-LSTM Networks
Renewable energy (RE) is a promising solution to save grid power in mobile edge computing (MEC) systems and thus reducing the carbon footprints. However, to effectively operate the RE-based MEC system, a method for predicting the state of energy (…
