Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art
Automatic wheelchairs have evolved in terms of instrumentation and control, solving the mobility problems of people with physical disabilities. With this work it is intended to establish the background of the instrumentation and control methods of automatic wheelchairs and prototypes, as well as a c...
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doaj-0afeb1066076423a8998080ededb0f1c2020-11-25T03:59:38ZengMDPI AGSensors1424-82202020-11-01206326632610.3390/s20216326Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the ArtMauro Callejas-Cuervo0Aura Ximena González-Cely1Teodiano Bastos-Filho2Grupo de Investigación en Software, Universidad Pedagógica y Tecnológica de Colombia, Avenida Central del Norte 39-115, Tunja 150003, Boyacá, ColombiaGrupo de Investigación en Software, Universidad Pedagógica y Tecnológica de Colombia, Avenida Central del Norte 39-115, Tunja 150003, Boyacá, ColombiaPostgraduate Program in Electrical Engineering, Federal University of Espírito Santo, Av. Fernando Ferrari, 514-Goiabeiras, Vitória, Espírito Santo 29075-910, BrazilAutomatic wheelchairs have evolved in terms of instrumentation and control, solving the mobility problems of people with physical disabilities. With this work it is intended to establish the background of the instrumentation and control methods of automatic wheelchairs and prototypes, as well as a classification in each category. To this end a search of specialised databases was carried out for articles published between 2012 and 2019. Out of these, 97 documents were selected based on the inclusion and exclusion criteria. The following categories were proposed for these articles: (a) wheelchair instrumentation and control methods, among which there are systems that implement micro-electromechanical sensors (MEMS), surface electromyography (sEMG), electrooculography (EOG), electroencephalography (EEG), and voice recognition systems; (b) wheelchair instrumentation, among which are found obstacle detection systems, artificial vision (image and video), as well as navigation systems (GPS and GSM). The results found in this review tend towards the use of EEG signals, head movements, voice commands, and algorithms to avoid obstacles. The most used techniques involve the use of a classic control and thresholding to move the wheelchair. In addition, the discussion was mainly based on the characteristics of the user and the types of control. To conclude, the articles exhibited the existing limitations and possible solutions in their designs, as well as informing the physically disabled community about the technological developments in this field.https://www.mdpi.com/1424-8220/20/21/6326automatic wheelchaircontrolinstrumentationintelligent wheelchair |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mauro Callejas-Cuervo Aura Ximena González-Cely Teodiano Bastos-Filho |
spellingShingle |
Mauro Callejas-Cuervo Aura Ximena González-Cely Teodiano Bastos-Filho Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art Sensors automatic wheelchair control instrumentation intelligent wheelchair |
author_facet |
Mauro Callejas-Cuervo Aura Ximena González-Cely Teodiano Bastos-Filho |
author_sort |
Mauro Callejas-Cuervo |
title |
Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art |
title_short |
Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art |
title_full |
Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art |
title_fullStr |
Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art |
title_full_unstemmed |
Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art |
title_sort |
control systems and electronic instrumentation applied to autonomy in wheelchair mobility: the state of the art |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-11-01 |
description |
Automatic wheelchairs have evolved in terms of instrumentation and control, solving the mobility problems of people with physical disabilities. With this work it is intended to establish the background of the instrumentation and control methods of automatic wheelchairs and prototypes, as well as a classification in each category. To this end a search of specialised databases was carried out for articles published between 2012 and 2019. Out of these, 97 documents were selected based on the inclusion and exclusion criteria. The following categories were proposed for these articles: (a) wheelchair instrumentation and control methods, among which there are systems that implement micro-electromechanical sensors (MEMS), surface electromyography (sEMG), electrooculography (EOG), electroencephalography (EEG), and voice recognition systems; (b) wheelchair instrumentation, among which are found obstacle detection systems, artificial vision (image and video), as well as navigation systems (GPS and GSM). The results found in this review tend towards the use of EEG signals, head movements, voice commands, and algorithms to avoid obstacles. The most used techniques involve the use of a classic control and thresholding to move the wheelchair. In addition, the discussion was mainly based on the characteristics of the user and the types of control. To conclude, the articles exhibited the existing limitations and possible solutions in their designs, as well as informing the physically disabled community about the technological developments in this field. |
topic |
automatic wheelchair control instrumentation intelligent wheelchair |
url |
https://www.mdpi.com/1424-8220/20/21/6326 |
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