‘Smart’ wheelchairs for mobility training

Nisbet, Paul; Craig, J. W. T.; Odor, Phil; Aitken, Stuart

doi:10.3233/tad-1996-5107

Cited by 33 publications

(50 citation statements)

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“…In an extreme case, the human operator might only point the target and the machine would be in charge of motion planning and path tracking on its own (Bourhis and Agostini 1998;Crisman and Cleary 1998;Frese et al 2005;Gomi and Griffith 1998;Nisbet et al 1995;Simpson and Levine 1997). These systems work like a conventional autonomous robot: the user simply provides a destination and the wheelchair is totally in charge of getting there via a hybrid navigation scheme.…”

Section: Deliberative Shared Controlmentioning

confidence: 98%

A new multi-criteria optimization strategy for shared control in wheelchair assisted navigation

et al. 2010

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In todays aging society, many people require mobility assistance, that can be provided by robotized assistive wheelchairs with a certain degree of autonomy when manual control is unfeasible due to disability.Robot wheelchairs, though, are not supposed to be completely in control because lack of human intervention may lead to loss of residual capabilities and frustration. Most of these systems rely on shared control, which typically consists of swapping control from human to robot when needed. However, this means that persons never deal with situations they find difficult. We propose a new shared control approach to allow constant cooperation between humans and robots, so that assistance may be adapted to the user's skills. Our proposal is based on the reactive navigation paradigm, where robot and human commands become different goals in a Potential Field. Our main novelty is that human and robot attractors are weighted by their respective local efficiencies at each time instant. This produces an emergent behavior that combines both inputs in an efficient, safe and smooth way and is dynamically adapted to the user's needs. The proposed control scheme has been successfully tested at hospital Fondazione Santa Lucia (FSL) in Rome with several volunteers presenting different disabilities.

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Section: Deliberative Shared Controlmentioning

confidence: 98%

A new multi-criteria optimization strategy for shared control in wheelchair assisted navigation

et al. 2010

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“…One clinically and commercially available system that includes bump sensors is the Communication Aids for Language and Learning (CALL) Centre Smart Wheelchair. This device was intended to enable children with severe disabilities to learn skills for mobility before progressing to a conventional power wheelchair, or as a more permanent means of mobility using the adaptive features (CALL Centre, 2000;Nisbet, Craig, Odor, & Aitken, 1996). Bump sensors consist of rubber tubes and pressure switches.…”

Section: Power Wheelchair Technologymentioning

confidence: 99%

“…A significant proportion of nursing home residents use wheelchairs as a means of mobility. The 1996The /1997 Canadian National Population Health Survey found that 49% of residents in health care institutions used wheelchairs (Shields, 2004). Residents who are physically unable to move a manual wheelchair may use power wheelchairs; however, power wheelchair use may be restricted because of safety concerns related to cognitive limitations.…”

Section: Introductionmentioning

confidence: 98%

Evaluation of a Contact Sensor Skirt for an Anti-Collision Power Wheelchair for Older Adult Nursing Home Residents With Dementia: Safety and Mobility

Wang

PEng

Holliday

et al. 2011

Assistive Technology

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We studied an anti-collision power wheelchair's ability to enable safe, independent mobility in nursing home residents with dementia. The device had a contact sensor skirt that compensated for drivers' absent or delayed responses to obstacles. Safety observations were tracked during device use. In six single-subject studies, distances traveled by residents in manual and anti-collision wheelchairs were compared. Two residents could use the device: One resident's mobility and well-being improved; the other thought it was unhelpful. Another resident with potential for use did not like its usability, speed, and appearance. For two other residents, the device did not compensate for decreased initiation, motor planning, and awareness of obstacles above the sensors. Another resident was withdrawn because of verbal aggression. Interviews and focus groups revealed the device's usefulness. Perceptions of safety were mixed. Further work should improve environmental coverage, sensor skirt reliability, and safety; match technology to the needs of a wider range of residents; and enhance usability, functionality, and acceptance.

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“…This system can be utilized by different brands of wheelchairs and does not require any modifications. A system called CALL [4] has also been developed which is used as mobility training aid. It follows lines and on collision with an obstacle it comes back.…”

Section: Related Workmentioning

confidence: 99%

“…The first group [4], [8], [12] has functional capabilities such as path planning and execution. They require either some information about the area such as its complete map or some adjustments to their environment.…”

Section: Related Workmentioning

confidence: 99%

Smart wheelchair using fuzzy inference system

Tyagi¹,

Gupta²,

Tyagi³

2013

2013 IEEE Global Humanitarian Technology Conference: South Asia Satellite (GHTC-SAS)

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In this paper "Smart Wheelchair using Fuzzy Inference System" has been presented, which has a user friendly guidance system and has ability to avoid obstacles. For guiding the wheelchair Finger Tip Control is used and for obstacle avoidance Ultrasonic Sensors have been used. The fuzzy If-Then rules have been defined which govern the functioning of the wheelchair in different conditions. The system is simulated on fuzzy tool box and results have been generated. The use of fuzzy control allows the use of inexpensive and imprecise sensors, which will keep the overall system cost and complexity low. Using fuzzy logic control makes the implementation of the system much more practical which is the number one goal.

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‘Smart’ wheelchairs for mobility training

Cited by 33 publications

References 0 publications

A new multi-criteria optimization strategy for shared control in wheelchair assisted navigation

A new multi-criteria optimization strategy for shared control in wheelchair assisted navigation

Evaluation of a Contact Sensor Skirt for an Anti-Collision Power Wheelchair for Older Adult Nursing Home Residents With Dementia: Safety and Mobility

Smart wheelchair using fuzzy inference system

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