Towards this, we present a real-time two-tiered framework called EMAP, which cross-correlates the input with all the EEG signals in our mega-database (a combination of multiple EEG datasets) at the cloud, while tracking the signal in real-time at the edge, to predict the occurrence of a neurological anomaly.
A real-time two-tiered framework called EMAP is presented, which cross-correlates the input with all the EEG signals in the authors' mega-database at the ...
EMAP: A Cloud-Edge Hybrid Framework for EEG Monitoring and Cross-Correlation Based Real-time Anomaly Prediction. -. Citation: Prabakaran, B. S., Garcia ...
Real-Time Systems. Conference Paper. EMAP: A Cloud-Edge Hybrid Framework for EEG Monitoring and Cross-Correlation Based Real-time Anomaly Prediction. July 2020.
Towards this, we present a real-time two-tiered framework called EMAP, which cross-correlates the input with all the EEG signals in our mega-database (a ...
Towards this, we present a real-time two-tiered framework called EMAP, which cross-correlates the input with all the EEG signals in our mega-database (a ...
EMAP: A Cloud-Edge Hybrid Framework for EEG Monitoring and. Cross-Correlation Based Real-time Anomaly Prediction. Bharath Srinivas Prabakaran∗,‡, Alberto ...
Nov 19, 2020 · Download EMAP for free. A Cloud-Edge Framework for EEG Monitoring and Real-time Anomaly Pred. We present a real-time two-tiered framework ...
Apr 25, 2024 · EMAP: A Cloud-Edge Hybrid Framework for EEG Monitoring and Cross-Correlation Based Real-time Anomaly Prediction. DAC 2020: 1-6. [i1]. view.
"EMAP: A Cloud-Edge Hybrid Framework for EEG Monitoring and Cross-Correlation Based Real-time Anomaly Prediction"; Talk: 2020 57th ACM/IEEE Design ...