airo national journal volume 5 issn 23213914 sinha national.docx · web viewluigi bianchi, fabio...

AIRO NATIONAL JOURNAL VOLUME 5 ISSN 23213914

Development of a Real-Time Wireless Embedded Brain Signal Acquisition/Processing System and its Application on Driver's Drowsiness

Estimation

Submitted by : Yashwant Sinha

Abstract

In this paper, a compact ongoing remote implanted mind signal procurement/preparing framework is produced. The proposed framework coordinates electroencephalogram signal speaker procedure, remote transmission method, and installed continuous framework. The improvement procedure of this framework contains three sections: First, the Bluetooth convention is utilized as a transmission interface and incorporated with the bio-signal intensifier to transmit the deliberate physiological flags remotely. Second, the OMAP (Open Multimedia Architecture Platform) is utilized as an advancement stage and an implanted working framework for OMAP is additionally planned. At last, DSP Gateway is created as a system to manage the cerebrum signal examining assignments shared by ARM and DSP. A driver's subjective state estimation program has been created and executed on the proposed double center processor-based continuous remote implanted framework for show.

I. INTRODUCTION

W5 rITH the improvement of inserted framework and sign preparing strategy, there is an inclination to apply the installed framework procedure to Brain Computer Interface (BCI). An electroencephalogram-based Brain Computer Interface (EEG-based BCI) gives a novel idea to the correspondence between the human mind and the PC [1 ]-[4]. Customarily, the varieties of mind waveforms are measured on subject's scalp by the PC-based measuring instruments. For the detriment of utilizing PCs for moment figuring, we have to create wearable and reasonable Brain Computer Interface frameworks little gadgets with long battery life that can be conveyed inside or outside [5]. Continuous and installed frameworks

offer a superior stage to construct wearable and reasonable BCI frameworks, their constrained processor and memory assets are productively used.

The application might be anything but difficult to relocate to more up to date stages at whatever point littler and all the more capable gadgets are produced.

Subsequent to the handling of the EEG information investigation needs an extensive number of estimations, the figuring capacity of the implanted processor gets to be critical while picking a suitable inserted processor. So we consider the DSP processor as a coprocessor with ARM (Advance RSIC Machines). In this paper, we added to an implanted Brain Computer Interface framework. One of the primary separation of the actualized BCI framework is remote transmission which is more comfort for clients. Another reason is that double center inserted processor builds working execution and can spare registering time. The paper is sorted out as takes after. In Section II, the framework design of the BCI framework is presented. In Section III, the proposed information process technique is depicted. In Section IV, the test consequence of the proposed BCI framework is depicted.

Discussions and conclusions are summarized in Section V.

II. SYSTEM ARCHITECTURE

In this study, the overall system we developed can be divided into three units: (1) signal acquisition and amplifying unit, (2) wireless data transmission unit, and (3) dual core processing and display unit. The block diagram of the proposed system isa given in Fig.1


Fig.1 Block diagram of a BCI system

A. Signal Acquisition andAmplifying Unit

The sign procurement and opening up unit is utilized to gauge the EEG flag and sift through the commotion. The square outline of the unit is appeared in Fig. 2. The EEG intensifying circuit was organized of a pre-enhancer with the addition of 100, a segregated speaker to secure the subject, a band-pass channel to save 1-IOOHz which was made out of a low-pass channel and a high-pass channel, a differential intensifier which had the increase of ten or fifty (which can be picked by a switch), and a 60Hz step channel to dispense with the impact of the attachment antiquity.

Fig.2 Block diagram of a signal acquisition and amplification unit

Fig . 3 The signal aquisition and amplification unit

Fig. 3. The EEG was recorded uni-polarly from 2 gold-electrodes fixed on the forehead ofthe subject. The EEG signal is recorded with 343Hz sampling rate (8-bit resolution), the signal is then transmitted to the data processing unit by wireless data transmission unit.

B. Wireless Data Transmission Unit

Fig.4 demonstrates the remote information transmission unit which changes over the simple sign to computerized sign, and afterward it encodes and transmits through the remote transmitter and collector. To do that, we utilize ALTERA FLEX1 OK EPF 1 OKI OTC 144-3 CPLD (Complex Programmable Logic Device) to control the A/D converter and encode the information for the transmitter which is appeared as Fig.5. We pick the Bluetooth gadgets as the remote transmitter and wirelessreceiver, as a result of three preferences: (1) low transmission power, (2) the lack of awareness of the clamor, and (3) higher security. The attributes of the Bluetooth are appeared in the Table I.


C. Dual-core Processing and Display Unit

The double center handling and show unit is the fundamental part of the compact continuous remote inserted mind signal obtaining/preparing framework. The working center is TI (Texas Instruments) OMAP (Open Multimedia Architecture Platform) 1510, which is made out of ARM925 and TMS32OC55x DSP center. Fig.6 demonstrates Innovator Development Kit which is an advancement stage created by TI. A DSP processor is useful for EEG information handling with an expansive number of scientific counts. In this study, the DSP processor forms EEG information and the ARM925 speaks with alternate gadgets, for example, remote beneficiary gadgets and system. The DSP Gateway is utilized as the collaboration structure for correspondence between the two centers following the two processors have diverse capacities.

Fig. 6 Innovator development kit

DSP Gateway associates the ARM center with the DSP center, it can be considered as a product layer which is set at two centers. DSP door makes ARM center conceivable to utilize asset of DSP center by API (Application Program Interface),and works like a little ongoing portion which deals with the source and information stream in the DSP center. By this strategy, it drives the DSP center just when we have to prepare the EEG information. The Linux working framework is worked to deal with the asset of ARM center. The design of the DSP Gateway is appeared as Fig. 7.

The capacity of ARM center can be separated into three sections:

remote recipient control, (2) TCP/IP control, and (3) DSP Gateway driver. The examination calculation is planned in the DSP processor, which will be presented in next segment. A presentation module is intended to show the examination yield and the first EEG wave signals on PC. The piece outline of the double center handling and show Unit is appeared in Fig. 8.


Fig.7. The structure of DSP Gateway

III. ANALYSIS ALGORITHM

In this paper, the proposed framework was utilized to obtain the driver's EEG signs and tiredness state of the driver was to be assessed through programmed EEG examination. Keeping in mind the end goal to test and check our examination calculation, we constructed a test domain first. As of late, driving securely has gotten expanding consideration of the publics because of the developing number of car crashes. Drivers' weakness has been involved as a causal variable in numerous mischances in view of the checked decrease in the drivers' capacities of observation, acknowledgment and vehicle control capacities while sluggish. In this paper, we utilize this framework and execute a

calculation to recognize the languor ofthe driver precisely.

A VR-based element driving recreation environment and a 6-DOF dynamic Stewart movement stage were utilized to reenact the circumstance of the driving in the interstate, and measure the EEG signs of the subject. The 3-D roadway driving scene is appeared as Fig. 9. The four paths from left to right are isolated by a middle stripe. The subject must keep the auto in the center ofthe third path, and the auto is driven at an altered rate of 100 km/hr on the thruway. The auto is arbitrarily floated away from the cruising path to the copy results of a non-perfect street surface.

The execution of our estimation figuring relies on upon the driving oversight of the subject, since it is hard to keep the auto in the midst of the cruising way if the subject is lethargic. Past studies [6-7] indicated when the subject starts to fall into littler scale rest or end up being less thought in the midst of the way keeping driving undertaking, the reduction in the driver's vehicle control limit will make the auto skimming far from within ofthe cruising way. With a particular final objective to look into the relationship between the planned EEG banners and subject's scholarly state, and to assess the level of the subject's status, we described the subject's driving execution index(driving botch) as the deviation between the point of convergence of the vehicle and the point of convergence of the cruising way as an underhanded estimation ofthe subject's


sharpness level.

It has been demonstrated that human weakness or tiredness most generally happens late during the evening and amid the evening.

Amid these periods, readiness shortages would in all likelihood happen in 1-h repetitive working [8][9]. In this paper, we hence led every single driving analysis in the early evening hours after lunch to boost the chances to gather information amid which subject driving execution got to be irregular. For every session, the subject began with a min alignment strategy and afterward was approached to drive the auto ceaselessly for 45 min. The EEG information and the driving blunders were measured and recorded at the same time. Members then returned on various days to finish the second 45-min driving session or the third session if fundamental. We select members who had two or more microsleep scenes in view of the deliberate driving blunders.

A. Information handling stream

Fig. 10 demonstrates the information handling stream. In the wake of obtaining the crude EEG information, we change the specimen rate to 64 Hz, and change to power arrangement by utilizing Short-Time FFT. The length of the handling window of Short-Time FFT is set as 64 information focuses. At that point we standardized the force arrangement and disposed

of commotion by a moving normal channel. Finally, the prepared information was sustained into the direct relapse model to evaluate the driving execution ofthe driver.

Fig. 10. Flowchart of the EEG signal analysis procedure.

B. Analysis System Design

By depiction in area II, the primary errands of the inserted processor OMAP1510 contain EEG information process, remote recipient control, and TCP/IP control. In this manner we disseminate the errands to DSP processor and ARM processor to fulfill the prerequisites. By attributes of the processors, the DSP processor ascertained the driving blunder estimation errand which required an expansive amount of ceaseless EEG information calculation, and we keep it as a module which can be taken care of by ARM. The ARM center executes three undertakings: (1) control the Bluetooth gadget to procure the EEG crude information, (2) handle the DSP assignment to evaluate the driving blunder ofthe driver, and (3) demonstrate the aftereffects of the estimation over the system.

The ARM processor is chosen for these undertakings for the reason of its magnificent interface control capacity. All procedure stream and errand division is appeared in Fig. 11.


Fig. 1 1. The structure of the EEG process.

IV. RESULT

A. Signal Acquisition andamplifying Unit Test

The test ofour framework was performed by three stages. Initially, we utilized EEG test system to produce sin wave with recurrence of5 Hz and the plentifulness ofvibration was set as 30uV. In Fig. 12, we utilized this unit to gauge the sign ofeye flickers, subsequent to the adequacy of the sign was anything but difficult to be recognized. Keeping in mind the end goal to affirm the accuracy of measured sign, the subject was approached very still with eye-shut for the event of a wave. The a wave with recurrence of 8-12Hz was measured and appeared in Fig. 13.

B. Wireless Data Transmission Unit Test

We utilized two PCs to control the Bluetooth gadgets. Host gadget was going to seek another

Bluetooth gadget naturally. Customer gadget held up until host gadget had discovered it, and after that the association and information transmission were begun. The CPLD was utilized to control the customer gadget while OMAP 1510 was controlling disjoin gadget, and after that test proceeded.

C. Analysis Algorithm

By depiction in segment III, we apply our framework to gauge the driver's subjective state. Before performing the estimation calculation on the OMAP, we should train an estimation model, test and confirm it disconnected from the net by PC.

We utilized C code to actualize our estimation calculation and after that assessed its execution by a Matlab program. Fig. 14 demonstrates the estimation of the preparation information and Fig. 15 demonstrates the estimation of the testing information. The blue line is the genuine driving blunder and the red line is the driving mistake estimation. In Fig. 14, the connection coefficient ofthe two time arrangement in the preparation information is 0.87. In Fig. 15, the relationship coefficient of the two time arrangement in the testing information is 0.87. By result, we could utilize the model which was prepared disconnected from the net to appraise the driving blunder on the web. This exhibits it was practical to gauge using so as to drive mistake as the list of tiredness EEG signals.


D. Overall System Test

After the subsystems were tried and confirmed, we coordinated the subsystems and tried on the web. So as to demonstrate the estimation aftereffects of our framework, we utilized a Java project to get estimation results by system and drawn a diagram. The Java show screen are appeared in Fig. 16 and 17, the left two edges are line information of BEG signs of two channels, and the right side are the consequences of estimation, individually. Outline C demonstrates the consequence of estimation at regular intervals and zero when the DSP center ascertaining. Outline D demonstrates the

aftereffect of estimation ceaselessly. In the event that the driver is ready, the showcase screen is show as Fig. 16. Since the driver is ready, there are no crests in casing C. Fig. 17 demonstrates the presentation screen when driver is sluggishness, there are crests in edge C. Te result shows that the framework we created is practical.

V. DISCUSSION AND CONCLUSION

In this paper, a double center based implanted framework is proposed for an actualized mind PC interface (BCI) to gauge languor state of driver. The executed framework appears as Fig. 18, we utilized the VR-based driving environment and a 6-DOF dynamic Stewart movement stage for reenactment of the driving circumstance, and after that the EEG sign was gained by means of terminals and the increasing unit. The sign was transmitted to the OMAP1510 through the Bluetooth gadget.


Estimation of the driving mistake of subject was accomplished by the processor, and the information was transmitted to the server through the system. The fundamental segregation of the actualized framework can be portrayed as takes after: (1) remote transmission which gives comfort ofusing it.

(2) double center installed processor which advance execution and spare registering time.

Fig. 18. The estimation ofthe training data.

The most troublesome work of our examination is to build up the I/O driver to interface the Bluetooth gadget and coordinate the all subsystems ofthe BCI framework. In the transmission unit, we should comprehend the structure of the bundles and the transmission convention. In the sign procurement and enhancing unit, the best approach to regulate the framework for getting the sign effectively is a crucial work. At the point when the framework was incorporated, we endeavored bunches of endeavors on the strength of the framework.

The proposed framework coordinates electroencephalogram signal enhancer method, remote transmission procedure, and inserted constant framework. We have actualized an ongoing inserted framework to prepare the EEG signals.

Moreover, we coordinated Bluetooth transmission system and the sign obtaining and intensifying unit. We utilized OMAP1510 as an inserted processor to exploit the figuring power ofDSP to lessen registering time. Later on, we plan to incorporate the EEG examination

framework onto a chip, make it more advantageous to convey for moment investigation.

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airo national journal volume 5 issn 23213914 sinha national.docx · web viewluigi bianchi, fabio...

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