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السجلات المعروضة 1 -- 7 من 7
Multimodal deep learning approach for Joint EEG-EMG Data compression and classification
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
In this paper, we present a joint compression and classification approach of EEG and EMG signals using a deep learning approach. Specifically, we build our system based on the deep autoencoder architecture which is designed ...
Energy-cost-distortion optimization for delay-sensitive M-health applications
(
IEEE Computer Society
, 2015 , Conference Paper)
Mobile-health (m-health) systems leverage wireless and mobile communication technologies to promote new ways to acquire, process, transport, and secure the raw and processed medical data to provide the scalability needed ...
CAE Adaptive Compression, Transmission Energy and Cost Optimization for m-Health Systems
(
IEEE Computer Society
, 2021 , Conference Paper)
The rapid increase in the number of patients requiring constant monitoring inspires researchers to investigate the area of mobile health (m-Health) systems for intelligent and sustainable remote healthcare applications. ...
Deep learning and low rank dictionary model for mHealth data classification
(
Institute of Electrical and Electronics Engineers Inc.
, 2018 , Conference Paper)
In the context of mobile Health (mHealth) applications, data are prone to several sources of contamination which would lead to false interpretation and misleading classification results. In this paper, a robust deep learning ...
Optimizing Energy-Distortion Trade-off for Vital Signs Delivery in Mobile Health Applications
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Healthcare is considered a top priority worldwide, considering the swift increase in the number of chronic patients who require continuous monitoring. This motivates the researchers to develop scalable remote health ...
UAV-based Semi-Autonomous Data Acquisition and Classification
(
Institute of Electrical and Electronics Engineers Inc.
, 2018 , Conference Paper)
In the context of mobile Health (mHealth) applications, data are prone to several sources of contamination which would lead to false interpretation and misleading classification results. In this paper, a robust deep learning ...
A Simple Approach for Securing IoT Data Transmitted over Multi-RATs
(
Institute of Electrical and Electronics Engineers Inc.
, 2018 , Conference Paper)
In an mHealth remote patient monitoring scenario, usually control units/data aggregators receive data from the body area network (BAN) sensors then send it to the network or 'cloud'. The control unit would have to transmit ...