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Mind-Wave Wheelchair System


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DOI: https://doi.org/10.15866/iremos.v14i1.17842

Abstract


Rapid advances in technology have helped to improve human life, specifically for people with disabilities. These people cannot control their muscles, write, or talk properly because of disruptions in their nervous system. However, many of them can control their brain activity and eye movement. Electroencephalography (EEG) tools are used to track brainwaves and eyes blink activities and convert them to useful metrics. Using EEG tools, people with movement or speech disabilities can only be trained to think of any action they want to take to make it real. This paper proposes a system that can be integrated into a wheelchair to control the movements using brainwaves signals. In this paper, the NeuroSky mind-wave mobile headset is used as an EEG tool. NeuroSky signals combined with neural network MATLAB code as training code with the adjusted parameters of this code are supplied to the standalone Arduino controller used to control the mini wheelchair prototype.
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Keywords


Arduino Standalone AI Application; Artificial Neural Network (ANN); Brain-Computer Interface (BCI); EEG; Mind-Wave Wheelchair; NeuroSky Headset; Self-Organizing Maps

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References


O A Rușanu , L Cristea , M C Luculescu and P A Cotfas, A brain-computer interface based on the integration of NI myRIO development device and NeuroSky Mindwave headset, The 8th International Conference on Advanced Concepts in Mechanical Engineering, pp. 14-24, 2018.
https://doi.org/10.1088/1757-899x/444/4/042014

Derong Jiang, Jinghai Yin, Research of Auxiliary Game Platform Based on BCI Technology, Information Processing 2009. APCIP 2009. Asia-Pacific Conference, pp. 424-428, 2009.
https://doi.org/10.1109/apcip.2009.111

S. Z. Diya, R. A. Prorna, I. I. Rahman, A. B. Islam and M. N. Islam, Applying Brain-Computer Interface Technology for Evaluation of User Experience in Playing Games, 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE), Cox'sBazar, pp. 1-6, Bangladesh, 2019.
https://doi.org/10.1109/ecace.2019.8679203

J. M. McQuighan, G. Bajwa and J. M. Pittman, B2CI 2019: The IEEE Brain to Computer Interface Competition’s Gaming Event, 2019 IEEE Conference on Games (CoG), pp. 1-7, London, United Kingdom, 2019.
https://doi.org/10.1109/cig.2019.8848115

Zhen Liang, Hongtao Liu, Joseph N Mak, Detection of Media Enjoyment using Single-Channel EEG, IEEE Biomedical Circuits and Systems Conference (BioCAS), pp 516-519, 2016.
https://doi.org/10.1109/biocas.2016.7833845

Bose, J., Singhai, A., Patankar, A., Kumar, A., Attention Sensitive Web Browsing, Proceedings of the 9th annual ACM India conference, pp. 147-152, Jan 2016.
https://doi.org/10.1145/2998476.2998494

He Z, Li Z, Yang F, Wang L, Li J, Zhou C, Pan J., Advances in multimodal emotion recognition based on brain–computer interfaces, Brain Sci, Volume 10(Issue 10):1-29, 2020.
https://doi.org/10.3390/brainsci10100687

Apeksha Rani H. M, Prathibha Kiran, A Novel Method for Analysis of EEG Signals Using Brain Wave Data Analyzer, International Journal of Soft Computing and Engineering (IJSCE), Volume-5, (Issue-2): 98-100, May 2015.

Edisson Naula et al., Evaluating the Mindwave Headset for AutomaticUpper Body Motion Classification, International Conference on Information Systems and Computer Science (INCISCOS), pp 166-173, 2017.
https://doi.org/10.1109/inciscos.2017.10

Amaya, D., Villamil, M., Segura, S., Gutierrez, D., Processing and Analysis of EEG Signals Related to Short Time Memory Using a Brain-Computer Interface Device, (2016) International Review of Electrical Engineering (IREE), 11 (2), pp. 223-229.
https://doi.org/10.15866/iree.v11i2.8016

Fouad, I.A., Labib, F.E.M., Mabrouk, M.S. et al. Improving the performance of P300 BCI system using different methods, Network Model Anal Health Inform Bioinforma, Volume 9,( Issue 1): 434-441, 1 December 2020, Article number 64.
https://doi.org/10.1007/s13721-020-00268-1

Zhong Yin, et.al., Locally robust EEG feature selection for individual-independent emotion recognition, Expert Systems with Applications, Volume 162: 11768- 11770, 30 December 2020.
https://doi.org/10.1016/j.eswa.2020.113768

Shi, T., Ren, L. and Cui, W., Feature Extraction of Brain-Computer Interface Electroencephalogram Based on Motor Imagery, IEEE Sensors Journal, Volume 20, (Issue 20) :11787-11794, Article number 8824096, 15 October 2020.
https://doi.org/10.1109/jsen.2019.2939343

Pradnya Patil , Dimple Chaudhari, NeuroSky Mindwave BCI System: To Save Lives during Transportation, International Journal of Science and Research (IJSR), Volume 5–( Issue 01): 1952-1954, 2016.
https://doi.org/10.21275/v5i1.25011601

C. Liu, S. Xie, X. Xie, X. Duan, W. Wang and K. Obermayer, Design of a video feedback SSVEP-BCI system for car control based on improved MUSIC method, 2018 6th International Conference on Brain-Computer Interface (BCI), pp. 1-4, GangWon, 2018.
https://doi.org/10.1109/iww-bci.2018.8311499

J. Katona, T. Ujbanyi, G. Sziladi and A. Kovari, Speed control of Festo Robotino mobile robot using NeuroSky MindWave EEG headset based brain-computer interface, 2016 7th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), pp. 000251-000256, Wroclaw, 2016.
https://doi.org/10.1109/coginfocom.2016.7804557

Chi Hang Cheng, Shuai Li, Seifedine Kadry, Mind-Wave Controlled Robot: An Arduino Robot Simulating the Wheelchair for Paralyzed Patients, International Journal of Robotics and Control, Volume 1, (Issue 01): 6-19. 2018.
https://doi.org/10.5430/ijrc.v1n1p6

Kalyani Choudhari et al., Brainwave Controlled Robot, International Journal for Scientific Research & Development, Volume 4, (Issue 02): 609-612, 2016.

Yang D, Nguyen T-, Chung W-. A bipolar-channel hybrid brain-computer interface system for home automation control utilizing steady-state visually evoked potential and eye-blink signals. Sensors, Volume 20(Issue 19):1-15, 2020.
https://doi.org/10.3390/s20195474

R. ChandanaPriya, K. Aparna, Mind Wave Sensor Controlled Wheel Chair, International Journal of Advance Engineering and Research Development, Volume 4,(Issue 9): 415-417, September -2017.

Priyanka D. Girase , M. P. Deshmukh, Mindwave Device Wheelchair Control, International Journal of Science and Research (IJSR), Volume 5 (Issue 6): 2172-2176, 2016.
https://doi.org/10.21275/v5i6.nov164722

O. A. Ruşanu, L. Cristea and M. C. Luculescu, Simulation of a BCI System Based on the Control of a Robotic Hand by Using Eye-blinks Strength, 2019 E-Health and Bioengineering Conference (EHB), pp. 1-4, Iasi, Romania, 2019.
https://doi.org/10.1109/ehb47216.2019.8969941

B. Chambayil, R. Singla and R. Jha, Virtual keyboard BCI using Eye blinks in EEG, 2010 IEEE 6th International Conference on Wireless and Mobile Computing, Networking and Communications, pp. 466-470, Niagara Falls, ON, 2010.
https://doi.org/10.1109/wimob.2010.5645025

W. Zhi-Hao, Hendrick, K. Yu-Fan, C. Chuan-Te, L. Shi-Hao and J. Gwo-Jia, Controlling DC motor using eye blink signals based on LabVIEW, 2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE), pp. 61-65, Malang, 2017.
https://doi.org/10.1109/iceeie.2017.8328763

Sanket Ghorpade et al, Mindwave-A New Way to Detect an Eye Blink, International Journal of Advanced Research in Computer and Communication Engineering Volume 4, (Issue 3): 82-84, March 2015.
https://doi.org/10.17148/ijarcce.2015.4319

P. Lahane, J. Jagtap, A. Inamdar, N. Karne and R. Dev, A review of recent trends in EEG based Brain-Computer Interface, 2019 International Conference on Computational Intelligence in Data Science (ICCIDS), Chennai, India, pp. 1-6, 2019.
https://doi.org/10.1109/iccids.2019.8862054

H. G. Yeom, Trends and Future of Brain-Computer Interfaces, 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS), pp. 785-788, Toyama, Japan 2018.
https://doi.org/10.1109/scis-isis.2018.00130

P. Prashant, A. Joshi and V. Gandhi, Brain computer interface: A review, 2015 5th Nirma University International Conference on Engineering (NUiCONE), pp. 1-6, 2015.
https://doi.org/10.1109/nuicone.2015.7449615

Torres, E.P.; Torres, E.A.; Hernández-Álvarez, M.; Yoo, S.G. EEG-Based BCI Emotion Recognition: A Survey. Sensors, Volume 20, (Issue 18):1-36 Article number 5083, 2 September 2020.
https://doi.org/10.3390/s20185083

Drishti Yadav, Shilpee Yadav, Karan Veer , A comprehensive assessment of Brain Computer Interfaces: Recent trends and challenges, Journal of Neuroscience Methods, Volume 346: 108918, 1 December 2020.
https://doi.org/10.1016/j.jneumeth.2020.108918

Salguero, J., Avilés Sánchez, O., Mauledoux Monroy, M., Design of a Personal Communication Device, Based in EEG Signals, (2017) International Journal on Communications Antenna and Propagation (IRECAP), 7 (2), pp. 88-94.
https://doi.org/10.15866/irecap.v7i2.10927

Michael Negnevitsky, Artificial Intelligence A Guide to Intelligent Systems, Second Edition, Pearson Education Limited, 2005.

Marzbani, H., Marateb, H. R., & Mansourian, M., Neurofeedback: a comprehensive review on system design methodology and clinical applications. Basic and Clinical Neuroscience, Volume 7, (Issue 2):143-158, 2016.
https://doi.org/10.15412/j.bcn.03070208

Neurosky MindWave Mobile, Last access 16/10/2020.
http://neurosky.com/2018/06/mindwave-mobile-2-available-now-improved-comfort/

Hendel, M., Benyettou, A., Hendel, F., Fusion of Direct Probabilistic Multi-Class Support Vector Machines to Enhance Mental Tasks Recognition Performance in BCI Systems, (2018) International Journal on Communications Antenna and Propagation (IRECAP), 8 (5), pp. 430-438.
https://doi.org/10.15866/irecap.v8i5.14068

Marrugo Cardenas, N., Amaya Hurtado, D., Ramos Sandoval, O., Comparison of Multi-Class Methods of Features Extraction and Classification to Recognize EEGs Related with the Imagination of Two Vowels, (2018) International Journal on Communications Antenna and Propagation (IRECAP), 8 (5), pp. 398-405.
https://doi.org/10.15866/irecap.v8i5.12709


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