Identification of wheelchair user steering behaviour within indoor environments

Onyango, S.O.; Hamam, Yskandar; Djouani, Karim; Daachi, B.

doi:10.1109/robio.2015.7419114

Cited by 3 publications

(2 citation statements)

References 30 publications

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“…The system usability was evaluated quantitatively with four participants, unlike this research, conducted with 10 participants. Lastly, Onyango et al [ 54 ] validated the prototype implementing an evaluation system that differs of the used in this research. The system had static obstacles and they evaluated the system safety when avoiding obstacles, such as in this research.…”

Section: Discussionmentioning

confidence: 99%

Design and Implementation of a Position, Speed and Orientation Fuzzy Controller Using a Motion Capture System to Operate a Wheelchair Prototype

Callejas-Cuervo

Gonźalez-Cely

Bastos

2021

Sensors

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The design and implementation of an electronic system that involves head movements to operate a prototype that can simulate future movements of a wheelchair was developed here. The controller design collects head-movements data through a MEMS sensor-based motion capture system. The research was divided into four stages: First, the instrumentation of the system using hardware and software; second, the mathematical modeling using the theory of dynamic systems; third, the automatic control of position, speed, and orientation with constant and variable speed; finally, system verification using both an electronic controller test protocol and user experience. The system involved a graphical interface for the user to interact with it by executing all the controllers in real time. Through the System Usability Scale (SUS), a score of 78 out of 100 points was obtained from the qualification of 10 users who validated the system, giving a connotation of “very good”. Users accepted the system with the recommendation to improve safety by using laser sensors instead of ultrasonic range modules to enhance obstacle detection.

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Section: Discussionmentioning

confidence: 99%

Design and Implementation of a Position, Speed and Orientation Fuzzy Controller Using a Motion Capture System to Operate a Wheelchair Prototype

Callejas-Cuervo

Gonźalez-Cely

Bastos

2021

Sensors

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“…Although extensive information regarding modelling and control of powered wheelchairs exists [ 11 – 17 ], behaviour modelling for assistance and rehabilitation is still limited. In fact, apart from [ 18 – 23 ], the authors failed to locate more behaviour models related to wheelchair drivers. Studies in the vast area of behaviour modelling have been approached mainly from the field of automotives, aviation simulators, and robotic intelligence [ 24 , 25 ].…”

Section: Introductionmentioning

confidence: 99%

A Driving Behaviour Model of Electrical Wheelchair Users

Onyango

Hamam

Djouani

et al. 2016

Computational Intelligence and Neuroscience

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In spite of the presence of powered wheelchairs, some of the users still experience steering challenges and manoeuvring difficulties that limit their capacity of navigating effectively. For such users, steering support and assistive systems may be very necessary. To appreciate the assistance, there is need that the assistive control is adaptable to the user's steering behaviour. This paper contributes to wheelchair steering improvement by modelling the steering behaviour of powered wheelchair users, for integration into the control system. More precisely, the modelling is based on the improved Directed Potential Field (DPF) method for trajectory planning. The method has facilitated the formulation of a simple behaviour model that is also linear in parameters. To obtain the steering data for parameter identification, seven individuals participated in driving the wheelchair in different virtual worlds on the augmented platform. The obtained data facilitated the estimation of user parameters, using the ordinary least square method, with satisfactory regression analysis results.

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