Due to pathologies or age-related problems, in some disabled people, motor impairment is associated with cognitive and/or visual impairments. This combination of limitations unfortunately leads to an inability to move around independently. Indeed, their situation does not allow them to use a conventional electric wheelchair, for safety reasons, and for the moment there is no other technological solution providing safe movement capacity. This lack of access to an autonomous travel solution has the consequence of weakening the intellectual, personal, social, cultural and moral development, as well as the life expectancy, of the people concerned. In this context, our team is working on the development of an optoelectronic system that secures the displacement of electric wheelchairs. This is a large project that requires the development of several functionalities such as: the anti-collision of the wheelchair with its environment, the prevention of falls from the wheelchair on uneven levels, and the adaptation of the system mechanically and electronically to the majority of commercially available electric wheelchair models, among others. In this article, we introduce our solution for detecting dangerous height differences, also called "negative obstacles", through the creation of a dedicated sensor. This sensor works by optical triangulation and can embed several laser beams in order to extend its detection zone. It has the particularity of being robust in direct sunlight and rain and has a sufficiently high measurement rate to be suitable for the displacement of electric wheelchairs. We develop an adapted algorithm, and point out compromises, in particular between the orientation of the laser beams and the maximal speed of the wheelchair.
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http://dx.doi.org/10.3390/s21196341 | DOI Listing |
Sensors (Basel)
November 2024
Human Engineering Research Laboratories, Department of VA Pittsburgh Healthcare System, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15206, USA.
: Caregivers experience high rates of occupational injuries, especially during wheelchair transfers, which often result in back pain and musculoskeletal disorders due to the physical demands of lifting and repositioning. While mechanical floor lifts, the current standard, reduce back strain, they are time-consuming and require handling techniques that subject caregivers to prolonged and repeated non-neutral trunk postures, increasing the risk of long-term back injuries. : The aim was to assess the time efficiency and ergonomics of the powered personal transfer system (PPTS), a robotic transfer device designed for bed-to/from-wheelchair transfers.
View Article and Find Full Text PDFEur Burn J
September 2024
Department of Plastic and Reconstructive Surgery, The Royal Brisbane and Women's Hospital, Brisbane 4029, Australia.
Cogn Neurodyn
October 2024
College of Electrical Engineering and Automation, Fuzhou University, Fuzhou,, 350108 Fujian China.
Currently, electroencephalogram (EEG)-based motor imagery (MI) signals have been received extensive attention, which can assist disabled subjects to control wheelchair, automatic driving and other activities. However, EEG signals are easily affected by some factors, such as muscle movements, wireless devices, power line, etc., resulting in the low signal-to-noise ratios and the worse recognition results on EEG decoding.
View Article and Find Full Text PDFAm J Phys Med Rehabil
November 2024
From the Neuro-musculoskeletal Functioning and Mobility Group, Swiss Paraplegic Research, Nottwil, Switzerland (FMB, UM, UA); Institute for Biomechanics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland (FMB); Life Course Epidemiology Group, Swiss Paraplegic Research, Nottwil, Switzerland (MWGB); Swiss Paraplegic Centre, Nottwil, Switzerland (IE-H); Faculty of Health Science and Medicine, University Lucerne, Lucerne, Switzerland (IE-H, UM, MWGB); and Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland (MS).
Sensors (Basel)
September 2024
Chair of Biomechanics, Faculty of Engineering Science, University of Bayreuth, D-95440 Bayreuth, Germany.
This review reports on the use of sensors in wheelchair sports to monitor and analyze performance during match and training time. With rapid advancements in electronics and related technologies, understanding performance metrics in wheelchair sports is essential. We reviewed nine studies using various sensor types, including electric motors, inertial measurement units, miniaturized data loggers with magnetic reed switches, and smartphones with inbuilt accelerometers and gyroscopes, operating at frequencies from 8 Hz to 1200 Hz.
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