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dreamwithsom-blog · 5 years

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EEG Sensor Research

We started by researching what type of software there was available to make sure it was plausible to achieve our idea.

Recommended by: https://makeitmech.com/material-required-for-portable-eeg-system-development/

Multisim: Multisim is simulation software for various designs. This software is widely used because almost all required components are available in it. It is a tool used for testing various programs, simulations and complex electronics designs. It is also used for schematic designing and capture and for PCB (Printed Circuit Board) designing. We have used multisim for developing simulation circuits for Main Board and all other 3 stages of the circuit. PCB is also designed using the same software. - Has a free variation with less options

MATLAB: MATLAB is used for real time signal plotting. We used MATLAB as a tool for analyzing real time signal. AS the signal was quite noisy and fluctuating so we used MATLAB scope to plot the signal in real time. MATLAB is platform for mathematics and all types of functions and signal processing. WE can also use MATLAB for further signal processing. We used only the Simulink part of the MATLAB for Arduino board values. - Has a one month free trial avalible

Arduino IDE: The Arduino IDE is the software for Arduino development board. The Arduino IDE is used for writing Arduino Code for the EEG circuit. The Arduino code to identify the threshold values of ADC and averaging the EEG signal values. - the free arduino coding software

Recommended by: http://openeeg.sourceforge.net/buildeeg/software.php

BWView (http://uazu.net/bwview/)

This application, released as free software under the GNU GPL v2 for Linux and Windows, is designed for getting a rapid visual understanding of recorded brain-wave data. It uses FFT-accelerated convolution to do the analysis, which enables much greater flexiblity than using the traditional FFT-of-windowed-data approach. The frequency is plotted on a log scale, which is much better for viewing data that includes a wide range of frequencies. The window size is proportional to the wavelength at any frequency, so the convolution is effectively being done with a complex wavelet at various different scales. The ratio of window size to wavelength can be varied easily to allow different aspects of the data to be shown. Features:

Visually displays EEG data.

Platforms: Linux, Windows

This told us that there were many different Software that would be adequate to help us in our project. We then looked into existing headsets that use EEG:

When looking at these headsets it appeared that comfort and accuracy would be the main issue. Most headsets that exist currently are made of a hard plastic and are not comfortable to wear for extended periods of time.

Products such as Muse (https://choosemuse.com/) are used to monitor brainwaves to assist meditation and utilize a conductive rubber for added comfort. However, there is still a hard metal band for the sensors which would not be comfortable to sleep in.

Products like Emotiv (https://www.emotiv.com/) highlight the fact that the use of gels and liquids increases the accuracy of the readings. This means that electrodes constantly need replacing and also the added discomfort of liquids on the head during sleep makes this approach unlikely to be plausible for our idea. This means our readings will never be as accurate as they can be.

Even Sleep Shepherd (https://sleepshepherd.com/) a device already designed to sleep in looks bulky and has hard pieces that would make some sleeping positions highly uncomfortable. The use of soft materials however does show us that our idea is plausible.

Who did what?

Research: Steph

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