The aim of this explorative study was to determine the key inertial measurement unit-based wheelchair mobility performance components during a wheelchair tennis match. A total of 64 wheelchair tennis matches were played by 15 wheelchair tennis players (6 women, 5 men, 4 juniors). All individual tennis wheelchairs were instrumented with inertial measurement units, two on the axes of the wheels and one on the frame. A total of 48 potentially relevant wheelchair tennis outcome variables were initially extracted from the sensor signals, based on previous wheelchair sports research and the input of wheelchair tennis experts (coaches, embedded scientists). A principal component analysis was used to reduce this set of variables to the most relevant outcomes for wheelchair tennis mobility. Results showed that wheelchair mobility performance in wheelchair tennis can be described by six components: rotations to racket side in (1) curves and (2) turns; (3) linear accelerations; (4) rotations to non-racket side in (4) turns and (5) curves; and finally, (6) linear velocities. One or two outcome variables per component were selected to allow an easier interpretation of results. These key outcome variables can be used to adequately describe the wheelchair mobility performance aspect of wheelchair tennis during a wheelchair tennis match and can be monitored during training.
Daily wheelchair ambulation is seen as a risk factor for shoulder problems, which are prevalent in manual wheelchair users. To examine the long-term effect of shoulder load from daily wheelchair ambulation on shoulder problems, quantification is required in real-life settings. In this study, we describe and validate a comprehensive and unobtrusive methodology to derive clinically relevant wheelchair mobility metrics (WCMMs) from inertial measurement systems (IMUs) placed on the wheelchair frame and wheel in real-life settings. The set of WCMMs includes distance covered by the wheelchair, linear velocity of the wheelchair, number and duration of pushes, number and magnitude of turns and inclination of the wheelchair when on a slope. Data are collected from ten able-bodied participants, trained in wheelchair-related activities, who followed a 40 min course over the campus. The IMU-derived WCMMs are validated against accepted reference methods such as Smartwheel and video analysis. Intraclass correlation (ICC) is applied to test the reliability of the IMU method. IMU-derived push duration appeared to be less comparable with Smartwheel estimates, as it measures the effect of all energy applied to the wheelchair (including thorax and upper extremity movements), whereas the Smartwheel only measures forces and torques applied by the hand at the rim. All other WCMMs can be reliably estimated from real-life IMU data, with small errors and high ICCs, which opens the way to further examine real-life behavior in wheelchair ambulation with respect to shoulder loading. Moreover, WCMMs can be applied to other applications, including health tracking for individual interest or in therapy settings.
An important performance determinant in wheelchair sports is the power exchanged between the athletewheelchair combination and the environment, in short, mechanical power. Inertial measurement units (IMUs) might be used to estimate the exchanged mechanical power during wheelchair sports practice. However, to validly apply IMUs for mechanical power assessment in wheelchair sports, a well-founded and unambiguous theoretical framework is required that follows the dynamics of manual wheelchair propulsion. Therefore, this research has two goals. First, to present a theoretical framework that supports the use of IMUs to estimate power output via power balance equations. Second, to demonstrate the use of the IMU-based power estimates during wheelchair propulsion based on experimental data. Mechanical power during straight-line wheelchair propulsion on a treadmill was estimated using a wheel mounted IMU and was subsequently compared to optical motion capture data serving as a reference. IMU-based power was calculated from rolling resistance (estimated from drag tests) and change in kinetic energy (estimated using wheelchair velocity and wheelchair acceleration). The results reveal no significant difference between reference power values and the proposed IMU-based power (1.8% mean difference, N.S.). As the estimated rolling resistance shows a 0.9–1.7% underestimation, over time, IMU-based power will be slightly underestimated as well. To conclude, the theoretical framework and the resulting IMU model seems to provide acceptable estimates of mechanical power during straight-line wheelchair propulsion in wheelchair (sports) practice, and it is an important first step towards feasible power estimations in all wheelchair sports situations.
