Development of a Route Finding System for Manual Wheelchair Users Based on Actual Measurement Data

Sumida, Yasuaki; Hayashi, Masaki; Goshi, Kazuaki; Matsunaga, Katsuya

doi:10.1109/uic-atc.2012.151

Cited by 8 publications

(3 citation statements)

References 3 publications

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“…Rotational velocity control and use of nodes and databases to operate the wheelchair. [32] Laser sensor, GPS module, accelerometer, Arduino. Barrier detector system analysing the rotation of the wheels.…”

Section: Instrumentation Control Systems Referencesmentioning

confidence: 99%

“…It includes an encoder to measure the speed at which the chair moves and a joystick for its basic control. Sumida et al [32] develop a navigation system which is based on the collection of data about its environment in order to be able to trace routes, using a GPS, which is safe and indicates to the person where they have to go. The system implements the Dijkstra algorithm, which finds routes which have the lowest cost among the nodes, which are assigned at a certain constant distance.…”

Section: Instrumentation Control Systems Referencesmentioning

confidence: 99%

“…To this end, ref. [6,10,11,14,16,18,20,23,32,33,36,38,40,[42][43][44]50,[58][59][60]64,67,71,[74][75][76][77]81,87,88] include safety systems to avoid obstacles. This indicates that approximately 40% of the articles mention the use of algorithms with ultrasonic sensors, lasers, infrared, cameras, among others, in order to provide security in the movement of wheelchairs and avoid crashes.…”

Section: Wheelchair Instrumentation and Hmimentioning

confidence: 99%

See 2 more Smart Citations

Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art

Callejas-Cuervo

Gonźalez-Cely

Bastos

2020

Sensors

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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.

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Section: Instrumentation Control Systems Referencesmentioning

confidence: 99%

Section: Instrumentation Control Systems Referencesmentioning

confidence: 99%