Wheelchair automation using electromyographic signals obtained from facial movements
DOI:
https://doi.org/10.37636/recit.v6n4e317Keywords:
Automation, Motor disability, Electromyography, Wheelchair, TetraplegiaAbstract
Tetraplegia is a disease that can be caused by different factors, whether congenital or accidental, limiting people to live without being able to move both the lower and upper extremities. The present work shows the development of a prototype of a wheelchair for quadriplegics controlled by facial movements, this in order to give the patient independence and improve their emotional state by not requiring help to carry out the task of moving the chair. For the implementation of the prototype, an electronic circuit for analog acquisition, amplification and filtering of electromyography (EMG) signals was designed and built, which provides a signal corresponding to the degree of movement of the facial muscles. Subsequently, the signal obtained from the analog base board is digitized and processed with the help of an ATmega328p microcontroller, where additional filtering is performed and the movement made from the signals obtained is determined. This information is sent via Bluetooth connection to a second ATmega328p microcontroller in the physical prototype of the wheelchair. With the information of the action on the wheelchair's microcontroller, the conditioning of the signal is carried out to control the motors that will carry out the corresponding movement. Finally, a mobile application was designed and implemented to control the prototype through buttons, with the idea that a person responsible for the user of the chair can take control if necessary. As a result, the system was implemented on a basic commercial wheelchair, where the motors and a transmission by bands were adapted to generate the movement, this allowed basic control through facial movement and through the mobile application, however, the EMG system requires to be calibrated for different users. As future work, it is proposed to modify the transmission of the prototype and allow an automatic calibration to be applied regardless of the user.
Downloads
References
C. P. Henao-Lema y J. E. Pérez-Parra, “Lesiones medulares y discapacidad: revisión bibliográfica.” Aquichan, vol. 10 no. 2, pp. 157-172, agosto 2010. ISSN: 1657-5997. https://doi.org/10.5294/aqui.2010.10.2.5 DOI: https://doi.org/10.5294/aqui.2010.10.2.5
A. Fernández Pascual, “The spinal cord: the cord of life. The story of a quadriplegic by traffic accident.” Index de Enfermería, vol. 20, no. 3, pp. 199-202, julio 2011. https://doi.org/10.4321/S1132-12962011000200013 DOI: https://doi.org/10.4321/S1132-12962011000200013
D. García P., J. Castillo M. y J. Castillo C., “Complicaciones respiratorias de la tetraplejia: Una mirada a las alternativas terapéuticas actuales”, Revista chilena de enfermedades respiratorias, vol. 23, no. 2, pp. 106-116, junio 2007 https://dx.doi.org/10.4067/S0717-73482007000200005
M. Gifre, A. Valle, M. Yuguero, Á. Gil y P. Monreal, “La mejora de la calidad de vida de las personas con lesión medular: La transición del centro rehabilitador a la vida cotidiana desde la perspectiva de los usuarios.” Athenea Digital. Revista de Pensamiento e Investigación Social, no. 18, pp. 3-15, 2010. ISSN: 1578-8946. Disponible en: https://www.redalyc.org/articulo.oa?id=53720000001
M. J. Bernal González, N. J. Cabrera Viltres, M. Nápoles Pérez y L. Álvarez Placeres, “Cirugía reconstructiva de la mano en pacientes tetrapléjicos.” Revista Cubana de Ortopedia y Traumatología, vol. 33, no. 2, diciembre 2019. Recuperado en 20 de mayo de 2021, de http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S0864-215X2019000200001&lng=es&tlng=es.
F. Freire Carrera, O. Chadrina, E. Maila Andrango y V. Drozdov, “Diseño de sistema para controlar una silla de ruedas mediante señales eléctricas cerebrales”, MediSur, vol. 17, no. 5, pp. 650-663, octubre de 2019. Recuperado en 21 de mayo de 2021, de http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1727-897X2019000500650&lng=es&tlng=es
I. Gago Fernández y J. Seco Calvo, “Independencia funcional para el manejo autónomo de la silla de ruedas. A propósito de un caso”. Fisioterapia, vol. 32, no. 1, pp. 41-45, febrero 2010, ISSN 0211-5638, https://doi.org/10.1016/j.ft.2009.03.003 DOI: https://doi.org/10.1016/j.ft.2009.03.003
O. Veloz Segarra y M. Fornell Sánchez, “Diseño e implementación de un sistema de control de una silla de ruedas eléctrica mediante sensores mioeléctricos EOG/EMG”, Tesis de licenciatura, Escuela Superior Politécnica del Litoral, Guayaquil, Ecuador, 2015. Disponible en: http://www.dspace.espol.edu.ec/handle/123456789/34970
J. L. Correa-Figueroa, E. Morales-Sánchez, J. A. Huerta-Ruelas, J. J. González-Barbosa y C. R. Cárdenas-Pérez, “Sistema de Adquisición de Señales SEMG para la Detección de Fatiga Muscular”, Revista mexicana de ingeniería biomédica, vol. 37, no. 1, pp. 17-27, enero 2016. https://doi.org/10.17488/RMIB.37.1.4 DOI: https://doi.org/10.17488/RMIB.37.1.4
J. M. Weiss, L. D. Weiss, and J. K. Silver, Easy EMG-E-Book: A Guide to Performing Nerve Conduction Studies and Electromyography, Philadelphia, USA, Elsevier Health Sciences, 2023. Disponible en: https://www.us.elsevierhealth.com/easy-emg-9780323796866.html
M. Atzori, A. Gijsberts, C. Castellini, et al., "Electromyography data for non-invasive naturally-controlled robotic hand prostheses." Scientific data, vol. 1, no. 140053, pp. 1-13, diciembre 2014. https://doi.org/10.1038/sdata.2014.53 DOI: https://doi.org/10.1038/sdata.2014.53
R. M. Singh y S. Chatterji “Trends and challenges in EMG based control scheme of exoskeleton robots-a review.” International Journal of Scientific & Engineering Research, vol. 3, no. 8, Agosto 2012. ISSN 2229-5518. Disponible en: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=f119d63499566fae9bb13dcfadf8a82d6ce49fa5
G. Yin, X. Zhang, D. Chen, H. Li, J. Chen, C. Chen and S. Lemos, “Processing surface EMG signals for exoskeleton motion control.” Frontiers in Neurorobotics, vol. 14, julio 2020, ISSN=1662-5218, https://doi.org/10.3389/fnbot.2020.00040 DOI: https://doi.org/10.3389/fnbot.2020.00040
Y. Bouteraa, I. B. Abdallah and A. Elmogy, “Design and control of an exoskeleton robot with EMG-driven electrical stimulation for upper limb rehabilitation.” Industrial Robot: The International Journal of robotics research and Application, vol. 47, no. 4, pp. 489-501, mayo 2020, https://doi.org/10.1108/IR-02-2020-0041 DOI: https://doi.org/10.1108/IR-02-2020-0041
D. Dalal and U. Keshwala, "Design and analysis of EMG controlled anthropomorphic Prosthetic hand," 2021 8th International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India, 2021, pp. 345-349, https://doi.org/10.1109/SPIN52536.2021.9565947 DOI: https://doi.org/10.1109/SPIN52536.2021.9565947
A. Kaur, “Wheelchair control for disabled patients using EMG/EOG based human-machine interface: a review”, Journal of medical engineering & technology, vol. 45, no. 1, pp. 61-74, diciembre 2020, https://doi.org/10.1080/03091902.2020.1853838 DOI: https://doi.org/10.1080/03091902.2020.1853838
A. S. Kundu, O. Mazumder, P. K. Lenka y S. Bhaumik. “Hand gesture recognition based omnidirectional wheelchair control using IMU and EMG sensors”, Journal of Intelligent & Robotic Systems, Springer, vol. 91, pp. 529-541, october 2017. https://doi.org/10.1007/s10846-017-0725-0 DOI: https://doi.org/10.1007/s10846-017-0725-0
J. Vigliotta, J. Cipleu, A. Mikell and R. Alba-Flores, “EMG controlled electric wheelchair”. Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol. 296, pp. 439-449. Springer International Publishing 2022. https://doi.org/10.1007/978-3-030-82199-9_29 DOI: https://doi.org/10.1007/978-3-030-82199-9_29
A. C. Manero, S. L. McLinden, J. Sparkman and B. Oskarsson, “Evaluating surface EMG control of motorized wheelchairs for amyotrophic lateral sclerosis patients.” Journal of neuroengineering and rehabilitation, vol. 19, no. 1, pp. 1-10, Agosto 2022, https://doi.org/10.1186/s12984-022-01066-8 DOI: https://doi.org/10.1186/s12984-022-01066-8
INEGI. Discapacidad. Recuperado el 13 de noviembre de 2022. [Online] Disponible en:
https://cuentame.inegi.org.mx/poblacion/discapacidad.aspx
ASIA. American Spinal Injury Association. asia-spinalinjury.org. (28 de octubre de 2019) Obtenido de asia-spinalinjury.org. [online] Disponible en: https://asia-spinalinjury.org/wp-content/uploads/2019/11/International-Standards-Worksheet-Spanish-Final_10_28_2019.pdf
Y. Bahena-Salgado y J. Bernal-Márquez. “Calidad de vida de los pacientes con paraplejía secundaria a lesión vertebral traumática”. Acta ortopédica mexicana, vol. 21, no. 1, pp. 3-7. Recuperado el 04 de Septiembre de 2019, de https://www.medigraphic.com/pdfs/ortope/or-2007/or071b.pdf
World Health Organization. “International Perspectives on Spinal Cord Injury (IPSCI)”. In: Jerome Bickenbach, Cathy Bodine, Douglas Brown, et al. (eds.) Geneva, 2013. Disponible en: https://www.who.int/publications/i/item/international-perspectives-on-spinal-cord-injury
A. Polo, P. Narvaez, and C. Robles Algarín, “Implementation of a cost-effective didactic prototype for the acquisition of biomedical signals”, Electronics, vol. 7, no. 5, mayo 2018. Disponible en: https://doi.org/10.3390/electronics7050077 DOI: https://doi.org/10.3390/electronics7050077
A. Panja, A. Bhattacharya and T. P. Banerjee, "Design and Analysis of Notch Depth for T-Notch Filter," 2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA), Durgapur, India, 2020, pp. 1-4, https://doi.org/10.1109/NCETSTEA48365.2020.9119943 DOI: https://doi.org/10.1109/NCETSTEA48365.2020.9119943
K. Afifah and N. Retdian, “Design of N-path notch filter circuits for hum noise suppression in biomedical signal acquisition”, IEICE Transactions on Electronics, vol. E103-C, no. 10, pp. 480-488, october 2020. https://doi.org/10.1587/transele.2019CTP0009 DOI: https://doi.org/10.1587/transele.2019CTP0009
Y. E. Prasetyo, H. Hindarto, S. Syahrorini, and A. Wisaksono, “Wheelchair Control Using Bluetooth-Based Electromyography Signals”. Journal of Computer Networks, Architecture, and High-Performance Computing, vol. 5, no. 1, pp. 148-159, enero 2023. https://doi.org/10.47709/cnahpc.v5i1.2063 DOI: https://doi.org/10.47709/cnahpc.v5i1.2063
R. K. Singh, A. Sarkar, D. Chakravarty, P. Goyal, V. Lodhi and A. Sharma, "Bluetooth communication controlled robot based on gesture recognition," 2015 IEEE International Transportation Electrification Conference (ITEC), Chennai, India, 2015, pp. 1-5. https://doi.org/10.1109/ITEC-India.2015.7386937 DOI: https://doi.org/10.1109/ITEC-India.2015.7386937
MITAppInventor. (2011). appinventor.mit. [online] Obtenido de https://appinventor.mit.edu/about-us
F. Posada Prieto, “Creando aplicaciones para móviles Android con MIT App Inventor 2”, Instituto Nacional de Tecnologías Educativas y de Formación del Profesorado (INTEF), Recursos Educativos Digitales, abril 2019. ISSN:2695-4176. https://doi.org/104438/2695-4176_OTE_2019_847-19-121-5
E. W. Patton, M. Tissenbaum and F. Harunani, “MIT app inventor: Objectives, design, and development”, Computational thinking education, Springer Open, Singapure, ISBN 978-981-13-6528-7 (eBook) https://doi.org/10.1007/978-981-13-6528-7_3 DOI: https://doi.org/10.1007/978-981-13-6528-7_3
L. Zhu, G. Mao, H. Su, Z. Zhou., W. Li, X. Lü and Z. Wang. “A wearable, high-resolution, and wireless system for multichannel surface electromyography detection”, IEEE Sensors Journal, vol. 21, no. 8, pp. 9937-9948, abril 2021. https://doi.org/10.1109/JSEN.2021.3058987 DOI: https://doi.org/10.1109/JSEN.2021.3058987
S. H. Yeon and H. M. Herr, "Rejecting Impulse Artifacts from Surface EMG Signals using Real-time Cumulative Histogram Filtering," 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021, pp. 6235-6241. https://doi.org/10.1109/EMBC46164.2021.9631052 DOI: https://doi.org/10.1109/EMBC46164.2021.9631052
Z. Xiao, J. Ye, H. Shen, S. Deng, H. Zhu and H. Xiao, "Analysis of Digital Filtering Design Based on Surface EMG Signals," 2023 IEEE 3rd International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB), Taichung, Taiwan, 2023, pp. 542-546, https://doi.org/10.1109/ICEIB57887.2023.10170168 DOI: https://doi.org/10.1109/ICEIB57887.2023.10170168
M. Boyer, L. Bouyer, J. S. Roy, and A. Campeau-Lecours, “Reducing Noise, Artifacts, and Interference in Single-Channel EMG Signals: A Review”. Sensors, vol. 23, no. 6, marzo 2023. https://doi.org/10.3390/s23062927 DOI: https://doi.org/10.3390/s23062927
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2023 Jesús García García, Guillermo Rey Peñaloza Mendoza, Mario Salvador Castro Zenil, Víctor Becerra Tapia
This work is licensed under a Creative Commons Attribution 4.0 International License.
The authors who publish in this journal accept the following conditions:
The authors retain the copyright and assign to the journal the right of the first publication, with the work registered with the Creative Commons Attribution license 4.0, which allows third parties to use what is published as long as they mention the authorship of the work and the first publication in this magazine.
Authors may make other independent and additional contractual agreements for the non-exclusive distribution of the version of the article published in this journal (eg, include it in an institutional repository or publish it in a book) as long as they clearly indicate that the work it was first published in this magazine.
Authors are allowed and encouraged to share their work online (for example: in institutional repositories or personal web pages) before and during the manuscript submission process, as it can lead to productive exchanges, greater and more quick citation of published work (see The Effect of Open Access).