Tecnología asistiva para la comunicación y movilidad de personas con discapacidad motriz
x
DOI:
https://doi.org/10.33936/isrtic.v3i2.1958Keywords:
assistive technology; communication; mobility; motor disability; wheelchair.Abstract
This research focuses on developing a control system to apply in a conventional wheelchair through different technological tools (virtual keyboard, jostick, Neurosky MindWave) to help people with motor disabilities with language problems (communication) and mobilityof different degrees, through the use of hardware and free software. The joystick mobility and the Neurosky MindWave device and communication is carried out together with the manipulation of a mobile device (cellular, Tablet,) using the touch screen, implemented onthe wheelchair for the control of the disabled person, the hardware (Arduino) and software (Xamarin studio, PHP, java) used are open source complying with decree 1014 and code ingenios established in the Republic of Ecuador. It is proposed to implement this system and to offer important advantages over similar ones in terms of cost and easy adaptabilityto any standard wheelchair. In this way, people with disabilities can communicate and mobilize when they need it.
Downloads
References
[2] CONADIS. (2019). Personas con Discapacidad Registradas. Retrieved March 19, 2019,from https://public.tableau.com/views/Discapacidad/Inicio?:embed=y&:showVizHome=no&:loadOrderID=0&:display_count=yes&:showTabs=y
[3] Edyburn, D. L. (2018). Assistive Technology and Students with Mild Disabilities. Focus on Exceptional Children, 32(9), 18–28. https://doi.org/10.17161/fec.v32i9.6776
[4] Fernández-Merjildo, D., & Najar Trujillo, E. (2016). Informe mundial sobre la discapaci- dad. Revista Medica Herediana (Vol. 27). https://doi.org/10.20453/rmh.v27i1.2785
[5] Girase, P. D., & Deshmukh, M. P. (2016). Mindwave Device Wheelchair Con- trol. International Journal of Science and Research (IJSR), 5(6), 2172–2176. https://doi.org/10.21275/v5i6.nov164722
[6] Herrador, R. E. (2009). Guía de Usuario de Arduino. Universidad de Cordoba, 1, 8–10.
[7] Jácome, L., Jadan, J., & Chango, G. (2016). Teclado Virtual para Apoyar la Co- municación de Niños con Discapacidad Motriz Teclado Virtual para Apoyar la Comunicación de Niños con Discapacidad Motriz Virtual Keyboard to Support the Communication of Children with Motor Disability, 85–96. Retrieved from http://www.uti.edu.ec/antiguo/documents/investigacion/volumen4/7. articulo tecla- do virtual (1).pdf
[8] Juhong, A., Treebupachatsakul, T., & Pintavirooj, C. (2018). Smart eye-tracking sys- tem. 2018 International Workshop on Advanced Image Technology, IWAIT 2018, 1–4. https://doi.org/10.1109/IWAIT.2018.8369701
[9] Leaman, J., La, H. M., & Nguyen, L. (2017). Development of a smart wheelchair for people with disabilities. In IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (pp. 279–284). https://doi.org/10.1109/MFI.2016.7849501
[10] Maksud, A., Chowdhury, R. I., Chowdhury, T. T., Fattah, S. A., Shahanaz, C., & Chowd- hury, S. S. (2017). Low-cost EEG based electric wheelchair with advanced control features. IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2017-Decem, 2648–2653. https://doi.org/10.1109/TENCON.2017.8228309
[11] Morales, J., Guerra, H., & Morales, N. (2012). Control de una Silla de Ruedas porMedio de un Dispositivo Móvil con. Revista Tecnología Digital, 2(1), 1–13. Retrieved from http://www.capacidades.sistemastectuxtla.net/pdf/articulos/02_004_control_de_una_silla_de_ruedas_android.pdf
[12] Pu, J., Jiang, Y., Xie, X., Chen, X., Liu, M., & Xu, S. (2018). Low cost sensor network for obstacle avoidance in share-controlled smart wheelchairs under daily scenarios. Micro- electronics Reliability, 83, 180–186. https://doi.org/10.1016/J.MICROREL.2018.03.003
[13] Rabhi, Y., Mrabet, M., & Fnaiech, F. (2018). A facial expression controlled wheelchair for people with disabilities. Computer Methods and Programs in Biomedicine, 165, 89–105. https://doi.org/10.1016/j.cmpb.2018.08.013
[14] Sałabun, W. (2014). Processing and spectral analysis of the raw EEG signal from the MindWave. Przeglad Elektrotechniczny, 90(2), 169–173. https://doi.org/10.12915/pe.2014.02.44
[15] Samaniego, P., Laitamo, S.-M., Estela, V., & Francisco, C. (2012). Infor- me sobre el uso de las tecnologías de información y comunicación (TIC ) en la educación para personas con discapacidad, 77. Retrieved from https://unesdoc.unesco.org/ark:/48223/pf0000216382_spa
[16] Sanchez Alvarez, J. F., & Jiménez Builes, J. A. (2016). Teclado Virtual Pa-ra Personas Con Enfermedades Neuromusculares Accionado a Través DeUn Evento Acústico. Virtual Keyboard for People With Neuromuscular Di-seases Operated Through an Acoustic Event., 12(22), 33–40. Retrieved fromhttp://proxy2cobimet.net:2048/login?user=cobsocial&pass=C@bimet3sSocial&qurl=http %3A %2F %2Fsearch.ebscohost.com %2Flogin.aspx %3Fdirect %3Dtrue %26db %3Dfua %26AN %3D123595847 %26lang %3Des %26site %3Deds- live %26scope %3Dsite
[17] Sethi, A., Deb, S., Ranjan, P., & Sardar, A. (2017). Smart mobility solution with multiple input Output interface. Proceedings of the Annual International Conferen- ce of the IEEE Engineering in Medicine and Biology Society, EMBS, 3781–3784. https://doi.org/10.1109/EMBC.2017.8037680
[18] Silva de Souza, E., Cardoso, A., & Lamounier, E. (2018). A Virtual Environment-Based Training System for a Blind Wheelchair User Through Use of Three-Dimensional Au- dio Supported by Electroencephalography. Telemedicine and E-Health, 24(8), 614–620. https://doi.org/10.1089/tmj.2017.0201
[19] Sivakumar, B. G., & Sudhagar, K. (2015). Design & developent of intelligent wheelchair. ARPN Journal of Engineering and Applied Sciences, 10(11), 5004–5006. Retrieved from https://pdfs.semanticscholar.org/a4bb/d63fd0cd8c710cccb6c67bf5380ce0b4bba7.pdf
[20] Soma, S., Patil, N., & Jadhav, V. (2018). An Approach to develop a smart and intelligent wheelchair. In 9th International Conference on Computing, Com- munication and Networking Technologies (ICCCNT) (p. 7). Retrieved from https://ieeexplore.ieee.org/document/8494050
[21] Souza, A., Kelleher, A., Cooper, R., Cooper, R. A., Iezzoni, L. I., & Collins, D. M. (2010). Multiple sclerosis and mobility-related assistive technology: Systema- tic review of literature. The Journal of Rehabilitation Research and Development. https://doi.org/10.1682/JRRD.2009.07.0096
[22] Stephygraph, L. R., Arunkumar, N., & Venkatraman, V. (2015). Wireless Mobile Robot Control through Human Machine Interface, (May), 596–603. https://doi.org/10.1109 / ICSTM.2015.7225484
[23] Tiwari, K. (2015). BRAIN CONTROLLED ROBOT USING NEUROSKY MIND- WAVE. Journal of Technological Advances and Scientific Research, 6(4), 489–492. https://doi.org/10.7897/2277-4343.06493
[24] Velasco-Álvarez, F., Fernández-Rodríguez, Á., Díaz-Estrella, A., J. Blanca-Mena, M., & Ron-Angevin, R. (2018). Control strategies of a brain-controlled wheelchair using two mental tasks. Smart Wheelchairs and Brain-Computer Interfaces, 345–368. https://doi.org/10.1016/B978-0-12-812892-3.00014-5
Published
How to Cite
Issue
Section
License
Articles submitted to this journal for publication will be released for open access under a Creative Commons Attribution Non-Commercial No Derivative Works licence (http://creativecommons.org/licenses/by-nc-nd/4.0).
The authors retain copyright, and are therefore free to share, copy, distribute, perform and publicly communicate the work under the following conditions: Acknowledge credit for the work specified by the author and indicate if changes were made (you may do so in any reasonable way, but not in a way that suggests that the author endorses your use of his or her work. Do not use the work for commercial purposes. In case of remixing, transformation or development, the modified material may not be distributed.



