In wheelchair sports, there is an increasing need to monitor mechanical power in the field. When rolling resistance is known, inertial measurement units (IMUs) can be used to determine mechanical power. However, upper body (i.e., trunk) motion affects the mass distribution between the small front and large rear wheels, thus affecting rolling resistance. Therefore, drag tests – which are commonly used to estimate rolling resistance – may not be valid. The aim of this study was to investigate the influence of trunk motion on mechanical power estimates in hand-rim wheelchair propulsion by comparing instantaneous resistance-based power loss with drag test-based power loss. Experiments were performed with no, moderate and full trunk motion during wheelchair propulsion. During these experiments, power loss was determined based on 1) the instantaneous rolling resistance and 2) based on the rolling resistance determined from drag tests (thus neglecting the effects of trunk motion). Results showed that power loss values of the two methods were similar when no trunk motion was present (mean difference [MD] of 0.6 1.6 %). However, drag test-based power loss was underestimated up to −3.3 2.3 % MD when the extent of trunk motion increased (r = 0.85). To conclude, during wheelchair propulsion with active trunk motion, neglecting the effects of trunk motion leads to an underestimated mechanical power of 1 to 6 % when it is estimated with drag test values. Depending on the required accuracy and the amount of trunk motion in the target group, the influence of trunk motion on power estimates should be corrected for.
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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.
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PURPOSE: Athletes require feedback in order to comply with prescribed training programs designed to optimize their performance. In rowing, current feedback parameters on intensity are inaccurate. Mechanical power output is a suitable objective measure for training intensity, but due to movement restrictions related to crew rowing, it is uncertain whether crew rowers are able to adjust their intensity based on power-output feedback. The authors examined whether rowers improve compliance with prescribed power-output targets when visual real-time feedback on power output is provided in addition to commonly used feedback.METHODS: A total of 16 crew rowers rowed in 3 training sessions. During the first 2 sessions, they received commonly used feedback, followed by a session with additional power-output feedback. Targets were set by their coaches before the experiment. Compliance was operationalized as accuracy (absolute difference between target and delivered power output) and consistency (high- and low-frequency variations in delivered power output).RESULTS: Multilevel analyses indicated that accuracy and low-frequency variations improved by, respectively, 65% (P > .001) and 32% (P = .024) when additional feedback was provided.CONCLUSION: Compliance with power-output targets improved when crew rowers received additional feedback on power output. Two additional observations were made during the study that highlighted the relevance of power-output feedback for practice: There was a marked discrepancy between the prescribed targets and the actually delivered power output by the rowers, and coaches had difficulties perceiving improvements in rowers' compliance with power-output targets.
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Currently, many novel innovative materials and manufacturing methods are developed in order to help businesses for improving their performance, developing new products, and also implement more sustainability into their current processes. For this purpose, additive manufacturing (AM) technology has been very successful in the fabrication of complex shape products, that cannot be manufactured by conventional approaches, and also using novel high-performance materials with more sustainable aspects. The application of bioplastics and biopolymers is growing fast in the 3D printing industry. Since they are good alternatives to petrochemical products that have negative impacts on environments, therefore, many research studies have been exploring and developing new biopolymers and 3D printing techniques for the fabrication of fully biobased products. In particular, 3D printing of smart biopolymers has attracted much attention due to the specific functionalities of the fabricated products. They have a unique ability to recover their original shape from a significant plastic deformation when a particular stimulus, like temperature, is applied. Therefore, the application of smart biopolymers in the 3D printing process gives an additional dimension (time) to this technology, called four-dimensional (4D) printing, and it highlights the promise for further development of 4D printing in the design and fabrication of smart structures and products. This performance in combination with specific complex designs, such as sandwich structures, allows the production of for example impact-resistant, stress-absorber panels, lightweight products for sporting goods, automotive, or many other applications. In this study, an experimental approach will be applied to fabricate a suitable biopolymer with a shape memory behavior and also investigate the impact of design and operational parameters on the functionality of 4D printed sandwich structures, especially, stress absorption rate and shape recovery behavior.
Most trailer units currently lack a drivetrain to assist the truck. Given that trailers carry heavy loads, significant power is required to propel them especially during acceleration. Equipping trailers with an electric powertrain can help support the truck during traction and regenerate energy during braking, reducing emissions and energy consumption. This also is in line with the CO2 emissions goal of the European Green Deal for heavy duty vehicles . By utilizing a king-pin, the e-trailer can determine the level of support needed, making it fully independent. Currently, a measurement system for measuring forces on the king-pin is being developed. Using the information of forces, the support by the e-trailer during traction can be defined along with the recaptured energy during braking. Although, it will work in longitudinal direction but has its limitations when a lateral force is acting; like during cornering, road camber, turning etc. In reality, vehicles do not only drive in straight line, so dynamics of the vehicle have a significance role. If the support provided by e-trailer during lateral movement of the vehicle is not controlled, it may have an effect on the general ride and handling outside the longitudinal scenarios and in extreme cases lead to dangerous situations (like jack-knifing). Thus, for refine and safe drivability of the truck-e-trailer combination additional information on the manoeuvring status of the truck e-trailer combination is required. This added information will improvise controllability of the e-trailer and provide a safety net over the already defined e-trailer controls in a longitudinal direction, making basic movements involving lateral direction possible. It is proposed to integrate the articulation angle information, such that the complex electro-mechanical system of the e-tailer driveline can recognize the dynamic movements to help refine the control and ensure safety. Validation will be performed in Hardware-in-loop environment.
The demand for mobile agents in industrial environments to perform various tasks is growing tremendously in recent years. However, changing environments, security considerations and robustness against failure are major persistent challenges autonomous agents have to face when operating alongside other mobile agents. Currently, such problems remain largely unsolved. Collaborative multi-platform Cyber- Physical-Systems (CPSs) in which different agents flexibly contribute with their relative equipment and capabilities forming a symbiotic network solving multiple objectives simultaneously are highly desirable. Our proposed SMART-AGENTS platform will enable flexibility and modularity providing multi-objective solutions, demonstrated in two industrial domains: logistics (cycle-counting in warehouses) and agriculture (pest and disease identification in greenhouses). Aerial vehicles are limited in their computational power due to weight limitations but offer large mobility to provide access to otherwise unreachable places and an “eagle eye” to inform about terrain, obstacles by taking pictures and videos. Specialized autonomous agents carrying optical sensors will enable disease classification and product recognition improving green- and warehouse productivity. Newly developed micro-electromechanical systems (MEMS) sensor arrays will create 3D flow-based images of surroundings even in dark and hazy conditions contributing to the multi-sensor system, including cameras, wireless signatures and magnetic field information shared among the symbiotic fleet. Integration of mobile systems, such as smart phones, which are not explicitly controlled, will provide valuable information about human as well as equipment movement in the environment by generating data from relative positioning sensors, such as wireless and magnetic signatures. Newly developed algorithms will enable robust autonomous navigation and control of the fleet in dynamic environments incorporating the multi-sensor data generated by the variety of mobile actors. The proposed SMART-AGENTS platform will use real-time 5G communication and edge computing providing new organizational structures to cope with scalability and integration of multiple devices/agents. It will enable a symbiosis of the complementary CPSs using a combination of equipment yielding efficiency and versatility of operation.
