From theory to practice: Monitoring mechanical power output during wheelchair field and court sports using inertial measurement units

van Dijk, Marit P.; Hoozemans, Marco J.M.; Berger, Monique A.M.; Veeger, H.E.J.

doi:10.1016/j.jbiomech.2024.112052

Cited by 2 publications

(6 citation statements)

References 45 publications

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“…However, Fy is certainly valuable for understanding the dynamics of the moving masses, but it has no effect on the propulsive force (Figure 13a). Calculations of athlete power and energy expenditure should be based on the propulsive force only, as the power values obtained from velocity profiles (Figure 7a), acceleration profiles (Figure 10), and system mass significantly overestimate the power, as noted by van Dijk et al [19]. Particularly, the wheelchair user's positive power should be calculated only from the pure propulsive force that is required in the push phase to overcome the dissipative forces and that enables the gain or loss in speed per stroke cycle, but not directly from the measured velocity.…”

Section: Discussionmentioning

confidence: 82%

“…Nowadays the speed v in wheelchair sports is conveniently measured with IMUs (gyro component); previously, it was measured using optical encoders [20] and electric DC motors/generators [17]. Van Dijk et al [19] claimed that "Air resistance can be neglected during indoor wheelchair field and court sports". They support their claim with the argument that "As these [court] sports consist of short sprints and lots of braking, the wheelchair velocities are generally below 2.5 m/s" (9 kph).…”

Section: Discussionmentioning

confidence: 99%

“…DF and RF were determined simultaneously from coast-down experiments [7,17,18]. Van Dijk et al [19] claimed that "the information required to calculate air resistance cannot be derived from IMU data". However, when solving the differential equation of a coasting wheelchair [17], we obtained the following solution:…”

Section: Wheelchair Model With Moving Massesmentioning

confidence: 99%

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The Effect of Arm Movements on the Dynamics of the Wheelchair Frame during Manual Wheelchair Actuation and Propulsion

Fuss,

Tan,

Weizman

2024

Actuators

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Wheelchair propulsion and actuation are influenced by the moving masses of the wheelchair user; however, the extent of this effect is still unclear. The main evidence of this effect is that the speed of the wheelchair frame continues to increase after the end of the push phase. The wheelchair’s speed was measured using IMUs and the duration of the push period was recorded using miniaturised pressure sensors attached to the driver’s middle fingers. The velocity and acceleration were determined for various average stroke cycle speeds to determine the speed dependency of the acceleration. The wheelchair was then mounted on a force plate to measure the inertial forces of the hands moving back and forth. The aerodynamic drag and rolling resistance forces were determined from coast-down experiments. Based on the measured forces, the behaviour of the force and velocity profiles was finally modelled by gradually reducing the mass of the arms and thus their inertial force. The results showed that the wheelchair is accelerated throughout the push phase (except for a temporary deceleration in the middle of the push phase at higher velocities), and that this acceleration continues well after the push phase. In the second half of the recovery phase, the wheelchair decelerates. The horizontal inertial forces measured on the force plate are predominantly negative in the push phase and in the second half of the recovery phase, and positive in the first half of the push phase, and their impulse is zero due to the conservation of momentum. Modelling the wheelchair with moving masses showed that reducing the horizontal inertial forces has no effect on the driver’s propulsive force but reduces the velocity fluctuations. The main conclusion of this research is that the wheelchair user’s power should be calculated only from the pure propulsive force that is required in the push phase to overcome the dissipative forces and that enables the gain or loss in speed per stroke cycle, but not directly from the measured velocity.

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Section: Discussionmentioning

confidence: 82%

Section: Discussionmentioning

confidence: 99%

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The Effect of Arm Movements on the Dynamics of the Wheelchair Frame during Manual Wheelchair Actuation and Propulsion

Fuss,

Tan,

Weizman

2024

Actuators

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“…When the deceleration is known and the wheelchair user does not move, the rolling resistance can be determined from this deceleration and the total mass. However, recent studies (van Dijk MP et al, 2024 ; van Dijk et al, 2024 ) report a difference between rolling resistance during propulsion and that obtained during these commonly used tests.…”

Section: Introductionmentioning

confidence: 97%

“…Rolling resistance is an important resistive force in hand-rim wheelchair propulsion and can vary significantly between wheelchairs, tyres and surface types (de Klerk et al, 2020 ; Ott & Pearlman, 2021 ; Rietveld et al, 2021 ; van der Woude et al, 2003 ). Accurately assessing rolling resistance is crucial to estimate power output (de Klerk et al, 2020 ; van Dijk et al, 2024 ) or to optimize wheelchair settings (Ott & Pearlman, 2021 ). For this assessment, a drag or deceleration test is commonly used.…”

Section: Introductionmentioning

confidence: 99%

Towards an accurate rolling resistance: Estimating intra-cycle load distribution between front and rear wheels during wheelchair propulsion from inertial sensors

van Dijk,

Heringa,

Berger

et al. 2024

Journal of Sports Sciences

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Accurate assessment of rolling resistance is important for wheelchair propulsion analyses. However, the commonly used drag and deceleration tests are reported to underestimate rolling resistance up to 6% due to the (neglected) influence of trunk motion. The first aim of this study was to investigate the accuracy of using trunk and wheelchair kinematics to predict the intra-cyclical load distribution, more particularly front wheel loading, during hand-rim wheelchair propulsion. Secondly, the study compared the accuracy of rolling resistance determined from the predicted load distribution with the accuracy of drag test-based rolling resistance. Twenty-five able-bodied participants performed hand-rim wheelchair propulsion on a large motor-driven treadmill. During the treadmill sessions, front wheel load was assessed with load pins to determine the load distribution between the front and rear wheels. Accordingly, a machine learning model was trained to predict front wheel load from kinematic data. Based on two inertial sensors (attached to the trunk and wheelchair) and the machine learning model, front wheel load was predicted with a mean absolute error (MAE) of 3.8% (or 1.8 kg). Rolling resistance determined from the predicted load distribution (MAE: 0.9%, mean error (ME): 0.1%) was more accurate than drag test-based rolling resistance (MAE: 2.5%, ME: −1.3%).

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From theory to practice: Monitoring mechanical power output during wheelchair field and court sports using inertial measurement units

Cited by 2 publications

References 45 publications

The Effect of Arm Movements on the Dynamics of the Wheelchair Frame during Manual Wheelchair Actuation and Propulsion

The Effect of Arm Movements on the Dynamics of the Wheelchair Frame during Manual Wheelchair Actuation and Propulsion

Towards an accurate rolling resistance: Estimating intra-cycle load distribution between front and rear wheels during wheelchair propulsion from inertial sensors

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