Providing real-time feedback to improve speed skating performance.

The quantification of mechanical power can provide valuable insight into athlete performance because it is the mechanical principle of the rate at which the athlete does work or transfers energy to complete a movement task. Estimates of power are usually limited by the capabilities of measurement systems, resulting in the use of simplified power models. This review provides a systematic overview of the studies on mechanical power in sports, discussing the application and estimation of mechanical power, the consequences of simplifications, and the terminology. The mechanical power balance consists of five parts, where joint power is equal to the sum of kinetic power, gravitational power, environmental power, and frictional power. Structuring literature based on these power components shows that simplifications in models are done on four levels, single vs multibody models, instantaneous power (IN) versus change in energy (EN), the dimensions of a model (1D, 2D, 3D), and neglecting parts of the mechanical power balance. Quantifying the consequences of simplification of power models has only been done for running, and shows differences ranging from 10% up to 250% compared to joint power models. Furthermore, inconsistency and imprecision were found in the determination of joint power, resulting from inverse dynamics methods, incorporation of translational joint powers, partitioning in negative and positive work, and power flow between segments. Most inconsistency in terminology was found in the definition and application of ‘external’ and ‘internal’ work and power. Sport research would benefit from structuring the research on mechanical power in sports and quantifying the result of simplifications in mechanical power estimations.

Objective: Sport research often requires human motion capture of an athlete. It can, however, be labour-intensive and difficult to select the right system, while manufacturers report on specifications which are determined in set-ups that largely differ from sport research in terms of volume, environment and motion. The aim of this review is to assist researchers in the selection of a suitable motion capture system for their experimental set-up for sport applications. An open online platform is initiated, to support (sport)researchers in the selection of a system and to enable them to contribute and update the overview. Design: systematic review; Method: Electronic searches in Scopus, Web of Science and Google Scholar were performed, and the reference lists of the screened articles were scrutinised to determine human motion capture systems used in academically published studies on sport analysis. Results: An overview of 17 human motion capture systems is provided, reporting the general specifications given by the manufacturer (weight and size of the sensors, maximum capture volume, environmental feasibilities), and calibration specifications as determined in peer-reviewed studies. The accuracy of each system is plotted against the measurement range. Conclusion: The overview and chart can assist researchers in the selection of a suitable measurement system. To increase the robustness of the database and to keep up with technological developments, we encourage researchers to perform an accuracy test prior to their experiment and to add to the chart and the system overview (online, open access).

This study performed an analysis of the push-off forces of elite-short-track speed skaters using a new designed instrumented short-track speed skate with the aim to improve short-track skating performance. Four different skating strokes were distinguished for short-track speed skaters at speed. The strokes differed in stroke time, force level in both normal and lateral directions, and the centre of pressure (COP) on the blade. Within the homogeneous group of male elite speed skaters (N = 6), diversity of execution of the force patterns in the four phases of skating was evident, while skating at the same velocities. The male participants (N = 6) with a better personal record (PR) kept the COP more to the rear of their blades while hanging into the curve (r = 0.82, p < 0.05), leaving the curve (r = 0.86, p < 0.05), and entering the straight (r = 0.76, p < 0.10). Furthermore, the male skaters with a better PR showed a trend of a lower lateral peak force while entering the curve (r = 0.74, p < 0.10). Females showed a trend towards applying higher body weight normalised lateral forces than the males, while skating at imposed lower velocities.

Although speed skating has existed for centuries, it is not yet clear what the optimal skating technique actually is. Skating is a motion with many interconnected variables, and there seem to be different optimal techniques for different speed skaters. The aim of this dissertation is to determine the interconnectivity of technique variables and performance determining variables within a skating stroke by measuring and modelling the speed skating motion, which eventually can be used for real-time feedback in speed skating training. This is done by the development and verification of a simple 3D biomechanical skater model that simulates the skating motion, and developing new instrumented klapskates to measure the push-off forces. To analyse the mechanical power, a well-known performance characteristic, a mechanical power model of a speed skater is developed.

In gait studies body pose reconstruction (BPR) techniques have been widely explored, but no previous protocols have been developed for speed skating, while the peculiarities of the skating posture and technique do not automatically allow for the transfer of the results of those explorations to kinematic skating data. The aim of this paper is to determine the best procedure for body pose reconstruction and inverse dynamics of speed skating, and to what extend this choice influences the estimation of joint power. The results show that an eight body segment model together with a global optimization method with revolute joint in the knee and in the lumbosacral joint, while keeping the other joints spherical, would be the most realistic model to use for the inverse kinematics in speed skating. To determine joint power, this method should be combined with a least-square error method for the inverse dynamics. Reporting on the BPR technique and the inverse dynamic method is crucial to enable comparison between studies. Our data showed an underestimation of up to 74% in mean joint power when no optimization procedure was applied for BPR and an underestimation of up to 31% in mean joint power when a bottom-up inverse dynamics method was chosen instead of a least square error approach. Although these results are aimed at speed skating, reporting on the BPR procedure and the inverse dynamics method, together with setting a golden standard should be common practice in all human movement research to allow comparison between studies.

In gait studies body pose reconstruction (BPR) techniques have been widely explored, but no previous protocols have been developed for speed skating, while the peculiarities of the skating posture and technique do not automatically allow for the transfer of the results of those explorations to kinematic skating data. The aim of this paper is to determine the best procedure for body pose reconstruction and inverse dynamics of speed skating, and to what extend this choice influences the estimation of joint power. The results show that an eight body segment model together with a global optimization method with revolute joint in the knee and in the lumbosacral joint, while keeping the other joints spherical, would be the most realistic model to use for the inverse kinematics in speed skating. To determine joint power, this method should be combined with a least-square error method for the inverse dynamics. Reporting on the BPR technique and the inverse dynamic method is crucial to enable comparison between studies. Our data showed an underestimation of up to 74% in mean joint power when no optimization procedure was applied for BPR and an underestimation of up to 31% in mean joint power when a bottom-up inverse dynamics method was chosen instead of a least square error approach. Although these results are aimed at speed skating, reporting on the BPR procedure and the inverse dynamics method, together with setting a golden standard should be common practice in all human movement research to allow comparison between studies.

To assist speed skaters in improving their skating performance, we would like to provide them with real time feedback on the orientation of the skate within a single stroke. While of course the forces generated by the skater on the ice determine the acceleration of the skater, the orientation of the skate determines in which direction this force, and thus acceleration, is headed. In this study we focus on the validation of the lean angle measurements of the skate, which distributes the push-off forces over the global vertical and transverse component. To measure this angle, an inertial measurement unit (IMU) would be a logical choice, but two aspects render measuring with commercially available IMUs and their filters on an ice rink rather difficult, first the ferromagnetic materials in the vicinity of the IMU and secondly the large linear accelerations. In this paper we therefore propose filters that bypass these problems. In total three complementary filters with adaptive gain were validated with a motion capture system. The filter based on the assumption that the lean angle can be reset to zero (upright) when there is no change in steer angle of the skate, showed the most accurate results (mean RMSE error of 5.30 and 3.60, for the left and right skate respectively). Integrated into the filter is an IMU based stroke detection, which as a stand-alone system could provide feedback on stroke frequency, stroke length, contact time or double stance phase time. It is concluded that an IMU used with this filter can provide individual elite speed skaters reliable feedback on their skate lean angle.

Advice about the optimal coordination pattern for an individual speed skater, could be addressed by simulation and optimization of a biomechanical speed skating model. But before getting to this optimization approach one needs a model that can reasonably match observed behaviour. Therefore, the objective of this study is to present a verified three dimensional inverse skater model with minimal complexity, which models the speed skating motion on the straights. The model simulates the upper body transverse translation of the skater together with the forces exerted by the skates on the ice. The input of the model is the changing distance between the upper body and the skate, referred to as the leg extension (Euclidean distance in 3D space). Verification shows that the model mimics the observed forces and motions well. The model is most accurate for the position and velocity estimation (respectively 1.2% and 2.9% maximum residuals) and least accurate for the force estimations (underestimation of 4.5-10%). The model can be used to further investigate variables in the skating motion. For this, the input of the model, the leg extension, can be optimized to obtain a maximal forward velocity of the upper body.

In the current project we aim to provide speed skaters with real-time feedback on how to improve their skating performance within an individual stroke. The elite skaters and their coaches wish for a system that determines the mechanical power per stroke. The push-off force of the skater is a crucial variable in this power determination. In this study we present the construction and calibration of a pair of wireless instrumented klapskates that can continuously and synchronously measure this push-off force in both the lateral and normal direction of the skate and the centre of pressure of these forces. The skate consists of a newly designed rigid bridge (0.6 kg), embedding two three-dimensional force sensors (Kistler 9602, Kistler Group, Winterthur, Switzerland), which fits between most individual skate shoes and Maple skate blades. The instrumented klapskates were calibrated on a tensile testing machine, where they proved to be unaffected to temperature conditions and accurate up to a RMS of 42 N (SEM = 1 N) in normal and up to a RMS of 27 N (SEM = 1N) in lateral direction. Furthermore the centre of pressure of these forces on the blade was determined up to a mean error of 10.1 mm (SD = 6.9 mm). On-ice measurements showed the possibility of recording with both skates simultaneously and synchronously, straights as well as curves The option to send data wirelessly and real-time to other devices makes it possible to eventually provide skaters and coaches with visual real-time feedback during practice.

To assist speed skaters in improving their skating performance, we would like to provide them with real time feedback on the orientation of the skate within a single stroke. While of course the forces generated by the skater on the ice determine the acceleration of the skater, the orientation of the skate determines in which direction this force, and thus acceleration, is headed. In this study we focus on the validation of the lean angle measurements of the skate, which distributes the push-off forces over the global vertical and transverse component. To measure this angle, an inertial measurement unit (IMU) would be a logical choice, but two aspects render measuring with commercially available IMUs and their filters on an ice rink rather difficult, first the ferromagnetic materials in the vicinity of the IMU and secondly the large linear accelerations. In this paper we therefore propose filters that bypass these problems. In total three complementary filters with adaptive gain were validated with a motion capture system. The filter based on the assumption that the lean angle can be reset to zero (upright) when there is no change in steer angle of the skate, showed the most accurate results (mean RMSE error of 5.3 deg and 3.6 deg , for the left and right skate respectively). Integrated into the filter is an IMU based stroke detection, which as a stand-alone system could provide feedback on stroke frequency, stroke length, contact time or double stance phase time. It is concluded that an IMU used with this filter can provide individual elite speed skaters reliable feedback on their skate lean angle.