Background: Powered wheelchairs are an essential technology to support mobility, yet their use is associated with a high level of sedentarism that can have negative health effects for their users. People with Duchenne muscular dystrophy (DMD) start using a powered wheelchair in their early teens due to the loss of strength in their legs and arms. There is evidence that low-intensity exercise can help preserve the functional abilities of people with DMD, but options for exercise when sitting in a powered wheelchair are limited.
Methods: In this paper, we present the design and the feasibility study of a new version of the MOVit device that allows powered-wheelchair users to exercise while driving the chair. Instead of using a joystick to drive the wheelchair, users move their arms through a cyclical motion using two powered, mobile arm supports that provide controller inputs to the chair. The feasibility study was carried out with a group of five individuals with DMD and five unimpaired individuals. Participants performed a series of driving tasks in a wheelchair simulator and on a real driving course with a standard joystick and with the MOVit 2.0 device.
Results: We found that driving speed and accuracy were significantly lowered for both groups when driving with MOVit compared to the joystick, but the decreases were small (speed was 0.26 m/s less and maximum path error was 0.1 m greater). Driving with MOVit produced a significant increase in heart rate (7.5 bpm) compared to the joystick condition. Individuals with DMD reported a high level of satisfaction with their performance and comfort in using MOVit.
Conclusions: These results show for the first time that individuals with DMD can easily transition to driving a powered wheelchair using cyclical arm motions, achieving a reasonable driving performance with a short period of training. Driving in this way elicits cardiopulmonary exercise at an intensity found previously to produce health-related benefits in DMD.
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http://dx.doi.org/10.1186/s12984-020-00760-9 | DOI Listing |
Pediatr Phys Ther
January 2025
Parent of a child with CP, GMCS IV who explored power mobility from age 12 months and is now an independent power wheelchair user.
Assist Technol
December 2024
School of Occupational Therapy, Faculty of Health, Dalhousie University, Nova Scotia, Canada.
This study translated and culturally adapted the Wheelchair Use Confidence Scale for Manual Wheelchair Users (WheelCon-M) and the Wheelchair Use Confidence Scale for Power Wheelchair Users (WheelCon-P) into Arabic and examined their reliability and validity. Internal consistency and test-retest reliability were examined, and concurrent validity was evaluated using Pearson correlation coefficients with the Arabic versions of the Functioning Everyday with a Wheelchair (FEW) and the Functional Mobility Assessment (FMA). The Arabic translated versions of the WheelCon-M (WheelCon-M-A) and the WheelCon-P (WheelCon-P-A) were administered to 33 adult wheelchair users.
View Article and Find Full Text PDFSensors (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.
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