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Controlling a motorized electric wheelchair based on face tilting

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Disability, specifically impaired upper and/or lower limbs, has a direct impact on the patients’ quality of life. Nowadays, motorized wheelchairs supported by a mobility-aided technique have been devised to improve the quality of life of these patients by increasing their independence. This study aims to present a platform to control a motorized wheelchair based on face tilting. A real-time tracking system of face tilting using a webcam and a microcontroller circuit has been designed and implemented. The designed system is dedicated to control the movement directions of the motorized wheelchair. Four commands were adequate to perform the required movements for the motorized wheelchair (forward, right, and left, as well as stopping status). The platform showed an excellent performance regarding controlling the motorized wheelchair using face tilting, and the position of the eyes was shown as the most useful face feature to track face tilting.
Słowa kluczowe
Rocznik
Strony
art. no. 20190033
Opis fizyczny
Bibliogr. 19 poz., rys., tab.
Twórcy
  • Technical Engineering College, Northern Technical University, Mosul, Iraq
  • Technical Engineering College, Northern Technical University, Mosul, Iraq
  • Technical Engineering College, Northern Technical University, Mosul, Iraq
  • Technical Engineering College, Northern Technical University, Mosul, Iraq
Bibliografia
  • [1] Abu-Faraj ZO, Mashaalany MJ, BouSleiman HC, Heneine JD, Al Katergi WM. Design and development of a low-cost eye tracking system for the rehabilitation of the completely locked-in patient. International Conference of the IEEE Engineering in Medicine and Biology Society 2006. Available at: 10.1109/iembs.2006.260280. Accessed 2 Jul 2019.
  • [2] Stats about paralysis. Christopher & Dana Reeve Foundation, 2013. [Online]. Available at: https://www.christopherreeve.org/living-withparalysis/stats-about-paralysis.
  • [3] Kennedy PR, Adams KD. A decision tree for brain-computer interface devices. IEEE Trans Neural Syst Rehabil Eng 2003;11:148-50.
  • [4] Cutti A, Lettieri E, Verni G. Health technology assessment as theoretical framework to assess lower-limb prosthetics - issues and opportunities from an international perspective. J Prosthet Orthot 2019;31:55-73.
  • [5] Hassan AM, Alamgir H, Jahan Akhtar N, Hossain Z, Islam R, Sohrab HM. Characterisation of persons with lower limb amputation who attended a tertiary rehabilitation centre in Bangladesh. Disabil Rehabil 2019;29:1-7.
  • [6] Lin CS, Ho CW, Chen WC, Chiu CC, Yeh MS. Powered wheelchair controlled by eye-tracking system. Opt Appl 2006;36:2-3.
  • [7] Brandt Å, Iwarsson S, Ståhle A. Older people’s use of powered wheelchairs for activity and participation. J Rehabil Med 2004;36:70-7.
  • [8] Davies A, De Souza LH, Frank AO. Changes in the quality of life in severely disabled people following provision of powered indoor/outdoor chairs. Disabil Rehabil 2003;25:286-90.
  • [9] Thorp EB, Abdollahi A, Chen D, Farshchiansadegh A, Lee M, Pedersen JP, et al. Upper body-based power wheelchair control interface for individuals with tetraplegia. IEEE Trans Neural Syst Rehabil Eng 2016;24:249-60.
  • [10] Kundu A, Mazumder O, Lenka P, Bhaumik S. Hand gesture recognition based omnidirectional wheelchair control using IMU and EMG sensors. J Intell Robot Syst 2018;91:529-41.
  • [11] Ruzaij MF, Neubert S, Stoll N, Thurow K. Auto calibrated head orientation controller for a robotic-wheelchair using MEMS sensors and embedded technologies. IEEE Sensors Applications Symposium (SAS) 2016. Available at: 10.1109/sas.2016.7479886.
  • [12] Qassim HM, Basheer NM, Farhan MN. Brightness preserving enhancement for dental digital X-ray images based on entropy and histogram analysis. J Appl Sci Eng 2019;22:187-94.
  • [13] Mazhar O, Shah T, Khan M, Tehami S. A real-time webcam based Eye Ball Tracking System using MATLAB. IEEE 21st International Symposium for Design and Technology in Electronic Packaging (SIITME) 2015. Available at: 10.1109/siitme.2015.7342312.
  • [14] Russo JE. The limbus reflection method for measuring eye position. Behav Res Meth Instru 1975;7:205-8.
  • [15] Huang Q, He S, Wang Q, Gu Z, Peng N, Li K, Zhang Y, et al. An EOG-based human-machine interface for wheelchair control. IEEE Trans Biomed Eng 2018;65:2023-32.
  • [16] Sankardoss V, Geethanjali P. Design and low-cost implementation of an electric wheelchair control. IETE J Res. 2019;1-10. DOI: 10.1080/03772063.2019.1565951.
  • [17] Vázquez JE, Martin-Ortiz M, Olmos-Pineda I, Olvera-Lopez A. Wheelchair control based on facial gesture recognition. Internat J Info Technol Syst Approach 2019;12:104-22.
  • [18] Jiang H, Zhang T, Wachs JP, Duerstock BS. Enhanced control of a wheelchair-mounted robotic manipulator using 3-D vision and multimodal interaction. Comp Vis Image Underst 2016;149:21-31.
  • [19] Tang J. Real-time DC motor control using the MATLAB interfaced TMS320C31 Digital Signal Processing Starter Kit (DSK). In: Proceedings of IEEE International Conference on Power Electronics and Drive Systems. Hong Kong: IEEE, 1999;321-6.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-31171af1-457b-4f73-9ec1-4800d95fee3b
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