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AStar-Algorithm based Voice-Controlled Wheelchair for Quadriplegic Patients

by Mohamed R. Abdelkader, Eslam T. Abdullah, Rana A. Mohamed, Rehab K. Salam, Omar Y. Mohamed, Azza M. Anis
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 34
Year of Publication: 2023
Authors: Mohamed R. Abdelkader, Eslam T. Abdullah, Rana A. Mohamed, Rehab K. Salam, Omar Y. Mohamed, Azza M. Anis
10.5120/ijca2023923127

Mohamed R. Abdelkader, Eslam T. Abdullah, Rana A. Mohamed, Rehab K. Salam, Omar Y. Mohamed, Azza M. Anis . AStar-Algorithm based Voice-Controlled Wheelchair for Quadriplegic Patients. International Journal of Computer Applications. 185, 34 ( Sep 2023), 31-35. DOI=10.5120/ijca2023923127

@article{ 10.5120/ijca2023923127,
author = { Mohamed R. Abdelkader, Eslam T. Abdullah, Rana A. Mohamed, Rehab K. Salam, Omar Y. Mohamed, Azza M. Anis },
title = { AStar-Algorithm based Voice-Controlled Wheelchair for Quadriplegic Patients },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2023 },
volume = { 185 },
number = { 34 },
month = { Sep },
year = { 2023 },
issn = { 0975-8887 },
pages = { 31-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number34/32911-2023923127/ },
doi = { 10.5120/ijca2023923127 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:29:00.896023+05:30
%A Mohamed R. Abdelkader
%A Eslam T. Abdullah
%A Rana A. Mohamed
%A Rehab K. Salam
%A Omar Y. Mohamed
%A Azza M. Anis
%T AStar-Algorithm based Voice-Controlled Wheelchair for Quadriplegic Patients
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 34
%P 31-35
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Physical disabilities caused by ageing, accidents, and diseases, pose significant challenges for individuals, hence affecting their mobility and communication abilities. Besides, the conventional control mechanisms proved ineffective for individuals with hand injuries or paralysis. Therefore, assistive devices such as wheelchairs have received much interest in recent years. In this paper, a voice-controlled wheelchair based on AStar-algorithm is proposed to overcome these limitations. The proposed design consists of a microcontroller interfaced with an ultrasonic sensor, a rotary encoder, a gyroscope, and motors for rotating the wheels in a specific direction. Moreover, an android application is created to send voice commands via a bluetooth module to interact with the microcontroller unit. The proposed system allows users to communicate easily to their desired destination using voice commands, then the wheelchair will autonomously find the shortest path and guide a user accordingly. The validity of the design is confirmed by Proteus simulations. After that, the capability of mobile application for fast communication between a user and the design is verified. Finally, a prototype for the proposed voice-controlled wheelchair is implemented and tested for different destinations.

References
  1. World Health Organization. 2011. World Report on Disability Summary. World Rep Disabil. WHO/ NMH/ VIP/ 11.01. 1–23.‏
  2. Bourgeois-Doyle, R. I., George, J. 2004.‏ The Great Inventor. NRC Research Press.
  3. Kundu, A. S., Mazumder, O., Lenka, P. K., Bhaumik, S. 2018. Hand gesture recognition based omnidirectional wheelchair control using IMU and EMG sensors. J. Intell. Robot. Syst. Vol. 91, 1–13.
  4. Jha, P. and Khurana, P. 2016. Hand gesture controlled wheelchair. Int. J. Sci. Technol. Res. Vol. 9, 243–249.
  5. Yassine, R., Makrem, M., Farhat, F. 2018. Intelligent control wheelchair using a new visual joystick. J. Healthc. Eng., 1–20.
  6. Lopes, J., Sim, O. M., Mendes, N., Safeea, M., Afonso, J., Neto, P. 2017. Hand/arm gesture segmentation by motion using IMU and EMG sensing. Procedia Manuf. Vol. 11, 107–113.
  7. Eid, M. A., Giakoumidis, N., Saddik, A. E. 2016. A novel eye-gaze-controlled wheelchair system for navigating unknown environments: case study with a person with ALS. IEEE Access Vol. 4, 558–573.
  8. Meena, Y. K., Cecotti, H., Wong-Lin, K. F., Prasad, G. 2017. A multimodal interface to resolve the midas-touch problem in gaze controlled wheelchair. In Proceedings of the Engineering in Medicine & Biology Society, Jeju, Korea, 11–15.
  9. Dahmani, M., Chowdhury, M., Khandakar, A., Rahman, T., Kiranyaz, S. 2020. An intelligent and low-cost eye tracking system for motorized wheelchair control. Sensors Vol. 20, No. 14, 3936.
  10. Nobuaki, K. and Masahiro, N. 2018. BCI-based control of electric wheelchair using fractal characteristics of EEG. IEEJ Trans. Electr. Electron. Eng. Vol. 13, 1795–1803.
  11. Shahin, M. K., Tharwat, A., Gaber, T., Hassanien, A. E. 2017. A wheelchair control system using human-machine interaction: single modal and multimodal approaches. J. Intell. Syst. Vol. 28, 115–132.
  12. Liu, R., Wang, Y., Newman, G. I., Thakor, N. V., Ying, S. 2017. EEG classification with a sequential decision-making method in motor imagery BCI. Int. J. Neural Syst. Vol. 27, 1750046.
  13. Antoniou, E., Bozios, P., Christou, V., Tzimourta, K. D., Tzallas, A. T. 2021. EEG-based eye movement recognition using the brain–computer interface and random forests. Sensors Vol. 21, No. 7, 2339.
  14. Chahal, B. M. 2014. Microcontoller based gesture controlled wheelchair using accelerometer. Int. J. Eng. Sci. Res. Technol. Vol. 3, 1065–1070.
  15. Larrazabal, A. J., Cena, C., Martínez, C. 2019. Video oculography eye tracking towards clinical applications: a review. Comput. Biol. Med. Vol. 108, 57–66.
  16. Zaydoon, T., Zaidan, B. B., Zaidan, A. A., Suzani, M. S. 2018. A review of disability EEG based wheelchair control system: coherent taxonomy, open challenges and recommendations. Comput. Methods Programs Biomed. Vol. 164, 221–237.
  17. Suryawanshi, S. D., Chitode, J. S., Pethakar, S. S. 2013. Voice operated intelligent wheelchair. International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE), Vol. 3, No. 5, 487–490.
  18. Peixoto, N., Nik, H. G., Charkhkar, H. 2013. Voice controlled wheelchairs: fine control by humming. Computer Methods and Programs in Biomedicine, Vol. 112, No. 1, 156–165.
  19. Ruzaij, M. F., Neubert, S., Stoll, N., Thurow, K. 2017. Design and implementation of low-cost intelligent wheelchair controller for quadriplegias and paralysis patient. In 2017 International Symposium on Applied Machine Intelligence and Informatics (SAMI), 000399–000404.‏
  20. Wang, D. and Yu, H. 2017. Development of the control system of a voice-operated wheelchair with multi-posture characteristics. In Proceedings of the Asia-Pacific Conference on Intelligent Robot Systems, 151–155.
  21. Garg, U., Ghanshala, K. K., Joshi, R. C., Chauhan, R. 2018. Design and implementation of smart wheelchair for quadriplegia patients using IOT. In 2018 International Conference on Secure Cyber Computing and Communication (ICSCCC), 106–110.
  22. Aktar, N., Israt J., Bijoya, L. 2019. Voice recognition based intelligent wheelchair and GPS tracking system. In 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE), 1–6.
  23. Safy, M., Metwally, M., Thabet, N. E., Ahmed, I. N., AboElELa, G., Bayoumy, A., Ashraf, M. 2022. Low-cost smart wheelchair to support paraplegic patients. International Journal of Industry and Sustainable Development, Vol. 3, No. 1, 1–9.‏
Index Terms

Computer Science
Information Sciences

Keywords

AStar-Algorithm Voice-Controlled Wheelchair Sensors Microcontroller Motors Android Application

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