Literature DB >> 12547361

The push force pattern in manual wheelchair propulsion as a balance between cost and effect.

L A Rozendaal1, H E J Veeger, L H V van der Woude.   

Abstract

We investigate the hypothesis that the direction of the propulsion force in manual wheelchair propulsion can be interpreted as a result of the balance between the mechanical task requirements and the driver's biomechanical possibilities. We quantify the balance at the joint level in the form of an effect-cost criterion, from which we predict the force direction that results in an optimal compromise. Kinematic and dynamic data were collected from nine habitual wheelchair users driving at four velocities (0.83, 1.11, 1.39, 1.67 m/s) and three external power levels (10, 20, 30 W). Experimental data and predictions are in good agreement in the middle and final part of the push; the effect-cost value in this region approximates the achievable maximum. Early in the push the effect-cost criterion predicts an upwards propulsion force whereas the experimental force is downwards, the difference probably being mainly attributable to the force generation dynamics of the muscles. As a result of the geometric features of large-rim manual wheelchairs, the mechanically required and biomechanically preferred force directions are not in accordance during a substantial part of the push, making even the best compromise a poor one. This may contribute to the low mechanical efficiency of manual wheelchair propulsion and the high incidence of shoulder complaints.

Mesh:

Year:  2003        PMID: 12547361     DOI: 10.1016/s0021-9290(02)00320-2

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  10 in total

1.  Shoulder and elbow joint power differ as a general feature of vertical arm movements.

Authors:  J C Galloway; A Bhat; J C Heathcock; K Manal
Journal:  Exp Brain Res       Date:  2004-06-26       Impact factor: 1.972

2.  Hand rim wheelchair propulsion training using biomechanical real-time visual feedback based on motor learning theory principles.

Authors:  Ian Rice; Dany Gagnon; Jere Gallagher; Michael Boninger
Journal:  J Spinal Cord Med       Date:  2010       Impact factor: 1.985

3.  The influence of altering push force effectiveness on upper extremity demand during wheelchair propulsion.

Authors:  Jeffery W Rankin; Andrew M Kwarciak; W Mark Richter; Richard R Neptune
Journal:  J Biomech       Date:  2010-08-02       Impact factor: 2.712

4.  Shoulder model validation and joint contact forces during wheelchair activities.

Authors:  Melissa M B Morrow; Kenton R Kaufman; Kai-Nan An
Journal:  J Biomech       Date:  2010-06-08       Impact factor: 2.712

5.  A comparison of static and dynamic optimization muscle force predictions during wheelchair propulsion.

Authors:  Melissa M Morrow; Jeffery W Rankin; Richard R Neptune; Kenton R Kaufman
Journal:  J Biomech       Date:  2014-09-23       Impact factor: 2.712

6.  Early motor learning changes in upper-limb dynamics and shoulder complex loading during handrim wheelchair propulsion.

Authors:  Riemer J K Vegter; Johanneke Hartog; Sonja de Groot; Claudine J Lamoth; Michel J Bekker; Jan W van der Scheer; Lucas H V van der Woude; Dirkjan H E J Veeger
Journal:  J Neuroeng Rehabil       Date:  2015-03-10       Impact factor: 4.262

7.  Scoping review of the rolling resistance testing methods and factors that impact manual wheelchairs.

Authors:  Joseph Ott; Jonathan Pearlman
Journal:  J Rehabil Assist Technol Eng       Date:  2021-01-31

8.  A Dynamic Wheelchair Armrest for Promoting Arm Exercise and Mobility After Stroke.

Authors:  Marti Comellas; Vicky Chan; Daniel K Zondervan; David J Reinkensmeyer
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2022-07-14       Impact factor: 4.528

9.  Effect of Haptic Training During Manual Wheelchair Propulsion on Shoulder Joint Reaction Moments.

Authors:  Rachid Aissaoui; Dany Gagnon
Journal:  Front Rehabil Sci       Date:  2022-04-05

10.  Estimation of manual wheelchair-based activities in the free-living environment using a neural network model with inertial body-worn sensors.

Authors:  Emma Fortune; Beth A Cloud-Biebl; Stefan I Madansingh; Che G Ngufor; Meegan G Van Straaten; Brianna M Goodwin; Dennis H Murphree; Kristin D Zhao; Melissa M Morrow
Journal:  J Electromyogr Kinesiol       Date:  2019-07-17       Impact factor: 2.368

  10 in total

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