Three-Dimensional Body and Centre of Mass Kinematics in Alpine Ski Racing Using Differential GNSS and Inertial Sensors

A key point in human movement analysis is measuring the trajectory of a person’s center of mass (CoM). For outdoor applications, differential Global Navigation Satellite Systems (GNSS) can be used for tracking persons since they allow measuring the trajectory and speed of the GNSS antenna with centimeter accuracy. However, the antenna cannot be placed exactly at the person’s CoM, but rather on the head or upper back. Thus, a model is needed to relate the measured antenna trajectory to the CoM trajectory. In this paper we propose to estimate the person’s posture based on measurements obtained from inertial sensors. From this estimated posture the CoM is computed relative to the antenna position and finally fused with the GNSS trajectory information to obtain the absolute CoM trajectory. In a biomechanical field experiment, the method has been applied to alpine ski racing and validated against a camera-based stereo photogrammetric system. CoM position accuracy and precision was found to be 0.08 m and 0.04 m, respectively. CoM speed accuracy and precision was 0.04 m/s and 0.14 m/s, respectively. The observed accuracy and precision might be sufficient for measuring performance- or equipment-related trajectory differences in alpine ski racing. Moreover, the CoM estimation was not based on a movement-specific model and could be used for other skiing disciplines or sports as well

A New Training Assessment Method for Alpine Ski Racing: Estimating Center of Mass Trajectory by Fusing Inertial Sensors With Periodically Available Position Anchor Points

In this study we present and validate a method to correct velocity and position drift for inertial sensor-based measurements in the context of alpine ski racing. Magnets were placed at each gate and their position determined using a land surveying method. The time point of gate crossings of the athlete were detected with a magnetometer attached to the athlete’s lower back. A full body inertial sensor setup allowed to track the athlete’s posture, and the magnet positions were used as anchor points to correct position and velocity drift from the integration of the acceleration. Center of mass (CoM) position errors (mean ± standard deviation) were 0.24 m ± 0.09 m and CoM velocity errors were 0.00 m/s ± 0.18 m/s. For extracted turn entrance and exit speeds the 95% limits of agreements (LoAs) were between −0.19 and 0.33 m/s. LoA for the total path length of a turn were between −0.06 and 0.16 m. The proposed setup and processing allowed estimating the CoM kinematics with similar errors than known for differential global navigation satellite systems (GNSS), even though the athlete’s movement was measured with inertial and magnetic sensors only. Moreover, as the gate positions can also be obtained with non-GNSS based land surveying methods, CoM kinematics may be estimated in areas with reduced or no GNSS signal reception, such as in forests or indoors

Validity of the AdMos, Advanced Sport Instruments, GNSS Sensor for Use in Alpine Skiing

The AdMos receiver from Advanced Sport Instruments is a global navigation satellite system (GNSS) frequently used in alpine ski racing, with users from national and professional teams. Therefore, a validation was conducted for use of the AdMos in alpine skiing, using data from both recreational and competitive skiers. Athletes skied a total of 60 km in different measurement and skiing conditions, while carrying both an AdMos and a differential GNSS, which was used as the gold standard. From the GNSS position data, speed, acceleration, turn radius, trajectory incline and impulse were calculated as instantaneous and turn average measures for both GNSS systems and errors between the systems were calculated. The median and interquartile range (IQR) for the instantaneous errors were below 3.5 (3.5) m for horizontal plane position and below 7.0 (4.3) m for the 3D position. The median and IQR for instantaneous errors and turn average errors, respectively, were below 0.04 (0.24)/0.04 (0.16) m/s for speed, below 0.23 (1.06)/0.35 (0.63) m/s2 for acceleration, below 0.47 (5.65)/0.73 (5.3) m for turn radius, and below 0.043 (1.96)/0.42 (1.42) degrees for trajectory incline. The median and IQR for turn average impulse were 0.025 (0.099) BWs. The position error changed gradually and randomly over time, with low noise levels causing smooth trajectories of similar shape but spatially shifted from the true trajectory that allowed the position–time derivation of the performance parameters, and detection of turns with 3% median and 5% IQR error. The accuracy assessment revealed that (1) the error levels were comparable to other consumer-grade standalone GNSS units designed for sport; (2) the trajectories closely resembled the true trajectories but with a random shift that changed over time and had a low noise level; (3) there was a very low instantaneous speed error that may allow the detection of many performance aspects of skiing and other sports; and (4) there were larger instantaneous errors for the remaining performance parameters, which decreased substantially when averaged over a turn.publishedVersio

Estimation of the centre of mass kinematics in alpine ski racing using inertial and magnetic sensors

For performance analysis in alpine ski racing, an accurate and precise estimation of the centre of mass (CoM) kinematics is indispensable. Currently available systems satisfying this need are video-based stereo-photogrammetry or differential global navigation satellite systems (GNSS). However, they are impractical to use in regular training settings. Inertial sensors could be used instead but suffer from significant drifts in speed and position estimation due to the integration of acceleration and angular velocity data. The aim of the present study was to propose and validate an inertial and magnetometer sensor-based algorithm to estimate CoM kinematics in alpine ski racing. Relative CoM position and speed between-run comparisons were found to be highly accurate and precise with mean absolute deviations <0.15 m and <0.28 m/s

Drift Reduction for Inertial Sensor Based Orientation and Position Estimation in the Presence of High Dynamic Variability During Competitive Skiing and Daily-Life Walking

Nowadays inertial sensors are extensively used for gait analysis. They can be used to perform temporal event detection (i.e. step detection) and to estimate the orientation of the feet and other body segments to determine walking speed and distance. Usually, orientation is estimated from integration of the measured angular velocity. Prior to integration of measured acceleration to obtain speed, the gravity component has to be estimated and removed. During each integration small measurement errors accumulate and result in so-called drift. Since the first uses of inertial sensors for gait analysis methods have been presented to model, estimate and remove the drift. The proposed methods worked well for relatively slow movements and movements taking place in the sagittal plane. Many methods also relied on periodically occurring static phases such as the stance phase during walking to correct the drift. Inertial sensors could also be used to track higher dynamic movements, for example in sports. Potential applications focus on two aspects: performance analysis and injury prevention. To better explain and predict performance, in-field measurements to assess the coordination, kinematics, and dynamics are key. While traditional movement analysis (e.g. video analysis) can answer most of the questions related to both performance and injury, they are cumbersome and complex to use in-field. Inertial sensors, however, are perfectly suited since they allow to measure the movement in any environment and are not restricted to certain capture volumes. Nevertheless, most sports have very high movement dynamics (e.g. fast direction changes, high speeds) and are therefore challenging for computing reliable estimates of orientation, speed and position. The inertial measurements are compromised by noise and movements oftentimes don't provide static or slow phases used in gait analysis for drift correction. Therefore, the present thesis aimed to propose and validate new methods to model, estimate and remove drift in sports and for movements taking place outdoors in uncontrolled environments. Three different strategies were proposed to measure the movement of classical cross-country skiing and ski mountaineering, alpine ski racing, and outdoor walking over several kilometres. For each activity specific biomechanical constraints and movement dynamics were exploited. The proposed methods rely only on inertial sensors and magnetometers and are able to provide orientation, speed, and position information with an accuracy and precision close to existing gold standards. The most complete system was designed in alpine ski racing, probably one of the most challenging sports for movement analysis. Extreme vibrations, high speeds of over 120 km/h and a timing resolution below 0.01 seconds require maximum accuracy and precision. The athlete's posture and the kinematics of his centre of mass both in a relative athlete-centred frame and in a global Earth-fixed frame could be obtained with high accuracy and precision. Where 3D video analysis requires a very complex experimental setup and takes several hours of post processing to analyse a single turn of a skier, the proposed system allows to measure multiple athletes and complete runs within minutes. Thus, new experimental designs to assess performance and injury risk in alpine ski racing became feasible, greatly helping to gain further knowledge about this highly complex and risky sport

Influence of Turn Cycle Structure on Performance of Elite Alpine Skiers Assessed through an IMU in Different Slalom Course Settings

Small differences in turn cycle structure, invisible to the naked eye, could be decisive in improving descent performance. The aim of this study was to assess the influence of turn cycle structure on the performance of elite alpine skiers using an inertial measurement unit (IMU) in different slalom (SL) course settings. Four SL courses were set: a flat-turned (FT), a steep-turned (ST), a flat-straighter (FS) and a steep-straighter (SS). Five elite alpine skiers (21.2 ± 3.3 years, 180.2 ± 5.6 cm, 72.8 ± 6.6 kg) completed several runs at maximum speed for each SL course. A total of 77 runs were obtained. Fast total times correlate with a longer initiation (INI) time in FT, a shorter steering time out of the turn (STEOUT) in the FT and FS and a shorter total steering time (STEIN+OUT) in the FT and SS courses. The linear mixed model used for the analysis revealed that in the FT-course for each second increase in the INI time, the total time is reduced by 0.45 s, and for every one-second increase in the STEOUT and STEIN+OUT times, the total time increases by 0.48 s and 0.31 s, respectively. Thus, to enhance descent performance, the skier should lengthen the INI time and shorten the STEOUT and STEIN+OUT time. Future studies could use an IMU to detect turn phases and analyze them using the other built-in sensors

Tracking Performance in Endurance Racing Sports: Evaluation of the Accuracy Offered by Three Commercial GNSS Receivers Aimed at the Sports Market

Advances in global navigation satellite system (GNSS) technology have resulted in smaller and more accurate GNSS receivers, which have become increasingly suitable for calculating instantaneous performance parameters during sports competitions, for example by providing the difference in time between athletes at any location along a course. This study investigated the accuracy of three commercially available GNSS receivers directed at the sports market and evaluated their applicability for time analysis in endurance racing sports. The receivers evaluated were a 1 Hz wrist-worn standalone receiver (Garmin Forerunner 920XT, Gar-920XT), a 10 Hz standalone receiver (Catapult Optimeye S5, Cat-S5), and a 10 Hz differential receiver (ZXY-Go). They were validated against a geodetic, multi-frequency receiver providing differential position solutions (accuracy &lt; 5 cm). Six volunteers skied four laps on a 3.05 km track prepared for cross-country skiing, with all four GNSS receivers measuring simultaneously. Deviations in position (horizontal plane, vertical, direction of travel) and speed (horizontal plane and direction of travel) were calculated. In addition, the positions of all receivers were mapped onto a mapping trajectory along the ski track, and a time analysis of all 276 possible pairs of laps was performed. Specifically, the time difference between any two skiers for each integer meter along the track was calculated. ZXY-Go, CAT-S5, and GAR-920XT had horizontal plane position errors of 2.09, 1.04, and 5.29 m (third quartile, Q3), and vertical precision 2.71, 3.89, and 13.35 m (interquartile range, IQR), respectively. The precision in the horizontal plane speed was 0.038, 0.072, and 0.66 m s-1 (IQR) and the time analysis precision was 0.30, 0.13, and 0.68 s (IQR) for ZXY-Go, Cat-S5, and Gar-920XT, respectively. However, the error was inversely related to skiing speed, implying that for the low speeds typically attained during uphill skiing, substantially larger errors can occur. Specifically, at 2.0 m s-1 the Q3 was 0.96, 0.36, and 1.90 s for ZXY-Go, Cat-S5, and Gar-920XT, respectively. In summary, the differential (ZXY-Go) and 10 Hz standalone (Cat-S5) receivers performed substantially better than the wrist-worn receiver (Gar-920XT) in terms of horizontal position and horizontal speed calculations. However, all receivers produced sub-second accuracy in the time analysis, except at very low skiing speeds

Estimating Alpine Skiers’ Energetics and Turn Radius Using Different Morphological Points

Alpine ski analysis has always been very challenging, mainly due to the environmental conditions, large field and rapid and dynamic skiers’ movements. Global navigation satellite system (GNSS) offers a solution adapted to outdoor testing, but the relationship between the point where the antenna is attached and the real centre of mass (CoM) position is still unknown. This article proposes to compare different points of the body used to quantify the performance of alpine skiers. 3D models of seven elite skiers performing giant slalom (GS) were built using multiple camera system and dedicated motion tracking software. CoM as well as pelvis, head and feet trajectories were deduced from the data. The potential and kinetic energies corresponding to these points were calculated, as well as the evolution of the turn radius during the turn cycle. Differences between values given by the CoM and the other morphological points were analyzed. The pelvis offered the best estimation of the CoM: No differences were found for the biomechanical parameters, except for the kinetic energy, where 2% of the turn cycle had significant different values. The head was less accurate compared to the pelvis, showing significant differences with CoM between 7 and 20% of the turn cycle depending on the parameter. Finally, the feet offered the worst results, with significant differences between 16 and 41% of the turn cycle. Energies and turn radius calculated by using pelvis in place of CoM offered similar patterns, allowing the analysis of mechanical and dissipation energy in GS. This may potentially enable easier testing methods to be proposed and tested

Propulsive Power in Cross-Country Skiing: Application and Limitations of a Novel Wearable Sensor-Based Method During Roller Skiing

Cross-country skiing is an endurance sport that requires extremely high maximal aerobic power. Due to downhill sections where the athletes can recover, skiers must also have the ability to perform repeated efforts where metabolic power substantially exceeds maximal aerobic power. Since the duration of these supra-aerobic efforts is often in the order of seconds, heart rate, and pulmonary VO2 do not adequately reflect instantaneous metabolic power. Propulsive power (Pprop) is an alternative parameter that can be used to estimate metabolic power, but the validity of such calculations during cross-country skiing has rarely been addressed. The aim of this study was therefore twofold: to develop a procedure using small non-intrusive sensors attached to the athlete for estimating Pprop during roller-skiing and to evaluate its limits; and (2) to utilize this procedure to determine the Pprop generated by high-level skiers during a simulated distance race. Eight elite male cross-country skiers simulated a 15 km individual distance race on roller skis using ski skating techniques on a course (13.5 km) similar to World Cup skiing courses. Pprop was calculated using a combination of standalone and differential GNSS measurements and inertial measurement units. The method's measurement error was assessed using a Monte Carlo simulation, sampling from the most relevant sources of error. Pprop decreased approximately linearly with skiing speed and acceleration, and was approximated by the equation Pprop(v,v˙) = −0.54·v −0.71·v˙ + 7.26 W·kg−1. Pprop was typically zero for skiing speeds &gt;9 m·s−1, because the athletes transitioned to the tuck position. Peak Pprop was 8.35 ± 0.63 W·kg−1 and was typically attained during the final lap in the last major ascent, while average Pprop throughout the race was 3.35 ± 0.23 W·kg−1. The measurement error of Pprop increased with skiing speed, from 0.09 W·kg−1 at 2.0 m·s−1 to 0.58 W·kg−1 at 9.0 m·s−1. In summary, this study is the first to provide continuous measurements of Pprop for distance skiing, as well as the first to quantify the measurement error during roller skiing using the power balance principle. Therefore, these results provide novel insight into the pacing strategies employed by high-level skiers