AI-based smart and intelligent wheelchair
Rahimunnisa, K.; M., Atchaiya; Arunachalam, Brindhhiniy; Divyaa, V.
Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM
dor_id: 4110272
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590.#.#.d: Los artículos enviados a la revista "Journal of Applied Research and Technology", se juzgan por medio de un proceso de revisión por pares
510.0.#.a: Scopus, Directory of Open Access Journals (DOAJ); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Indice de Revistas Latinoamericanas en Ciencias (Periódica); La Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (Redalyc); Consejo Nacional de Ciencia y Tecnología (CONACyT); Google Scholar Citation
561.#.#.u: https://www.icat.unam.mx/
650.#.4.x: Ingenierías
336.#.#.b: article
336.#.#.3: Artículo de Investigación
336.#.#.a: Artículo
351.#.#.6: https://jart.icat.unam.mx/index.php/jart
351.#.#.b: Journal of Applied Research and Technology
351.#.#.a: Artículos
harvesting_group: RevistasUNAM
270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx
590.#.#.c: Open Journal Systems (OJS)
270.#.#.d: MX
270.1.#.d: México
590.#.#.b: Concentrador
883.#.#.u: https://revistas.unam.mx/catalogo/
883.#.#.a: Revistas UNAM
590.#.#.a: Coordinación de Difusión Cultural
883.#.#.1: https://www.publicaciones.unam.mx/
883.#.#.q: Dirección General de Publicaciones y Fomento Editorial
850.#.#.a: Universidad Nacional Autónoma de México
856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/1351/794
100.1.#.a: Rahimunnisa, K.; M., Atchaiya; Arunachalam, Brindhhiniy; Divyaa, V.
524.#.#.a: Rahimunnisa, K., et al. (2020). AI-based smart and intelligent wheelchair. Journal of Applied Research and Technology; Vol. 18 Núm. 6, 2020; 362-367. Recuperado de https://repositorio.unam.mx/contenidos/4110272
245.1.0.a: AI-based smart and intelligent wheelchair
502.#.#.c: Universidad Nacional Autónoma de México
561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM
264.#.0.c: 2020
264.#.1.c: 2020-12-31
653.#.#.a: smart wheelchair; artificial intelligence; health monitoring; gesture recognition; self-dependency; deep learning analysis; ThingSpeak; digital health chart
506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx
884.#.#.k: https://jart.icat.unam.mx/index.php/jart/article/view/1351
001.#.#.#: 074.oai:ojs2.localhost:article/1351
041.#.7.h: eng
520.3.#.a: The differently abled and/or old-aged people require assistance for their movement. Generally, such assistant providing tool is wheelchair. Normal wheelchairs are manually operated and heavy to move adding burden to the suffered. Hence, automated wheelchairs that are equipped with sensors and a data processing unit constitute a special class of wheeled mobile robots, termed as “smart wheelchairs” in general. In the existing system, the wheelchair movement that is controlled by joystick uses buttons to start and stop the wheel. This is difficult for the differently abled to press the required button with precision. Although there are smart wheelchairs with gesture control, it lacks accuracy in the calculation of the location. The proposed system uses artificial intelligence for its working and proves to be a unique combination of wheelchair and health monitoring system. The wheelchair can be accessed both in manual and automatic modes. In the manual mode, the wheel is controlled using joystick whereas in the automated mode, MPU6050 sensor and accelerometer is used to control the direction by gesture. SPO2 sensor attached to the wheelchair is used to collect the health parameters. Thus, enabling the self-dependency of the person. Further, deep learning analysis of the data from the sensors and the wheelchair usage pattern is compared with the dataset to determine the stress level. The signal from the sensors is monitored and the vitals data is updated in the ThingSpeak website via Bluetooth module serving as a digital health chart.
773.1.#.t: Journal of Applied Research and Technology; Vol. 18 Núm. 6 (2020); 362-367
773.1.#.o: https://jart.icat.unam.mx/index.php/jart
022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423
310.#.#.a: Bimestral
300.#.#.a: Páginas: 362-367
264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM
doi: https://doi.org/10.22201/icat.24486736e.2020.18.6.1351
harvesting_date: 2023-11-08 13:10:00.0
856.#.0.q: application/pdf
file_creation_date: 2020-12-17 23:30:02.0
file_modification_date: 2020-12-17 23:30:02.0
file_creator: Yolanda G.G.
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last_modified: 2024-03-19 14:00:00
license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es
license_type: by-nc-sa
Rahimunnisa, K.; M., Atchaiya; Arunachalam, Brindhhiniy; Divyaa, V.
Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM
Rahimunnisa, K., et al. (2020). AI-based smart and intelligent wheelchair. Journal of Applied Research and Technology; Vol. 18 Núm. 6, 2020; 362-367. Recuperado de https://repositorio.unam.mx/contenidos/4110272