11.IJAEST-Vol-No-8-Issue-No-1-Wireless-Sensor-Network-For-Brain-Computer-Interface-075-079 by ISERP ISERP

Ms. Vaidehi Baporikar* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 075 - 079

Wireless Sensor Network For Brain Computer Interface Student G.H.Raisoni College of Engineering Nagpur, India vaidehi.ycce2008@gmail.com

Keywords-Brain Computer Interface, Wireless Sensor Network, EEG.

INTRODUCTION

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Recent advances in computer hardware and signal processing have made possible the use of EEG signals or ― brain waves‖ for communication between humans and Computers. The electrical nature of the human nervous system has been recognized for more than a century. It is well known that the variation of the surface potential distribution on the scalp reflects functional activities emerging from the underlying brain .This surface potential variation can be recorded by affixing an array of electrodes to the scalp, and measuring the voltage between pairs of these electrodes, which are then filtered, amplified, and recorded. The resulting data is called the EEG. Electrodes conduct voltage potentials as microvolt level signals, and carry them into amplifiers that magnify the signals approximately ten thousand times. The use of this technology depends strongly on the electrodes positioning and the electrodes contact. One such limitation involves the signal artifacts created by movement of wires; even small movements of wires within the generated magnetic field causes artifacts of considerable magnitude. Instead of using labor-intensive, on-site EEG data acquisition and weird BCI system, low-power EEG Sensor

ISSN: 2230-7818

Assistant Professor G.H.Raisoni College Of Engineering Nagpur, India

and Network between various modules of BCI can help to improve mobility of BCI System. In Sensor Network patient‘s EEG signal (analog format) could be automatically collected and processed (such as using Analog-to-Digital conversion) by a EEG sensor, and then be wirelessly sent to a remote host computer for analysis purpose (such as using data classification to find out anomaly). Because of the limited radio broadcasting distance of an EEG sensor (typically less than 300 feet), a patient‘s EEG sensor should use a neighbor sensor to relay its data if his/her distance is too far away from the host computer. EEG activity can be analyzed and quantified in the time domain, as voltage versus time or in the frequency domain, as voltage or power versus frequency .Both forms of analysis can be used for EEG based communication. Also the various studies have indicated that people can learn to control certain features of EEG thereby the use of EEG signals became more popular than all other types of BCI. The ‗mental typewriter,‘ developed by researchers at the Fraunhofer Institute and Humboldt University medical school in Berlin, was exhibited at the CeBit computer fair in Hanover, Germany. The Berlin Brain-Computer Interface (BBCI) consists of an electroencephalogram cap containing electrodes that measure the electrical activity in the motor cortex. This region of the brain starts generating electrical signals when movements are being planned. The BCCI amplifies the signals and transmits them to the computer which converts them into electronic cursor control signals. After 20 minutes of imagining the arm movements required to move a cursor, a user can control the computer‘s cursor to move over an on-screen keyboard using the power of thought. A brain-computer interface is a communication system that does not depend on the brain's normal output pathways of peripheral nerve and muscles. In brain computer interface, signals emitted from the brain are directly recorded, interpreted and acted upon wheelchair in order to move it in specific direction. Hence work is done without the use of any muscles. This technology has the ability to solve blocked people suffering with the disorders but it also brings the promise of simplifying every individual's lives. The aim of such research is that the person should be able to perform functions that he wished to without using his body muscles.

Abstract— A Brain-Computer Interface (BCI) is a system that acquires and analyzes neural signals with the goal of creating a communication channel directly between the brain and the computer. BCI is a system that allows its users to control external devices with brain activity. EEG is a powerful noninvasive tool widely used for both medical diagnosis and neurobiological research because it can provide high temporal resolution in milliseconds that directly reflects the dynamics of the generating cell assemblies. The use of EEG signals became more popular than all other types of BCI. Objective of paper is to develop wireless network to connect various modules involve in BCI system. Our goal in this work is to propose a wireless network to control wheelchair/peripherals from a BCI. This requires robotic wheels able to assist the user with the navigation task.

Mrs. Swapnili Karmore

Ms. Vaidehi Baporikar

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Ms. Vaidehi Baporikar* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 075 - 079

II.

SUGGESTED METHODE

Brain Computer Interface System can be divided into 3 basic modules 1) Brain Signal Acquisition System. 2) Brain computer Interface for converting Signals into Commands. 3) Device to be Controlled Brain Signal Acquisitio n System Module 1

Brain Compute r Interface on Host System

Device controlled by BCI (wheelchair or robotic arm)

Module 2

Module 3

Brain Signal Acquisiti on System Node 1

Brain Comput er Interfac e on Host System

Device controlled by BCI (wheelchair or robotic arm)

DESIGN OF PROTOTYPE MODEL

1) Node1- Signal Transmitter Node The initial part of this node is EEG signal conditioning but main focus is to transmit digitalized EEG data. The design of EEG Sensor Node contains Microcontroller which includes A/D converter which will convert analog signal into digital form. Then flash memory to store data and software. a micro-processor core which will control data transfer. The data is then transferred wirelessly through wireless transmitter interfaced with micro-controller. This all requirements are fulfilled by Microcontroller ATMEGA16 interfaced with RF transmitter. The advantages of the microcontroller‘s higher level of integration are:  Lower cost — one part replaces many parts.  More reliable — Fewer packages, fewer interconnects.  Better performance — System components are optimized for their environment.  Faster — Signals can stay on the chip.

Node 3

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Node 2

III.

Figure1 Existing Wired communications between Modules of BCI

transmission. This is the main objective of this project. Instead of using labor-intensive, on-site EEG data acquisition and weird BCI system, low-power EEG Sensor and Network for BCI can help to improve mobility of BCI System. The objective of paper can be achieved by employing wireless sensor network; the system will have following nodes, 1) Signal Transmitter.-Node1 2) Signal Receiver.-Node2 3) Device control system.Node-3

This means that the thoughts of the user are converted to actions. This project aims to develop wireless platform do this. The electrical signals from the Cerebral Cortex of the user's brain are recorded, these are then interpreted by the use of an algorithm and the required function is performed.

Figure 2 Proposed Wireless communications between Modules of BCI

All these systems are having wired communication between modules; hence the main goal of this project is to provide wireless network in-between these modules. As Shown in figure 1 the existing BCI systems are having wired communication between modules for data transfer. The purposed model is shown in figure 2 which contains wireless media to communicate between modules. The objective of this work is to develop prototype of wireless network between modules of brain computer interface. As per earlier discussion the suggested work is to develop wireless network to connect various modules involve in this system in other words wireless communication between modules of BCI. This involves wireless EEG signal transmission. This work is only concern about signal

ISSN: 2230-7818

Figure 3 Signal Transmitter Node Here as we are developing prototype of system the EEG conditioning part is replace by simple wave generator. 2) Node2- Signal Receiver The fig 4 gives overview of wireless node which will receive signal and provide brain computer interface running on host computer system. The brain computer interface program is beyond scope of this project. This node only focuses on reception of signal and communication of micro-controller The Transmitter and Receiver contains micro-controller and RF module for signal transmission.

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Ms. Vaidehi Baporikar* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 075 - 079

2) Signal Receiver Node U1 19

29 30 31

Figure 5 Design of Signal Receiver Node

1 2 3 4 5 6 7 8

XTAL1

XTAL2

RST

39 38 37 36 35 34 33 32

P0.0/AD0 P0.1/AD1 P0.2/AD2 P0.3/AD3 P0.4/AD4 P0.5/AD5 P0.6/AD6 P0.7/AD7

21 22 23 24 25 26 27 28

P2.0/A8 P2.1/A9 P2.2/A10 P2.3/A11 P2.4/A12 P2.5/A13 P2.6/A14 P2.7/A15

PSEN ALE EA

P1.0 P1.1 P1.2 P1.3 P1.4 P1.5 P1.6 P1.7

RXD TXD

10 11 12 13 14 15 16 17

P3.0/RXD P3.1/TXD P3.2/INT0 P3.3/INT1 P3.4/T0 P3.5/T1 P3.6/WR P3.7/RD

RTS CTS

AT89C51

3) Node3-Device Control system Micro-controller

3) Device Control System

Receiver

Figure 7 schematic of Node2

The figure 5 present design of receiver node includes receiver and micro-controller which contains communication interface for communicate with external world and flash memory to store controlling commands. The micro-processor cores will synchronies the reception of wireless signal and transfer of data to host PC through RS232 communication interface. Hence this data can be accessed at PC via Com port. This node is implemented using 89v51 micro-controller which is simple 8051 micro-controller.

Actuators

Figure 8 schematic of Node3

The figure 3.5 shows device control system. A user wants to control device like robotic arm or wheelchair which contains actuators like wheels or dc motors to perform movements. For controlling purpose this actuators must be interfaced with micro-controller to convert BCI commands in movements of wheels. Here the simple robot is used as device control System. A robot contains two wheels which are interfaced with dc motors.

Software Implementation

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Figure 3.4 Structure of Node3 Device Control System

1) Node-1 Signal Transmitter node Start

Receive voltages at Pin

IV.IMPLEMENTATION

1) Signal Transmitter Node

Convert Analog signal to Digital

13 12 40 39 38 37 36 35 34 33 1 2 3 4 5 6 7 8

RESET XTAL1 XTAL2

PA0/ADC0 PA1/ADC1 PA2/ADC2 PA3/ADC3 PA4/ADC4 PA5/ADC5 PA6/ADC6 PA7/ADC7

PB0/T0/XCK PB1/T1 PB2/AIN0/INT2 PB3/AIN1/OC0 PB4/SS PB5/MOSI PB6/MISO PB7/SCK

PC0/SCL PC1/SDA PC2/TCK PC3/TMS PC4/TDO PC5/TDI PC6/TOSC1 PC7/TOSC2 PD0/RXD PD1/TXD PD2/INT0 PD3/INT1 PD4/OC1B PD5/OC1A PD6/ICP1 PD7/OC2

AREF AVCC

22 23 24 25 26 27 28 29 14 15 16 17 18 19 20 21

RXD

Transmit the converted value using serial communication

TXD RTS CTS

VCC

GND

81%

VCC

RV1

32 30

ATMEGA16

Figure 6 schematic of Node1

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Figure 9 Flowchart of Node1

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Ms. Vaidehi Baporikar* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 075 - 079

RESULTS

2) Node-2 Signal Receiver node Start

Receive data on RX pin

Store it Temporary

Rece iver

Figure 9 Flowchart of Node1 3) Node3-Device Control system

Microcontroller

Actuat ors

Transmit the received data using serial communication to host

Figure 11 Wireless transmissions between nodes

Start

Receive data at Pin RX

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Store it temporary

1) Reception of wave

Command Robotâ&#x20AC;&#x2DC;s wheels as per received data

Figure 10 Flowchart of Node 3

ISSN: 2230-7818

As receiver module is connected to host computer, the data received is appeared on HyperTerminal of host system. Values appeared on HyperTerminal gives this waveform. Node 1 is EEG acquisition system where EEG waves are converted in digital form. 2) Movement of Robot As soon as commands are received at node3 Device control system that is simple robot, starts its movement in circular way. But these commands are followed by on one dc

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Ms. Vaidehi Baporikar* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 075 - 079

REFERENCES [1]

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CONCLUSION A BCI is a communication system that does not depend on the brain‘s normal output pathways of peripheral nerves and muscles. Therefore, BCI system can provide an augmentative communication method for patients with severe motor disabilities. Paralyzed patients can ask for basic necessities like water and food or use a computer by moving the cursor on a monitor screen using a BCI system without any voluntary muscle control. Wireless platform for Brain Computer Interface improve efficiency and mobility of such bulkier system as well as it will also provide greater advantage in research of signal acquisition. One can record EEG signals while performing various tasks like walking, running and exercising. Handicap person can also access its devices without using wired communication.

[13] B. Rivet1, A. Souloumiac , G. Gibert , V. Attina, and O. Bertrand ― Sensor selection for P300 speller brain computer interface ‖ Author manuscript, published in "ESANN, Belgium (2009) ― [14] Syed M. Saddique and Laraib Hassan Siddiqui ― EEG Based Brain Computer Interface‖ journal of software, vol. 4, no. 6, august 2009 [15] Rui Ma, Dae-Hyeong Kim, Martin McCormick, Todd Coleman and John Rogers “A Stretchable Electrode Array for Non-invasive, SkinMounted Measurement of Electrocardiography (ECG), Electromyography (EMG) and Electroencephalography (EEG)‖ National Security Science and Engineering Faculty Fellowship and by the U.S. Department of Energy, Division of Materials Sciences under Award No. DE-FG02-07ER46471 [16] Iturrate, J. Antelis and J. Minguez ― Synchronous EEG Brain-Actuated Wheelchair with Automated Navigation‖ Tech. Rep., Neil Squire Society, Vancouver, Canada,2006.

motor and other remains switch off which enables robot to move circular motion. The command is given through wireless network adopted in this experiment movement of robot in circular path assures that data is receiving at this end hence the objective of this project to develop prototype wireless frame work has been achieved

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[30] Wanli Min and Gang Luo ― Medical Applications of EEG Wave Classification‖ CHANCE VOL. 22, NO. 4, 2009

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