Editorial board editor-in-chief

SIGNAl VISuAlISATION SOFTwARE
FOR mINDSET mS-1000 ElECTROENCEPHAlOGRAPH
P
iotr
w
ierzgała
, g
rzegorz
M. w
óJcik
Institute of Computer Science, Maria Curie-Sklodowska University 
Marii Curie-Sklodowskiej Sq. 1, 20-031 Lublin, Poland
Abstract:
 
The paper presents EEG signal visualisation software designed for the Mindset MS-1000 EEG 16-channel device, 
manufactured by Nolan Computer Systems. The software is designed to work system independently and be accessible via web 
browsers. The presented application was developed in Adobe Flex technology with external Papervision3D library. It provides 
complete visualisation solutions such as navigable EEG chart or two separated 3D head models with applied EEG data. 
The goal and general idea
Our goal was to develop EEG visualisation project for Mindset 
MS-1000 device. The idea is to create usable, commonly avail
-
able and environment independent application. To provide best 
usability, EEG signal is visualised on a 3D head model that allows 
interaction with user’s control device. Taking into account the 
high signiicance of the Internet nowadays and diversiication 
of users operating systems, the main requirement for applica-
tion is to work in a web browser as well as desktop and to be 
completely independent of user’s operating system. Besides 
that, to ensure lexibility of development and decrease its costs 
the application is created only with tools that are open source 
and available free of charge.
Methods
The application was created in Adobe Flex [4-6] technology with 
external library Papervision3D [7-8]. 
Flex technology is used for development of Rich Internet 
Applications (RIA) which is the type of application that runs in 
a web browser and has capabilities comparable to desktop ap-
plications. One of the greatest RIA’s functionalities is executing 
application on the client’s side, what is signiicant for keeping 
high performance of servers and decreasing Internet connections 
trafic. As a consequence, once application is loaded it does not 
require to be refreshed after each user’s action, what is typical 
for HTML based web applications [9].
The cross-platform character of Flex applications is acquired 
by Flash Player, which is a virtual machine for all Flash technology
Introduction
In the Division of Complex Systems and Neurodynamics of 
Computer Science Institute of Maria Curie-Sklodowska University 
a software for EEG data visualisation is being developed. The 
software is designed for the Mindset MS-1000 EEG device, 
manufactured by Nolan Computer Systems [1]. 
This device contains a 16-channel analog ampliier, a 16-bit 
analogue-to-digital converter and a gathered data transmission 
trace. The device control and data interchange is operated by 
a SCSI interface. An appropriate SCSI commands set makes it 
possible to control the sampling rate value (64, 128, 256, 512 or 
1024 samples per second) and to begin and inish the process of 
data sampling [2-3]. According to the Nyquist frequency it is far 
enough to record human brain electrical activity that in natural 
conditions generates signal at frequency rate value from 1Hz 
to 100Hz.
Fig. 1.
Mindset 1000 EEG System main device

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Ima
ge
Pr
ocessing
84
Signal visualisation software for Mindset MS-1000 electroencephalograph
based applications. Flex applications are compiled to swf format 
iles, which are afterwards executed by proper Flash Player ver
-
sion installed for a speciic user’s operating system.
Flex sources are included with Flex SKD, which is provided 
free of charge. As a programming environment an education 
version of Flex Builder was chosen.
In order to display head model with applied EEG visualisation 
in three dimensions the Papervision3D library was used. Paper
-
vision3D is one of the most advanced and commonly advised 
3D libraries for Flash technology. It is capable of rendering 3D 
scene in a real time and it supports external 3D models saved 
in various popular formats [10]. 
As a 3D modelling tool needed to create 3D head model 
the Blender was chosen. It is a complex and up-to-date well 
documented tool with a strong support from Internet society as 
well as from publishers [11].
Application
The main application class BEAV (Brain Electrical Activity Vi-
sualisation), apart from initialising all other major classes, is 
responsible for reading ile with real EGG samples and putting 
them into array, which is the basic on which application compo-
nents operate [12].