Literature DB >> 24800451

The development of an instrumented wheelchair propulsion testing and training device.

Joseph Klaesner, Kerri A Morgan, David B Gray.   

Abstract

Researchers have used several types of testing devices and training surfaces to examine wheelchair propulsion. Testing and training wheelchair users on the actual surface of interest, such as tile floors or ramps, is ideal but difficult. Devices such as treadmills, dynamometers, and ergometers allow for researchers and clinicians to observe wheelchair users in a controlled space. However, these devices often do not have the ability to realistically simulate the environment. This methodological article describes the instrumentation, development and function of a wheelchair dynamometer system, the WheelMill System (WMS), a uniquely adjustable roller system for wheelchairs. Three participants wheeled on the WMS, over a tile surface and up two different graded slopes with the SmartWheel to compare speed and forces. The WMS reasonably simulated propulsion over a tile floor, though the participants' speed was slightly faster on tile, and the peak forces for each propulsion stroke varied more on tile than on the WMS. For the slopes, the speed oscillated over a greater range and was slower, and the measured peak forces were higher than the values measured on the WMS. The WMS may have several applications, though additional studies on a greater and more diverse population are needed.

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Mesh:

Year:  2014        PMID: 24800451     DOI: 10.1080/10400435.2013.792020

Source DB:  PubMed          Journal:  Assist Technol        ISSN: 1040-0435


  4 in total

1.  Exercise testing protocol using a roller system for manual wheelchair users with spinal cord injury.

Authors:  Kerri A Morgan; Kelly L Taylor; Susan M Tucker; W Todd Cade; Joseph W Klaesner
Journal:  J Spinal Cord Med       Date:  2018-03-08       Impact factor: 1.985

2.  A motor learning approach to training wheelchair propulsion biomechanics for new manual wheelchair users: A pilot study.

Authors:  Kerri A Morgan; Susan M Tucker; Joseph W Klaesner; Jack R Engsberg
Journal:  J Spinal Cord Med       Date:  2015-12-16       Impact factor: 1.985

3.  Toward community-based wheelchair evaluation with machine learning methods.

Authors:  Pin-Wei B Chen; Kerri Morgan
Journal:  J Rehabil Assist Technol Eng       Date:  2018-12-17

4.  Physiological and biomechanical comparison of overground, treadmill, and ergometer handrim wheelchair propulsion in able-bodied subjects under standardized conditions.

Authors:  Rick de Klerk; Vera Velhorst; Dirkjan H E J Veeger; Lucas H V van der Woude; Riemer J K Vegter
Journal:  J Neuroeng Rehabil       Date:  2020-10-17       Impact factor: 4.262

  4 in total

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