Search

Purpose:Wheelchair locomotion is constraining for the upper limbs and involves a set of motor tasks that need to be learnt by a novice user. To understand this integration process, we investigated the evolution of shoulder kinetics during start-up and propulsion within the initial phase of low-intensity uninstructed training. Materials and methods:Seventeen novice able-bodied subjects performed a 120-min uninstructed practice distributed over 4 weeks. During the initial and final sessions, upper limbs kinematics and hand-rim kinetics were continuously collected. Inverse kinematics and dynamics coupled to a three-dimensional linked-segment model were used to compute shoulder net moments. Results:Participants increased the speed of the wheelchair with practice. In average, an increase of shoulder net moments and mechanical work during the push phase was observed. Conversely, during the recovery phase, participants slightly increased shoulder power but maintained a similar level of shoulder loading. However, individual evolutions allowed the definition of two groups defined as: “increasers”, who increased shoulder loading and mechanical work versus “decreasers”, who managed to limit shoulder loading while improving the wheelchair speed. Conclusion:These findings underline that individual adaptation strategies are essential to take into account when designing a rehabilitation protocol for wheelchair users. Implications for RehabilitationThe learning process of manual wheelchair locomotion is essential for the assimilation of motor tasks leading individuals to select their propulsion technique.Novice users display different learning strategies: some people increase shoulder loading very early but others spontaneously manage to increase the wheelchair speed while maintaining a constant level of shoulder loading.Wheelchair rehabilitation programs should be individualized to take into account the subject-specific learning strategy. [ABSTRACT FROM PUBLISHER]

A six-component handrim dynamometer (HRD) is a dynamometer that rotates around the wheel axle during measurements. For this kind of dynamometer, static zero level calibration is insufficient because the proportion of the forces (i.e. handrim weight and centrifugal force) measured by each sensor varies according to the angular position and velocity of the dynamometer. The dynamic calibration presented in this paper is based on the direct correction of the sensor signals using Fourier's polynomials that take into account the influences of both the handrim weight distribution on the sensors with respect to the wheel's angular position and the effect of the wheel's angular velocity. When these corrections were applied to the signals produced by the sensors while the HRD was rotating and no effort was being exerted on the handrim, the calculated forces and torques remained close to zero, as expected. Based on these results, the wheel dynamometer can be confidently used for studying manual wheelchair locomotion under various real conditions. The method could also be applied in other situations in which a dynamometer rotates during measurements. [ABSTRACT FROM AUTHOR]

This article proposes a simple and convenient method for assessing the subject-specific rolling resistance acting on a manual wheelchair, which could be used during the provision of clinical service. This method, based on a simple mathematical equation, is sensitive to both the total mass and its fore-aft distribution, which changes with the subject, wheelchair properties, and adjustments. The rolling resistance properties of three types of front casters and four types of rear wheels were determined for two indoor surfaces commonly encountered by wheelchair users (a hard smooth surface and carpet) from measurements of a three-dimensional accelerometer during field deceleration tests performed with artificial load. The average results provided by these experiments were then used as input data to assess the rolling resistance from the mathematical equation with an acceptable accuracy on hard smooth and carpet surfaces (standard errors of the estimates were 4.4 and 3.9 N, respectively). Thus, this method can be confidently used by clinicians to help users make trade-offs between front and rear wheel types and sizes when choosing and adjusting their manual wheelchair. [ABSTRACT FROM AUTHOR]