Mentalligent SRS

8/13/2019 Mentalligent SRS

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GROUP : MENTALLIGENT

COMPANY : Minder Technology

STN YILDIRIM 1629419

BERK ESEROL 1534908

EVN ASLAN 1559921

REM GKE AYDIN 1550268

Course : CENG 490

Assistant : Levent BAYINDIR

2010

SOFTWARE

REQUIREMENTS

SPECIFICATIONfor

BRAINWAVE BASED

CONCENTRATION

ENHANCING AND

REHABILITATION SYSTEM


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Table of Contents1 INTRODUCTION .......................................................................................................................... 1

1.1 Problem Definition ......................................................................................................................... 1

1.2 Purpose .......................................................................................................................................... 1

1.3 Scope .............................................................................................................................................. 1

1.4 User and Literature Survey ............................................................................................................ 1

1.5 Definitions and Abbreviations ....................................................................................................... 1

1.6 References ..................................................................................................................................... 3

1.7 Overview ........................................................................................................................................ 3

2 Overall Description .................................................................................................................... 3

2.1 Product Perspective ....................................................................................................................... 4

2.2 Product Functions .......................................................................................................................... 6

2.3 Constraints, Assumptions and Dependencies ............................................................................... 9

3 SPECIFIC REQUIREMENTS ......................................................................................................... 10

3.1 Interface Requirements ............................................................................................................... 10

3.1.1 User Interfaces ..................................................................................................................... 10

3.1.2 Hardware Interfaces ............................................................................................................. 10

3.1.3 Software Interfaces .............................................................................................................. 10

3.2 Functional Requirements ............................................................................................................. 10

3.2.1 User Interface ....................................................................................................................... 10

3.2.2 Database Interface ............................................................................................................... 103.2.3 Game and AI ......................................................................................................................... 14

3.3 Non-functional Requirements ..................................................................................................... 17

3.3.1 Performance requirements .................................................................................................. 20

3.3.2 Design Constraints ............................................................................................................... 20

4 Data Model and Description ..................................................................................................... 21

4.1 Data Description .......................................................................................................................... 22

4.1.1 Data Objects ......................................................................................................................... 22

4.1.2 Relationships ........................................................................................................................ 23

4.1.3 Complete Data Model .......................................................................................................... 24

4.1.4 Data Dictionary ..................................................................................................................... 24

5 Behavioral Model and Description............................................................................................ 25

5.1 Description For Software Behavior .............................................................................................. 26

5.2 State Transition Diagrams ............................................................................................................ 27

6 PLANNING ............................................................................................................................... 27

6.1 Team Structure ............................................................................................................................ 27

6.2 Estimation (Basic Schedule) ......................................................................................................... 276.3 Process Model .............................................................................................................................. 30

7 CONCLUSION ........................................................................................................................... 30


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S o f t w a r e R e q u i r e m e n t S p e c i f i c a t i o n f o r B r a i n w a v e B a s e d C o n c e n t r a t i o n E n h a n c i n g 1

1 INTRODUCTION

1.1 Problem Definition

The main concern of this BCES is to measure the magnitude and frequency of users brainwaves by

aBCID, record them and monitor them while they are playing a game that we will create. By

observing these changes of brainwaves, users will be able to control their brainwaves and finally

enhance concentration.1.2 Purpose

This software requirements specification provides a complete description and constraints of BCES.1.3 Scope

This software system will be Concentration Enhancing and Rehabilitation Software for users of

almost any age. This system will be designed to help users to find out how to control their

brainwaves.

More specifically, this system is designed to help people to control their brainwaves and finally

enhance their concentration. At first, if they want, users will go through a training phase. While

training there is no score or rank for users. Users will just see how to concentrate and how

brainwave meter act according to concentration. Then they are going to play a game that we

designed. The games purpose will be to force users to gather their attention. Since the users willsee the representation of their beta brainwaves (brainwave meter) on the screen they will learn

how this act while they are focusing. Therefore they will learn how to concentrate not only while

playing the game but also in normal life. Finally they will be able to enhance their concentration.

1.4 User and Literature Survey

1.4.1 Literature Survey

In the late 1960's and 1970's it was learned that it was possible to recondition and retrain

brainwave patterns. Some of this work began with training to increase alpha brainwave activity to

increase relaxation, while other work originating at UCLA focused on uncontrolled epilepsy. This

brainwave training is called EEG biofeedback or neurofeedback. Brainwaves occur at various

frequencies. The classic names of these EEG bands are alpha, beta, theta and delta.

- Beta brainwaves are small, faster brainwaves associated with a state of mental, intellectual

activity and outwardly focused concentration.

Beta1focused concentration( 13 to 30Hz) (1330 cycles per second)Beta2alert stateBeta3very alert, vigilantBeta4Hyper vigilant

- Alpha brainwaves are slower and larger. They are associated with a state of relaxation and

basically represent the brain shifting into an idling gear, relaxed and a bit disengaged, waiting to

respond when needed. If someone merely close their eyes and begin picturing something


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peaceful, in less than half a minute there begins to be an increase in alpha brainwaves.Its

frequency is 8 Hz to 12Hz (8 to 12 cycles per second).

- Theta brainwaves generally represent a daydream-like,rather spacey state of mind that is

associated with mental inefficiency. At very slow levels, theta brainwave activity is a very relaxed

state, representing the twilight zone between waking and sleep.Its frequency is 4 Hz to 8 Hz (4 to 8cycles per second).

- Delta brainwaves are the slowest, highest amplitude (magnitude) brainwaves, and are what we

experience when we are asleep.Its frequency is 0.5 Hz to 4Hz (0.5 to 4 cycles per second).*2

Because the most effective brainwaves are alpha and beta according to the association level with

the mental activities, the data acquisition device technologies are especially developed for

extracting and catching them. Neurofeedback training is brainwave biofeedback. During typical

training, a couple of electrodes are placed on the scalp and one or two are usually put on theearlobes. Then, high-tech electronic equipment provides real-time, instantaneous audio and visual

feedback about your brainwave activity through these alpha and beta waves. So along the various

companies, there are some developed hardware as this electronic devices, which is connected to

the brain through a part of head as indicated before(brain skin or earlobes) to extract the

brainwave data and to visualize them for different psychological purposes. So in our project we

will try to extract these alpha and beta brainwaves as much accurate as we can, and accordingly

we will create some control mechanisms to use this resulting data. *3

1.4.2 Market Literature Survey

There are three existing products in the market. They are Mind Room, BioGraph Infinity Software

and Brain Masters. Mind Room, is mainly focused on cognitive development and stress

management for the individuals, evaluation of objective risk factors of stress-related work for

companies and athletes control over mind and body for the sportsmen.1

BioGraph Infinity Software, has been developed as a biofeedback and clinical tool. The programsmain abilities are to record accurate data, to track a users learning curve both within and acrossrecording sessions and to generate reliable reports.

2

Brain Masters projects application areas include clinical and personal biofeedback, peak-

performance, self-improvement, education, research, self-exploration, and brain-controlled

systems, in addition to games, art, sports, recreation, brain calisthenics, mental conditioning and

improvement, and virtual reality.3

In this project we will be focusing on enhancing concentration of users. Expected audience of our

final product will be people of almost any age, from child to adult, who wants to enhance their

concentration.

1http://mindroomsportsscience.com/attivita.php?id=4#neuro

2http://www.thoughttechnology.com/bioinf.htm

3http://www.brainmaster.com
https://123.writeboard.com/6udpvjeyn1ba740x#fn3https://123.writeboard.com/6udpvjeyn1ba740x#fn3https://123.writeboard.com/6udpvjeyn1ba740x#fn3https://123.writeboard.com/6udpvjeyn1ba740x#fn3


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1.5 Definitions and Abbreviations

SRS : Software Requirements SpecificationBCID : Brain Computer Interface DevicesBCES : Brainwave Based Concentration Enhancing and Rehabilitation Software

1.6 References*1 IEEE Std 830-1998: IEEE Recommended Practice for Software Requirements Specifications

*2 Cordyon D., (2006). What is Neurofeedback?, Utah School Of Medicine, International Society for

Neurofeedback & Research.

*3 Wolpow Jonathan, Birbaumer Niels, McFarland Dennis, Pfurtscheller Gert, Vaughan Theresa.

(2002). Braincomputer interfaces for communication and control. Laboratory of Nervous System

Disorders, Wadsworth Center, New York State Department of Health, State University of New

York, Institute of Medical Psychology and Behavioral Neurobiology, University of Tuebingen,

Department of Psychophysiology, University of Padova, Department of Medical Informatics,

Institute of Biomedical Engineering, Technical University of Graz.

1.7 Overview

This document contains two additional chapters. The first (Overall Description) is designed to

describe the general factors that affect the product and its requirements. It contains all the

functions performed by theBCES, constraints under which it is to operate, some assumptions

and dependencies about the system. The second chapter (Specific Requirements) of this

document is written primarily for designers to design a system to satisfy those requirements, and

testers to test that the system satisfies those requirements.2 Overall Description

In BCES, we will try to extract the brainwaves information of the user and by using that

information we will try to maximize the duration of concentration state of the user. The way that

we will use for this purpose is a computer game. In the game industry, there are many cognitive

games that focuses on developing concentration of the players in a specific given time. For

example a Nintendo DS game, Brain Age, is asking mathematics calculations to the player and the

time is counted. The littleness of the time is the key to get more score.4Similar to the these kind of

games, we will try to take the attention of the user and to make him/her be concentrated. So, in

the project the main factor that affect the product and its requirements are the brainwaves of theuser and the precisions of the transformation of the brainwaves from the BCID. Because if we can

not extract the brainwave information after applying same functions, the raw brainwave

information will be useless for the project and the rest of the operations in the software will be

meaningless. So, we will planning to get the brainwave information more accurately as possible as

we can.

In BCES, the whole system is composed of by two main parts. One of them is hardware, the other

one is software. At the fist stage, the user login the system and to get the brainwaves of the user

we need to have a Brain Computer Interface Device which will be provided by the company. In theprocess, after that we extract the brainwaves by the help of this device, by analyzing the features

4http://www.lumosity.com/brain-games/attention-games


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of different brainwaves(delta, alpha, theta, beta), the user will be asked to play the game

application that we will develop. While monitoring the brainwaves, through the levels of the

game, user will be wanted to concentrate very well to complete the level. In this process we

expect to see the changes in the brainwaves of the user in an effective way. As mentioned above,

the aim is to increase the Beta brainwaves which is observed at the concentration state. Because

the concentration of the user can be varied according to his gender, age, psychology and theenvironment, we will take these factors into account and will create a game in a way of getting

attention and focusing concentration of the user much more easily and quickly. Moreover, to

detect the brainwaves by the device correctly and to treat the user accordingly, there will be a

continuous literature survey in the whole process. The running mechanism of the software and so

the game will be explained in the following subsection.

2.1 Product Perspective

The software will have an interface ,including tab which are consist of start-up, calibration,

training, game and the analiysis(brain status with all the brainwaves). We think that if the brainstatus and the game are in the same interface at the same time, it can be a distractive factor for

the user while playing the game. Instead of this we will only place a Beta wave status bar beside

the game play window on the game tab. A sketch of the interface is as in the following.

Figure 1 - User Interface Sketch

The game we will have these main features;

- The main aim of the game will be feeding the animals(the black ones in the Figure), which are the

same kind and identical(size and color are the same) and continously moving, in the screen. After

feeding the animals there will be no change in the appearences of the animals. So the user should

concentrate on which animal did he/she feed before, which he/she didnt.


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- The number of fodder is equal to the number of animals on the screen. The user should feed

each animal only once. If not, the user have time punishment(the time, which begins from 0 and

counts from the beginning of the level, will increase suddenly).

- The animals can have different speed and move features. For example, some of them moves

quickly on the screen, some of them are slow and moves by jumping.

- According to the value in the Beta brainwave bar, we call it concentration-meter, the difficulty of

the next level will be decided. For example, if the users concentration level is very high during a

level, in the next level the number of animals to feed will more rapidly increase.

- The main aim of the game is feeding the moving animals by clicking over each of them and keep

this feeding time as short as possible, which means keeping the concentration state of the user as

long as possible.

The details of the game design and the relation between the Beta brainwaves and the level

concept will be explained on the Behavioral Model in the section 5.

Figure 2 - Block Diagram Of The Software

Considering the Figure 1, the mainframe of the software is theEEG Converter part. Following to

getting the raw data of the brainwaves via the device, the software will apply four transformations

to extract each type of the brainwaves with observable and distinct features. After doing

clustering, classification, and feature extraction, the user and we will be able to see the results on

the analysis interface. This monitoring part is so crucial that it shows the success of our

classification and feature extraction of brainwaves process. This is the first step that our software

will do.

The next step is to act according to the level of the Beta brainwaves of the user. The game

application we will introduce to the user aims to normalize the level of the concentration(which

means the level of the Beta brainwave) of the user if it is under the usual values. If it is already at

the normal range then the game application will adapt to increase the concentration level of the

user and see this increment on the monitoring interface. If the user are distracted, to take his

attention and make him concentrated a simple level will be asked to completed. Artificial

intelligence on the background will decide which difficulty level will be asked to be completed. In


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this process, we will continuously monitor the changes on the brainwaves of the user. At the end

of the game, the user is estimated to have more focused attention and be less distracted while

doing something.

2.2 Product Functions

The major functions that BCES will perform could be grouped under three sections; user interface,

database interface and game & AI. Besides of user interface and game&AI we will keep the

information of the users like, name, password, age and the history of brainwave analysis during

playing game. Because with the help of this database we will keep the track of the users

concentration enhancement day by day or weekly to get a feedback from the success of the these

trainings.

User Interface :

displayLogin()

This function is used to display the login interface at the beggining of the BCES. The user fills thename and password information.

displayCalibration()

This function is used to display the calibration screen when pressing the calibration tab. This

function ensures that the BCID is put on properly and the brainwaves can be extracted effectively.

manageInterfaceTabs()

This function manage the relations of the tabs which includes the individual interface properties.

getKeyboardMouseInput()

This function gets the external input from the user while playing the game or logging on the

system.


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getDeviceOutput()

This function gets the raw brainwave information from the BCID and as an output gives thetransformed brainwaves information to the AI of the game to decide accordingly.

Database Interface :

createNewUser()

This function creates a place in the database for a new user. The history information of the new

users will be assigned to null at first.

readUserLoginData()

This function reads the User information such as name, password, age, etc. from the database.

readUserHistoryData()

This function reads the brainwave analsis history of the user when needed to get a feedback day

by day or weekly to see whether the training has been succeeded or not.

deleteUserLoginData()

This function deletes the User name, password, age information from the database not to be login

to the system anymore.


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deleteUserHistoryData()

This function deletes the analysis results history of the user completely.

updateUserLogin()

This function updates the account information of the user when needed to be changed.

updateUserHistory()

This function updates the user brainwave analysis results during the game play in the database.

Game&AI:

analyzeUserRank()

This function decides the rank of the user after the game level finishes with respect to the gained

concentration experince during the play.

updateUserRank()

This function enables to update the rank attribute of the user in the database.


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decideNextLevel()

This function decides and creates the next level environment according to the game parameters.

playCurrentLevel()

This function enables the user to play the current game.

updateGameParameters()

This funtion updates the game parameters at the end of each level with respect to the cumulative

distribution of the concentration-meter results of the previous level.

analyzeUserStatus()

This funtion analyzes the Users brainwave status continuously from the beggining of the software.

And monitors it on the analysis tab in the interface.

2.3 Constraints, Assumptions and Dependencies

Because we will use a hardware, BCID, and because the extraction level of the brainwaves

depends on the users condition such as the thickness of the scalp, age, gender or etc., the

threshold value for each brainwaves is decided by taking this fact into consideration. The other

main standart that we will establish is to maintain the interfaces as simple as possible for the

users. Because the number of types of brainwaves is known as a fact, the number of brainwaves

types we will observe will be equal to that number. Moreover, the time of the training is limited.

Which means we will expect an improvement in the lack of concentration of the user in an specific

interval. The security of the database of brainwaves history of the users is important and for the

privacy rights of the users we will develop our database part as secure as possible.


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S o f t w a r e R e q u i r e m e n t S p e c i f i c a t i o n f o r B r a i n w a v e B a s e d C o n c e n t r a t i o n E n h a n c i n g 1 0

3 SPECIFIC REQUIREMENTS

3.1 Interface Requirements

3.1.1 User Interfaces

There will be just one user interface. Since software will be used by people from almost all age

groups it will be a user friendly interface. The colors will be hot colors that will attract people butwill not affect the eyes negatively. It will have big letters to increase readability. Looking at the content; it will have a window for the game, and at the left it will have a brainwave

meter that displays users beta brainwave output that we obtained and processed from raw datathat come from BCID. We will not be showing complete BCID brainwave output since it will cause

distraction of users but only beta brainwave output that we will use.3.1.2 Hardware Interfaces

Since BCID (Epoc neuroheadset) have its own hardware interface, we will be using just that

interface no additional interfaces.3.1.3 Software Interfaces

Windows operating system interface will be used through the project since the BCID that we are

going to use is compatible with Windows.There will be a simple database where users login

information and past information (history) will be kept. Since Epoc (BCID) is used its interface will

be used in background, but it will not take place in the user interface directly.3.2 Functional Requirements

There are twenty three main and sub functional parts in the product and these can be grouped

into three main groups such that user interface, database interface, game & AI.3.2.1 User InterfaceThese are the functional requirements for the user interface. There are five main functions that

the user interface must apply: displayLogin, displayCalibration,ManageInterfaceTabs,

getKeyboardMouseInput, getDeviceOutput.

3.2.1.1 displayLogin()1. Description

Multiple users can use BCES at different times. For each user, history is kept separated. Therefore,

each must log in to the system using their own user name and password. Thus the system can

determine the current user and use that information for database accesses. 2. Stimulus/Response Sequences

Data Flow:Basic Data Flow

1) User opens the application(start the software).2) Log in fields (user name and password) are appeared.3) User inserts his/her user name and password.

Alternative Data Flows1) Wrong user name and password


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1.1) User inserts wrong his/her user name or password.1.2) An error message is appeared to inform the user that asks to try again.

2) Exit2.1) User closes the application.

3) New user3.1) User clicks the new user button.3.2) New user form is displayed.

3. Functional Requirements

REQ-1: Users need access to the database, and open the log in page.

REQ-2: Users have an account to log in to the server.

3.2.1.2 displayCalibration()1. Description

A Calibration screen is required in order to make sure the user replaced the BCID properly. User

can not pass that screen until he/she wear the device and ready to use the program.2. Stimulus/Response SequencesData Flow:Basic Data Flow

1) User pass the log in screen and see the calibration screen.2) User applies the instructions and see that all receptors of BCID is enable.3) Start tab is opened.

Alternative Data Flows1) Receptors are not enable

1.1) User is informed about which receptor is disabled.2) Skip calibration

2.1) User is informed about that he/she can not use BCID related properties of the

application.3. Functional Requirements

REQ-1: User has access to the database, and opens the calibration page.REQ-2: Users have an account to log in to the server.REQ-3: User have BCID.


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3.2.1.3 manageInterfaceTabs()1. Description

The main screen of the application consists of five different tab segments which are Start, Game,

Training, Calibration, Analysis. This function controls the current tab alterations using the following

sub methods. Stimulus / response sequences and functional requirements of tab functions areidentical.

3.2.1.3.1 displayStart()1.1 Description

Function displays the Start tab. That tab contains various information about user previous

activities like user concentration rank and concentration experience.3.2.1.3.2 displayGame()1.2 DescriptionFunction displays the Game tab. That tab contains the currently available games for theapplication. These games works as separated modules.3.2.1.3.3 displayTraining()1.3 DescriptionFunction displays the Training tab. That tab contains a modular training application. It aims to

increase the coordination between the user and the BCID.3.2.1.3.4 displayCalibration()1.4 DescriptionFunction displays the Calibration tab. That tab contains the instruction and status information

for the calibration of BCID. If user takes off the device during the application is running, this

function is called.

3.2.1.3.5 displayAnalysis()1.5 DescriptionFunction displays the Analysis tab. That tab contains the information of previous user activities.

The graphical representation is used for the data. User can make customization on the range

and displaying content of the data charts.

2. Stimulus/Response SequencesData Flow:Basic Data Flow

1) After log in and calibration screens, user reaches the main screen that contains tab

manager.2) Tab manager allows the user to select the current tab.3) Each time changing the current tab, the corresponding display function is called.

Alternative Data Flows1) Take off the BCID


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3. Functional RequirementsREQ-1: The BCID is calibrated.REQ-2: A BCID input needed tab or application is active.

3.2.2 Database Interface

These are the functional requirements for the database interface. There are seven main functions

that the database interface of the product must apply: createNewUser, readUserLoginData,

readUserHistoryData, deleteUserLoginDatar, deleteUserHistoryData, updateUserLogin,

updateUserHistory.

3.2.2.1 createNewUser()1. Description

When a new user wants to create a new account, this method is activated. The user information is

taken by a short registration form and using it a new user account is initialized.


1) User click the add new user link in the log in screen.2) User fills the registration form.3) User clicks the confirmation button.

Alternative Data Flows1) Cancel registration

1.1) User can cancel the new user creation process by clicking cancel button in the form

page.2) Required fields are empty

2.1) A warning message is displayed to inform the user about empty form fields.3) Same user name exists

3.1) A warning message is displayed to inform the user to change his/her user name.3. Functional Requirements

REQ-1: User has access to the database.REQ-2: All required fields of form is filled.

REQ-3: Same user name does not exist in the database.


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3.2.2.2 readUserLoginData()1. Description

When the user data is needed for the log in process, this method is called. It obtains only user

name and password information from the database.2. Stimulus/Response Sequences

Data Flow:

Basic Data Flow

1) displayLogin function is called.2) User name and password fields are filled3) User clicks the log in button.

Alternative Data Flows1) User does not exist

1.1) A warning message is displayed to inform the user to try again or create a new account.3. Functional Requirements

REQ-1: User has access to the database.REQ-2: User name and password fields are filled.REQ-3: User has an account.

3.2.2.3 readUserHistoryData()

1. Description

When the user history data is needed to displayed, this method is called. It obtains partial or hole

data that belongs to the user according to its parameters.


1) A tab or application is called that need user history data.3. Functional Requirements

REQ-1: User has access to the database.REQ-2: User is logged in.REQ-3: A user history data related tab or application is running.


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3.2.2.4 deleteUserLoginData()1. Description

Function is called to data a user data completely. It is an irreversible operation. It also calls the

deleteUserHistoryData function.


1) User click to delete user button in the Analysis tab.2) A warning message is displayed to inform the user that this is an irreversible operation.

3. Functional RequirementsREQ-1: User has access to the database.REQ-2: User is logged in.

3.2.2.5 deleteUserHistoryData()

1. Description

Function is used when user needs to delete his/her previous data partially or completely. It is an

irreversible operation.


1) User opens the Analysis tab.2) User selects the data to delete.3) User clicks the delete button.

Alternative Data Flows1) deleteUserLoginData function is called.

1.1) If user is deleted using deleteUserLoginData, this function is called.3. Functional Requirements

REQ-1: User has access to the database.REQ-2: User is logged in.


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3.2.2.6 updateUserLogin()1. Description

Function is called when the user needs to update his/her account information. It is an irreversible

operation.

2. Stimulus/Response Sequences

Data Flow:Basic Data Flow

1) User click to update user account button in the Analysis tab.2) A warning message is displayed to inform the user that this is an irreversible operation.

3. Functional RequirementsREQ-1: User has access to the database.REQ-2: User is logged in.

3.2.2.7 updateUserHistory()1. Description

Function is called when a new data is generated by an application in the software. It is the main

function for games to record the data of the user.


1) A tab or application is called that generates user data.3. Functional Requirements

REQ-1: User has access to the database.REQ-2: User is logged in.REQ-3: A user history data related tab or application is running.

3.2.3 Game and AI

These are the functional requirements for the game and ai. There are six main functions that the

game and ai part of the product must apply: analyzeUserRank, updateUserRank, decideNextLevel,

playCurrentLevel, changeLevel, updateGameParameters, analyzeUserStatus.3.2.3.1 analyzeUserRank()1. Description

User rank is used in order to determine the initial difficulty of the games. This function converts

the current user rank information to the decision variables for initial game parameters.


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1) User starts a game.2) readUserHistoryData is called to obtain user rank data.

3. Functional RequirementsREQ-1: User has access to the database.REQ-2: User is logged in.REQ-3: Game tab is active.REQ-4: A game is running.

3.2.3.2 updateUserRank()1. Description

When a game level is completed, according to the game score, user gains experience points. If

experience points reach a specific point, user rank increases and this function is called.


1) User plays a game.2) User completes a level of that game.3) User concentration experience reaches a certain point.

3. Functional RequirementsREQ-1: User has access to the database.REQ-2: User is logged in.REQ-3: Game tab is active.REQ-4: A game level is completed.

3.2.3.3 decideNextLevel()1. Description

According to the previous concentration point of the user from the previous level of the currentgame, ai decides the parameters of the next level of the game and calls that function.


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1) User plays a game.2) User completes a level of that game.

3. Functional RequirementsREQ-1: User is logged in.REQ-2: Game tab is active.REQ-3: A game level is completed.

3.2.3.4 playCurrentLevel()1. Description

After deciding the next level of the current game, that function starts the level. It is called after the

decideNextLevel function.


1) User plays a game.2) User completes a level of that game or starts a new game.

3. Functional RequirementsREQ-1: User is logged in.REQ-2: Game tab is active.REQ-3: User starts a game or complete a game level.

3.2.3.5 updateGameParameters()1. Description

Game parameters determines the properties of the games current level. This function is calledafter decideNextLevel function in order to apply the decisions of the ai.


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1) User plays a game.2) User completes a level of that game or starts a new game.3) decideNextLevel is called.

3. Functional RequirementsREQ-1: User is logged in.REQ-2: Game tab is active.REQ-3: User starts a game or complete a game level.

3.2.3.6 analyzeUserStatus()1. Description

Function is called before starting a game or displaying an analyze result. The output of this

function is used as input data for ai decision function decideNextLevel.2. Stimulus/Response SequencesData Flow:Basic Data Flow

1) User opens Game tab.2) User starts a game.

Alternative Data Flows1) User opens Analyse tab and request status analyses.

3. Functional RequirementsREQ-1: User is logged in.REQ-2: A game is started or a status analyze is required.

3.3 Non-functional Requirements

3.3.1 Performance requirements

Simultaneous users will not be allowed on the same computer, therefore software is only

responsible for one user at a time. However since BCID will be used there are some time related

performance issues. Detailed explanation can be found on Design Constraints part below.


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3.3.2 Design Constraints

3.3.2.1 Software Standards

830-1998IEEE Recommended Practice for Software Requirements Specifications will be used in

this project.

3.3.2.2 Programming Languages

Object oriented programming languages will be used.

3.3.2.3 Hardware Constraints

Since the brain waves will be measured by aBCID and will be monitored on the computer, there

will be some constraints related to this device.

BCIDs system requirements is as follows5;

2.4 GHz Intel Pentium 4 processor (or equivalent).

Microsoft Windows XP with Service Pack 2, Windows Vista or Windows 7.

1GBRAM. 50MB available disk space.

One or two unusedUSB 2.0 ports (depending on the number of neuroheadsets you wish to use

simultaneously.

Also there are time related constraints of the BCID we will be using.Since some time passes while

device recognizes the waves when user first starts to think and some time passes when user stops

to think a bell shaped raw data is obtained from the device. Thus user have to think the same

thought for a while to get his/her brainwaves accurately monitored.3.3.2.4 Software System Attributes

3.3.2.4.1 Reliability:

The software is reliable except that it has some delays6:

- A delay while software records a thought (8 seconds)

- A short delay when activating cognitive output when user starts and stops thinking

3.3.2.4.2 Portability:

A version of Windows platform is needed for the BCID, therefore software is partially portable.3.3.2.4.3 Security:

Since the software will be used via a user interface the users will not be able to access the code of

software and modify it accidentally. Also since we are storing users past information in the

database, it must be secure enough to not let any person to access these information except that

user.

5

http://www.emotiv.com/store/hardware/299/

6http://www.emotiv.com/forum/messages/forum15/topic700/message4106/?phrase_id=143940#message4106


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4 Data Model and Description

This section describes information domain for the software.

4.1 Data Description

Data objects that will be managed/manipulated by the software are described in this section.The main data objects to be manipulated are the brainwaves of the user which are extracted by

te BCID. For monitoring(in analysis tab) and database parts we will use the brainwaves

informations. The managed data object is the level of Beta brainwaves. Because according to the

cumulative value of Beta brainwaves of the user, the AI of the game will decide the features of the

next level. So, the other managed data is the level of the game application. Moreover, we will

attach a rank attribute to the users. According to the time that the user completes each level, the

user will gain concentration experience. And after this concentration experiences reached the

decided upper bounds, the rank of the user will increase one by one. In other words, if the users

rank value is high then this means that this user has high ability of being in concentration state forlong time. In this situation, this high ranked user has completed the levels in shorter time and got

more scores in each played level by being concentrated during these levels not to make mistakes.

So the other minor data objects are the complete time, the score of each game level and

concentration level.

4.1.1 Data Objects

The main data objects in the BCES are;

Brainwaves :This data object has a name, representation(range, frequency, density etc.), unit and

range attributes. This data object can be inherited as Delta, Theta, Alpha and Beta brainwaves.

Game Levels : This data object has a name,representation, quantity and parameters(such as the

number of animals, the movement type of them, time to finish the level..) attributes.

- Game Level Completion Time : This sub-data object has range and quantity attributes.When the user consumes all the fodder, time will stop for that level. As mentioned

previously, the time starts counting from zero for every second and if the user feed theanimals that he has fed previously more seconds will be added to the current time. For

example while counting seconds one by one, if this situation occurs, an extra 5 seconds will

added to the time variable. If the time will be out of the previously decided range, for

example the user are not feeding the animals for a long time during the training, then level

will end and next level will be decided considering this lack of concentration stage.

- Game Level Score : This sub-data object has range and quantity attributes. While feedingthe animals that has not been fed before, an +10 points will be added to the score variable.

Feeding wrong animal that has been fed before will not contribute to the score.

User Data : This data object has a name, representation(including age and password variables) and

parameters(User Rank, User Concentration Experince) attributes.


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- User Rank :This sub-data object has only a name, quantity and range. This data object isassigned to the user after a certain number of concentration experience.

- User Concentration Experience : This sub-data object has range and quantity attributes. Atthe end of each level, the user will gain concentration experience according to the time

and score variables.

4.1.2 Relationships

Figure 3 - ERD of The Simple Data Objects


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4.1.3 Complete Data Model

Figure 4 - Complete Data Model

4.1.4 Data Dictionary

Data element 1 : Brainwaves

Name : Delta, Theta, Alpha, Beta

Representation : Class

Units/Format : Hz

Range :

- Delta Brainwaves : 0.5 to 4Hz, 0.5 to 4 cycles per second- Theta Brainwaves : 4 to 8 Hz , 4 to 8 cycles per second- Alpha Brainwaves : 8 to 12Hz ,8 to 12 cycles per second- Beta Brainwaves : 13 to 30Hz, 13 to 30 cycles per second


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Data element 2 : Game Level

Name : Level 1, Level 2, ... etc


Quantity : Up to 10 level(estimated)

Parameters :

- Number of animals- Randomly distributed movement types among the animals

Very slow Very fast Jumping Serpentine(like snakes)

- Maximum score(according to the number of animals)- Game Level Completion Time(starts from 0, up to a limit)- Game Level Score(starts from 0, up to (+10 points)* number of animals in that level)

Data element 3 : User Data

Name : UserName1, UserName2 ... etc


Parameters :

- User Rank (Rank1, Rank2..)- User Concentration Experince(100 experience / completion time of level)

5 Behavioral Model and Description

All behavioural models do is to describe the control structure of a system. This can be things like:

- Sequence of operations

- Object states

- and Object interactions

Furthermore, this modelling layer can also be called Dynamic Modelling. Because there is a flow in

the software from one state of the operation we can estimate the next step to deal with.


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5.1 Description For Software Behavior

As indicated in the 2th and 3th sections, there will be functions related to three different stages of

our software. By these functions we will react to the events in the software. The main events that

couse changing in states are the changes in the Beta brainwaves of the user. Also the other

affecting event is the change in game level. This correlative changes in the brainwave and gamelevel create the main flowing process of the BCES. Besides from these events, the actions to create

the database of the user can be thought as events. The resulting main states are; logging to the

system, starting BCID, extracting brainwaves, monitoring and analzing the brainwaves, updating

database, deciding the difficulty of the game level, changes the level of game and observing the

improvement in the concentration.

Brainwave Game level

The process between brainwave and game level runs as in the following.

- In a game level;o After feeding each animal on the screen, 3 seconds will pass to enable the animals

change their position and during this time interval the user can not feed the animals

and shoul wait and observe the animals to feed.

o The concentration-meter will show the amount of Beta Brainwaves of the user. Thisinformation will come from the BCID and some mentioned transformations

following to it.

oWhile playing the game, according to the moving number of animals in the screen,the user will be expected to concentrate on the level. Meanwhile, the value in

concentration-meter will change naturally. Because human can not be fully focused

in what he is doing all the time.

o While feeding the animals(correct or wrong), the time and score will be changingcontinuously. These time and score features of the levels makes the application

more resembled to the usual computer games.

o When the concentration-meter reach the top limit, the color of the remaning unfedanimals will be lightened for one second. This is a award for the concentrationed

users.o All the values of the Beta brainwaves during time of the level will be represented as

graphically(the descents and rises) in the analysis tab and be kept in the user

database for long-term feedback.

- Deciding next level;o The difficulty stage of the next level will be calculated according to the cumulative

average of the concentration-meter during the completion time of the previous

level. Because the level of the Beta brainwaves in the concentration-meter is

changing all the time.

o There will be a constant incrementation in the number of animals for the nextlevel(for example 2 animal more), but by taking into consideration of the


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cumulative average of concentration state of the user, this incrementation will be

additionally more.(instead of 2 animal, increase 5 animal)

o According to the completion time of previous level, the user will gain concentrationexperience. If this experience is enough to jump to next rank, the rank of the user

will be increased by one. So the completion time and concentration experience are

inversely correlated.

5.2 State Transition Diagrams

Figure 5 - State Transition Diagram of The Software

6 PLANNING

6.1 Team Structure

The team consists of four people from METU Computer Engineering Department seniors.

At the beginning of the project all of the members is responsible for doing literature search to

gather information that will help us through the project. Then we are going to modularize theproject in a way that it can be shared among team members.


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6.2 Estimation (Basic Schedule)

Below some expected due dates can be seen. These are extracted form the schedule of the

course.

- December 6, 2010: Requirement Analysis-

December 20, 2010: Initial Design Report- January 4, 2011: Detailed Design Report- January 11-23, 2011: Prototype Demo- May 27,2011: Final Product Demo

Besides, we will observe the time and effort cost estimation of the project by using COCOMO

model7.

FUNCTION POINTS

Parameters Simple Average Complex Count

User

Inputs

User Login 3

12User Registration 3

User Device Data 6

User

Outputs

Member Login Confirmation 4

29

Member Registration Confirmation 4

User Processed Data 7

User Game Level 7

User Rank 7

User

Inquiries

User Validation 3

13User Analysis History 6

User Information Update 4

Files Analysis History File 1525

User Account Information 10

External

Interfaces

User Database 10

41

Device Interface 10

Training Interface 7

Startup Interface 7

Calibration Interface 7

Count 120

7http://www.ceng.metu.edu.tr/~dogru/se3.pdf
http://www.ceng.metu.edu.tr/~dogru/se3.pdfhttp://www.ceng.metu.edu.tr/~dogru/se3.pdfhttp://www.ceng.metu.edu.tr/~dogru/se3.pdfhttp://www.ceng.metu.edu.tr/~dogru/se3.pdf


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COMPLEXITY ADJUSTMENT FACTOR

1 Reliable backup and recovery 5

2 Data communications 5

3 Distributed processing 3

4 Critical performance 4

5 Heavily utilized operational environment 3

6 On-line data entry 0

7 Input transactions over multiple screens (on-line) 0

8 Master file updates on-line 0

9 Complex input/output/file/inquiries 4

10 Complex internal processing 5

11 Reusable code design 4

12 Conversion and installation included in design 3

13 Multiple installations for different organizations 1

14 Design for facilitating change and ease of use 4

Total Fi 41

FP = CountTotal x [0.65 + 0.01 x Fi]

= 120* x [0.65 + 0.01 x 41]

= 127.2

We decided to use an Object Oriented Programming Language. Therefore according to FP to KLOC

transformation table;

FP / KLOC = 30

Project Size Estimation:

KLOC = FP / 30

= 127.2 / 30

= 4.24


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Project Effort Estimation:

Since we are a small group of people with good experience, our project is organic.

Effort = abx KLOCb

b

= 2.4 x 4.241.05

= 10.93 people / month

Project Schedule Estimation:

Time = cbx Effortd

b

= 2.5 x 10.930.38

= 6.2 months

Project Staffing Levels Estimation:

A small group of 4 people.

6.3 Process Model

Waterfall Model will be used through this project. In the coding part spiral model also can be used.7 CONCLUSION

In this project the requirements specified above will tried to be achieved at the end of the term.

However if we complete these specifications and still have time we will be designing more games

to meet users game taste. Namely more games will be provided so that users will have a chance to

choose a game from a set of games. Therefore they will enjoy more while they are enhancing their

concentration.

Mentalligent SRS

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