Review of intelligent wheelchair technology control development in the last 12 years

Wahyufitriyani, Cindy; Susmartini, Susy; Priadythama, Ilham

doi:10.1109/icimece.2016.7910458

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…Another algorithm is used for the detection of the eyes and blinking. Concerning the systematic review carried out [101], the book broadens the outlook with regard to the control systems implemented between 2004 and 2016, as expressed by the authors, to continue expanding the review on the topic. Consequently, the review indicates that from the categories arise multiple systems and that the authors make an effort to solve daily problems that people with physical disabilities are faced with.…”

Section: Discussionmentioning

confidence: 99%

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: Discussionmentioning

confidence: 99%

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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“…This segment of people needs to use a special control system depending on their abilities. In order to find a solution to this problem, various methods and techniques have been developed to create intelligent wheelchairs (IWs) over the last years [1], [2]. According to the general concept presented in the relevant literature, an IW is defined as a standard powered wheelchair equipped with sensors and a computer, allowing it to have certain intelligence.…”

Section: Introductionmentioning

confidence: 99%

Implementation of wheelchair controller using mouth and tongue gesture

Hassani

Boumehraz

Hamzi

2021

IJEECS

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In this paper, a simple human-machine interface allowing people with severe disabilities to control a motorized wheelchair using mouth and tongue gesture is presented. The development of the proposed system consists of three principal phases: the first phase is mouth detection which performed by using haar cascade to detect the face area and template matching to detect mouth and tongue gestures from the lower face region. The second phase is command extraction; it is carried by determining the mouth and tongue gesture commands according to the detected gesture, the time taken to execute the gestures, and the previous command which is stored in each frame. Finally, the gesture commands are sent to the wheelchair as instruction using the Bluetooth serial port. The hardware used for this project were; laptop with universal serial bus (USB) webcam as a vision-based control unit, Bluetooth module to receive instructions comes from the vision control unit, standard joystick used in case of emergency, joystick emulator which delivers to the control board signals similar to the signals that are usually generated by the standard joystick, and ultrasonic sensors to provide safe navigation. The experimental results showed the success of the proposed control system based on mouth and tongue gestures.

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“…The mobile robot uses ultrasonic range finders for detection and mapping in order to prevent collision with various obstacles [18]. An obstacle avoidance strategy used for this robot relies vitaly on the performance of the ultrasonic range finders although the sensors have limitations on the obstacle avoidance algorithm [19][20].…”

Section: Introductionmentioning

confidence: 99%

Smart Wheelchair with Dual Control using Touchpad and Android Mobile Device

Arboleda

Paulite

Carandang

2018

IJEEI

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The general objective of the design was to develop a touchpad controlled Android-based electronic wheelchair. It aimed to construct the Androidbased circuitry and program for the path finding mechanism of the drive system and interface the Arduino-based circuit to the electronic wheelchair setup. It was designed to evaluate the system in terms of the speed of the electronic wheelchair, reliability of the sensors to avoid obstacle, and ease of use of the wheelchair. C Programming Language was used by the system to control and manipulate the microcontroller, Gizduino AtM ega644. The Android application was programmed using the Java Language and Eclipse as the IDE. Its ports were used to interface input and output devices such as the ultrasonic sensors, infrared proximity sensor, touchpad, Bluetooth module, motor and motor driver. There was a satisfactory rating for the evaluation of the system while the Android software was rated excellent as a navigational controller.

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Review of intelligent wheelchair technology control development in the last 12 years

Cited by 6 publications

References 13 publications

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

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

Implementation of wheelchair controller using mouth and tongue gesture

Smart Wheelchair with Dual Control using Touchpad and Android Mobile Device

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