Resilience Aspects in Distributed Wireless Electroencephalographic Sampling

01/04/2022
by   R. Natarov, et al.
0

Resilience aspects of remote electroencephalography sampling are considered. The possibility to use motion sensors data and measurement of industrial power network interference for detection of failed sampling channels is demonstrated. No significant correlation between signals of failed channels and motion sensors data is shown. Level of 50 Hz spectral component from failed channels significantly differs from level of 50 Hz component of normally operating channel. Conclusions about application of these results for increasing resilience of electroencephalography sampling is made.

READ FULL TEXT
research
07/21/2021

Pushing the Limits: Resilience Testing for Mission-Critical Machine-Type Communication

Interdisciplinary application fields, such as automotive, industrial app...
research
10/24/2019

Resilience for Landslide Geohazards and Promoting Strategies in the Three Gorges Reservoir Area

Recently, resilience is increasingly used as a concept for understanding...
research
06/04/2021

Over-the-Air Computation via Broadband Channels

Over-the-air computation (AirComp) has been recognized as a low-latency ...
research
10/28/2021

The Optimal Error Resilience of Interactive Communication Over Binary Channels

In interactive coding, Alice and Bob wish to compute some function f of ...
research
10/12/2021

Remote Anomaly Detection in Industry 4.0 Using Resource-Constrained Devices

A central use case for the Internet of Things (IoT) is the adoption of s...
research
01/26/2021

Interference Alignment Using Reaction in Molecular Interference Channels

Interference alignment (IA) is a promising scheme to increase the throug...
research
02/16/2018

Improving Power Grid Resilience Through Predictive Outage Estimation

In this paper, in an attempt to improve power grid resilience, a machine...

Please sign up or login with your details

Forgot password? Click here to reset