Wheelchair control by head motion

Pajkanovic, Aleksandar; Dokić, Branko

doi:10.2298/sjee1301135p

Cited by 43 publications

(12 citation statements)

References 18 publications

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“…The analog bandwidth is not more than half the analog-to-digital sampling frequency to minimize aliasing. The analog bandwidth can be further decreased to reduce noise and improve resolution [1], [8], [9]. The ADXL335 noise has the characteristics of white Gaussian noise, which contributes equally at all frequencies and is described in terms of Hz.…”

Section: Accelerometer (Adxl335) Devicementioning

confidence: 99%

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Real Time Breath Processing Based Embedded Vehicle Using WSN

2016

IJSR

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Now a day, Quadriplegic people depend on powered wheelchairs for mobility which are rare, complicated and expensive.Considering the application of these wheelchairs, the digital type interface is not desirable, because control of wheelchair need preciseness and quickness for safe operation. The purpose of this project is to design a wireless powered wheelchair with novel control system using user's breath pressure and head motion. The two interfacing devices that operate the wheelchair [mounted on cap (head)] are used. Breath pressure (Exhaling and Inhaling) of person and head motions are measured using these devices. Depending upon the breath taken in and out the wheelchair function activates and it moves forward, backward, left and right directions with the help of accelerometer. With this new technique health of the person is monitored with the help of breath pressure without using any kind of sensors like temp sensor, pulse oximetry (SpO2) sensor, heartbeat sensor etc. Motion of wheelchair is controlled wirelessly using Zigbee transceiver. In this paper microcontroller system that enables standard electric wheelchair control by breath and head motion is presented.

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Section: Accelerometer (Adxl335) Devicementioning

confidence: 99%

“…When the wheelchair is in any motion states, the movements will start when the user passes the threshold circle which is shown in Fig.23. It stops when the user returns the head in the starting position (state of still) [1], [9]. In Fig.23 all direction of the wheelchair is given with threshold circle.…”

Section: Head Motion Recognition Algorithmmentioning

confidence: 99%

Real Time Breath Processing Based Embedded Vehicle Using WSN

2016

IJSR

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“…Gyroscope, accelerometer and magnetometer sensors mounted onto a helmet enable the 3D positioning of the head to facilitate the use of software by participants with cerebral palsy (Raya et al 2012). Both head mounted gyroscope sensors and head mounted accelerometer sensors have been implemented to enable disabled participants to control wheelchairs by using head movement (Rechy-Ramirez et al 2012) (Pajkanovic and Dokic 2013). These sensor based systems necessitate the participant wearing bulky and intrusive instrumentation on their heads.…”

Section: Related Work and Devicesmentioning

confidence: 99%

HeadBanger: controlling switchable software with head gesture

Oppenheim

2016

Journal of Assistive Technologies

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Purpose – The purpose of this paper is to present a novel non-contact method of using head movement to control software without the need for wearable devices. Design/methodology/approach – A webcam and software are used to track head position. When the head is moved through a virtual target, a keystroke is simulated. The system was assessed by participants with impaired mobility using Sensory Software’s Grid 2 software as a test platform. Findings – The target user group could effectively use this system to interact with switchable software. Practical implications – Physical head switches could be replaced with virtual devices, reducing fatigue and dissatisfaction. Originality/value – Using a webcam to control software using head gestures where the participant does not have to wear any specialised technology or a marker. This system is shown to be of benefit to motor impaired participants for operating switchable software.

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“…Thus, the ultrasonic sensor is also used for static or mobile obstacle detection. In addition, the wheelchair is controlled by head motion [11] which proposed a head motion recognition algorithm using accelerometer data. The wheelchair joystick controlled based on the system's mechanical actuator.…”

Section: Introductionmentioning

confidence: 99%

Smart Autonomous Wheelchair Controlled by Voice Commands-Aided by Tracking System

2019

IJCCCE

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This study focuses on the design of an autonomous wheelchair based smart driving features for disabled persons. The movement directions and position tracking of the wheelchair are controlled and localized by pre-defined voice commands and global positioning system (GPS), respectively. Arduino microcontroller based on speaker dependent voice recognition module and tracking system based on quad-board SIM808 has been used to help the wheelchair navigation. The experimental tests of the proposed system have been done and given satisfactory results in controlling the wheelchair and making a call on demand. Hence the proposed system is a simple, easy to use and lowcost hardware for designing.

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Wheelchair control by head motion

Cited by 43 publications

References 18 publications

Real Time Breath Processing Based Embedded Vehicle Using WSN

Real Time Breath Processing Based Embedded Vehicle Using WSN

HeadBanger: controlling switchable software with head gesture

Smart Autonomous Wheelchair Controlled by Voice Commands-Aided by Tracking System

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