Collecting Kinematic Data on a Ski Track with Optoelectronic Stereophotogrammetry: A Methodological Study Assessing the Feasibility of Bringing the Biomechanics Lab to the Field

Motion Capture Technology in Sports Scenarios: A Survey

Motion capture technology plays a crucial role in optimizing athletes' skills, techniques, and strategies by providing detailed feedback on motion data. This article presents a comprehensive survey aimed at guiding researchers in selecting the most suitable motion capture technology for sports science investigations. By comparing and analyzing the characters and applications of different motion capture technologies in sports scenarios, it is observed that cinematography motion capture technology remains the gold standard in biomechanical analysis and continues to dominate sports research applications. Wearable sensor-based motion capture technology has gained significant traction in specialized areas such as winter sports, owing to its reliable system performance. Computer vision-based motion capture technology has made significant advancements in recognition accuracy and system reliability, enabling its application in various sports scenarios, from single-person technique analysis to multi-person tactical analysis. Moreover, the emerging field of multimodal motion capture technology, which harmonizes data from various sources with the integration of artificial intelligence, has proven to be a robust research method for complex scenarios. A comprehensive review of the literature from the past 10 years underscores the increasing significance of motion capture technology in sports, with a notable shift from laboratory research to practical training applications on sports fields. Future developments in this field should prioritize research and technological advancements that cater to practical sports scenarios, addressing challenges such as occlusion, outdoor capture, and real-time feedback.

Non-human primate models and systems for gait and neurophysiological analysis

Brain-computer interfaces (BCIs) have garnered extensive interest and become a groundbreaking technology to restore movement, tactile sense, and communication in patients. Prior to their use in human subjects, clinical BCIs require rigorous validation and verification (V&V). Non-human primates (NHPs) are often considered the ultimate and widely used animal model for neuroscience studies, including BCIs V&V, due to their proximity to humans. This literature review summarizes 94 NHP gait analysis studies until 1 June, 2022, including seven BCI-oriented studies. Due to technological limitations, most of these studies used wired neural recordings to access electrophysiological data. However, wireless neural recording systems for NHPs enabled neuroscience research in humans, and many on NHP locomotion, while posing numerous technical challenges, such as signal quality, data throughout, working distance, size, and power constraint, that have yet to be overcome. Besides neurological data, motion capture (MoCap) systems are usually required in BCI and gait studies to capture locomotion kinematics. However, current studies have exclusively relied on image processing-based MoCap systems, which have insufficient accuracy (error: ≥4° and 9 mm). While the role of the motor cortex during locomotion is still unclear and worth further exploration, future BCI and gait studies require simultaneous, high-speed, accurate neurophysiological, and movement measures. Therefore, the infrared MoCap system which has high accuracy and speed, together with a high spatiotemporal resolution neural recording system, may expand the scope and improve the quality of the motor and neurophysiological analysis in NHPs.

Quantitative downhill skiing technique analysis according to ski instruction curricula: A proof-of-concept study applying principal component analysis on wearable sensor data

Downhill skiing technique represents the complex coordinative movement patterns needed to control skiing motion. While scientific understanding of skiing technique is still incomplete, not least due to challenges in objectively measuring it, practitioners such as ski instructors have developed sophisticated and comprehensive descriptions of skiing technique. The current paper describes a 3-step proof-of-concept study introducing a technology platform for quantifying skiing technique that utilizes the practitioners’ expert knowledge. The approach utilizes an inertial measurement unit system (Xsens™) and presents a motion analysis algorithm based on the Principal Movement (PM) concept. In step 1, certified ski instructors skied specified technique elements according to technique variations described in ski instruction curricula. The obtained data was used to establish a PM-coordinate system for skiing movements. In step 2, the techniques parallel and carving turns were compared. Step 3 presents a case study where the technique analysis methodology is applied to advise an individual skier on potential technique improvements. All objectives of the study were met, proving the suitability of the proposed technology for scientific and applied technique evaluations of downhill skiing. The underlying conceptual approach - utilizing expert knowledge and skills to generate tailored variability in motion data (step 1) that then dominate the orientation of the PMs, which, in turn, can serve as measures for technique elements of interest - could be applied in many other sports or for other applications in human movement analyses.

Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures

Integrating mobile eye tracking and optoelectronic motion capture enables point of gaze to be expressed within the laboratory co-ordinate system and presents a method not commonly applied during research examining dynamic behaviors, such as locomotion. This paper examines the quality of gaze data collected through the integration. Based on research suggesting increased viewing distances are associated with reduced data quality; the accuracy and precision of gaze data as participants (N = 11) viewed floor-based targets at distances of 1–6 m was investigated. A mean accuracy of 2.55 ± 1.12° was identified, however, accuracy and precision measures (relative to targets) were significantly (p < .05) reduced at greater viewing distances. We then consider if signal processing techniques may improve accuracy and precision, and overcome issues associated with missing data. A 4th-order Butterworth lowpass filter with cut-off frequencies determined via autocorrelation did not significantly improve data quality, however, interpolation via Quintic spline was sufficient to overcome gaps of up to 0.1 s. We conclude the integration of gaze and motion capture presents a viable methodology in the study of human behavior and presents advantages for data collection, treatment, and analysis. We provide considerations for the collection, analysis, and treatment of gaze data that may help inform future methodological decisions.

Comparative Analysis of Optoelectronic Accuracy in the Laboratory Setting Versus Clinical Operative Environment: A Systematic Review

STUDY DESIGN

Systematic review.

OBJECTIVES

The optoelectronic camera source and data interpolation process serve as the foundation for navigational integrity in robotic-assisted surgical platforms. The current systematic review serves to provide a basis for the numerical disparity observed when comparing the intrinsic accuracy of optoelectronic cameras versus accuracy in the laboratory setting and clinical operative environments.

METHODS

Review of the PubMed and Cochrane Library research databases was performed. The exhaustive literature compilation obtained was then vetted to reduce redundancies and categorized into topics of intrinsic accuracy, registration accuracy, musculoskeletal kinematic platforms, and clinical operative platforms.

RESULTS

A total of 465 references were vetted and 137 comprise the basis for the current analysis. Regardless of application, the common denominators affecting overall optoelectronic accuracy are intrinsic accuracy, registration accuracy, and application accuracy. Intrinsic accuracy equaled or was less than 0.1 mm translation and 0.1 degrees rotation per fiducial. Controlled laboratory platforms reported 0.1 to 0.5 mm translation and 0.1 to 1.0 degrees rotation per array. Accuracy in robotic-assisted spinal surgery reported 1.5 to 6.0 mm translation and 1.5 to 5.0 degrees rotation when comparing planned to final implant position.

CONCLUSIONS

Navigational integrity and maintenance of fidelity of optoelectronic data is the cornerstone of robotic-assisted spinal surgery. Transitioning from controlled laboratory to clinical operative environments requires an increased number of steps in the optoelectronic kinematic chain and error potential. Diligence in planning, fiducial positioning, system registration and intra-operative workflow have the potential to improve accuracy and decrease disparity between planned and final implant position.

Implementation of Sequence-Based Classification Methods for Motion Assessment and Recognition in a Traditional Chinese Sport (Baduanjin)

This study aimed to assess the motion accuracy of Baduanjin and recognise the motions of Baduanjin based on sequence-based methods. Motion data of Baduanjin were measured by the inertial sensor measurement system (IMU). Fifty-four participants were recruited to capture motion data. Based on the motion data, various sequence-based methods, namely dynamic time warping (DTW) combined with classifiers, hidden Markov model (HMM), and recurrent neural networks (RNNs), were applied to assess motion accuracy and recognise the motions of Baduanjin. To assess motion accuracy, the scores for motion accuracies from teachers were used as the standard to train the models on the different sequence-based methods. The effectiveness of Baduanjin motion recognition with different sequence-based methods was verified. Among the methods, DTW + k-NN had the highest average accuracy (83.03%) and shortest average processing time (3.810 s) during assessing. In terms of motion reorganisation, three methods (DTW + k-NN, DTW + SVM, and HMM) had the highest accuracies (over 99%), which were not significantly different from each other. However, the processing time of DTW + k-NN was the shortest (3.823 s) compared to the other two methods. The results show that the motions of Baduanjin could be recognised, and the accuracy can be assessed through an appropriate sequence-based method with the motion data captured by IMU.

Accuracy of Robotic-Assisted Spinal Surgery-Comparison to TJR Robotics, da Vinci Robotics, and Optoelectronic Laboratory Robotics

BACKGROUND

The optoelectronic camera source and data interpolation serve as the foundation for navigational integrity in the robotic-assisted surgical platform. The objective of the current systematic review serves to provide a basis for the numerical disparity that exists when comparing the intrinsic accuracy of optoelectronic cameras: accuracy observed in the laboratory setting versus accuracy in the clinical operative environment. It is postulated that there exists a greater number of connections in the optoelectronic kinematic chain when analyzing the clinical operative environment to the laboratory setting. This increase in data interpolation, coupled with intraoperative workflow challenges, reduces the degree of accuracy based on surgical application and to that observed in controlled musculoskeletal kinematic laboratory investigations.

METHODS

Review of the PubMed and Cochrane Library research databases was performed. The exhaustive literature compilation obtained was then vetted to reduce redundancies and categorized into topics of intrinsic optoelectronic accuracy, registration accuracy, musculoskeletal kinematic platforms, and clinical operative platforms.

RESULTS

A total of 147 references make up the basis for the current analysis. Regardless of application, the common denominators affecting overall optoelectronic accuracy are intrinsic accuracy, registration accuracy, and application accuracy. Intrinsic accuracy of optoelectronic tracking equaled or was less than 0.1 mm of translation and 0.1° of rotation per fiducial. Controlled laboratory platforms reported 0.1 to 0.5 mm of translation and 0.1°-1.0° of rotation per array. There is a huge falloff in clinical applications: accuracy in robotic-assisted spinal surgery reported 1.5 to 6.0 mm of translation and 1.5° to 5.0° of rotation when comparing planned to final implant position. Total Joint Robotics and da Vinci urologic robotics computed accuracy, as predicted, lies between these two extremes-1.02 mm for da Vinci and 2 mm for MAKO.

CONCLUSIONS

Navigational integrity and maintenance of fidelity of optoelectronic data is the cornerstone of robotic-assisted spinal surgery. Transitioning from controlled laboratory to clinical operative environments requires an increased number of steps in the optoelectronic kinematic chain and error potential. Diligence in planning, fiducial positioning, system registration, and intraoperative workflow have the potential to improve accuracy and decrease disparity between planned and final implant position. The key determining factors limiting navigation resolution accuracy are highlighted by this Cochrane research analysis.

Connected skiing: Validation of edge angle and radial force estimation as motion quality parameters during alpine skiing

Recent studies have developed wearable sensor systems to detect, classify and evaluate performance during alpine skiing. In order to enrich skiing data to provide motion quality feedback, edge angle (EA) and radial force (F_r) are parameters of interest. However, the estimation of these parameters via calibration-free wearable technologies has not been validated. The purpose of this study was to develop and validate a wearable method to estimate EA and F_r. Participants completed simulated skiing trials on an indoor skiing carpet. Two IMU's mounted to the ski boots estimated EA and F_r and compared to reference values measured with a 3D motion capture system. The performance of the wearable system was quantified by accuracy and precision. The overall accuracy and precision of the wearable system was 97.6 ± 12.4% and 15.5 ± 17.6% for EA, and 105.5 ± 5.7% and 29.8 ± 10.0%, respectively for F_r. The developed wearable system was accurate for the estimation of EA and F_r, but was highly variable with low precision for both metrics. Further research is needed to improve the precision of field-relevant skiing metrics during in-field studies using simple measurement setups that can easily be implemented by recreational and expert skiers alike.Highlights IMU's mounted on the boots are sufficient tools for accurate estimation of edge angle and radial force during both long and short style turns on a skiing simulator.As the estimation of edge angle and radial force are dependent on other estimated parameters (i.e. turn switch), the precision of these metrics is relatively low.The results of the current study apply only to simulated alpine skiing on a treadmill, and further work is required to prove the accuracy and precision of this system on snow.

Connected Skiing: Motion Quality Quantification in Alpine Skiing

Recent developments in sensing technology have made wearable computing smaller and cheaper. While many wearable technologies aim to quantify motion, there are few which aim to qualify motion. (2) To develop a wearable system to quantify motion quality during alpine skiing, IMUs were affixed to the ski boots of nineteen expert alpine skiers while they completed a set protocol of skiing styles, included carving and drifting in long, medium, and short radii. The IMU data were processed according to the previously published skiing activity recognition chain algorithms for turn segmentation, enrichment, and turn style classification Principal component models were learned on the time series variables edge angle, symmetry, radial force, and speed to identify the sources of variability in a subset of reference skiers. The remaining data were scored by comparing the PC score distributions of variables to the reference dataset. (3) The algorithm was able to differentiate between an expert and beginner skier, but not between an expert and a ski instructor, or a ski instructor and a beginner. (4) The scoring algorithm is a novel concept to quantify motion quality but is limited by the accuracy and relevance of the input data.

Spinal segment ranges of motion, movement coordination, and three-dimensional kinematics during occupational activities in normal-weight and obese individuals

Measurements of spinal segment ranges of motion (RoMs), movement coordination, and three-dimensional kinematics during occupational activities have implications in occupational/clinical biomechanics. Due to the large amount of adipose tissues, obese individuals may have different RoMs, lumbopelvic coordination, and kinematics than normal-weight ones. We aimed to measure/compare trunk, lumbar, and pelvis primary RoMs in all anatomical planes/directions, lumbopelvic ratios (lumbar to pelvis rotations at different trunk angles) in all anatomical planes/directions and three-dimensional spine kinematics during twelve symmetric/asymmetric statics load-handling activities in healthy normal-weight and obese individuals. Kinematics/motion data were collected from nine healthy young male normal-weight and nine age/height/sex matched obese individuals via a ten-camera Vicon motion capture system. Obese individuals had significantly smaller (p < 0.05) lumbar flexion (~9° in average) and larger pelvis right lateral bending (~5°) RoMs as well as smaller lumbopelvic ratios (~37%) in lateral bending and axial rotation movements as compared to normal-weight individuals. Moreover, the two groups had generally non-significant different segmental orientations (<20° and in most cases < 10°) in load-handling tasks that depended on the magnitude of load asymmetry angle (p < 0.05). Differences were larger for tasks performed near the floor, away from body, and at larger load asymmetry angles. Biomechanical models simulating pure lateral bending, axial rotation, or tasks involving large load asymmetry may therefore need subject-specific, rather than population-based, motion analysis due to the effects from body weight. In clinical applications, it should be noted that healthy obese individuals may have different RoMs and lumbopelvic rhythms than healthy normal-weight individuals in some anatomical planes/directions.

Studying Force Patterns in an Alpine Ski Boot and Their Relation to Riding Styles and Falling Mechanisms

In skiing, performance and safety can depend on small details. Consequently, the measurement of forces within the ski boots, which represent the essential form-fitting and force transmitting interface during skiing, will lead to enhanced performance and more importantly safety. This study presents a methodology to measure force patterns (continuous data acquisition) under laboratory as well as realistic slope conditions. The force measurements will be analyzed to gain insights of the skiing style, skiing technique, specific falling mechanisms (i.e., boot induced anterior drawer, phantom foot, hyperextension of the knee joint, and valgus-external rotation). Furthermore, the locations of force sensors in a overlap designed ski boot are discussed in terms of practicability and applicability. These insights are of particular interest to derive release conditions for predictive binding systems and furthermore provide data to improve the style of skiing (e.g., turn release action or center of gravity behavior). For that purpose, a ski boot was instrumented with seven force (piezoresistive) sensors while the basic structure of the boot and the binding remained unchanged. Three sensors were placed on the insole to measure ground reaction forces as well as the contact forces between the skier's foot and the boot. The other four sensors were positioned at spoiler/shaft and toecap (front sole) regions of the ski boot. The locations of the force sensors within the ski-boot are defined with regard to the main body movement while skiing (body-related planes). In addition, a commercially available ski and body mount measuring system were utilized to correlate speed, inclination and body position with the force patterns occurring during skiing on the slope as well as simulating specific body positions on an inclined ramp under laboratory conditions. The measured force revealed that the toecap (upper) sensors provide insufficient even non-conclusive data to deduce significant patterns. However, the insole sensors (heel and front sole area) as well as the spoiler/shaft (back) sensors are more reliable and show characteristic patterns indicating forward or backward lean. These results will have an important impact to the development of predictiveelectro-mechanical bindings to prevent knee-related injuries, which, from a statistical point of view, concerns largely women and young athletes.

A Comprehensive Comparison and Validation of Published Methods to Detect Turn Switch during Alpine Skiing

The instant of turn switch (TS) in alpine skiing has been assessed with a variety of sensors and TS concepts. Despite many published methodologies, it is unclear which is best or how comparable they are. This study aimed to facilitate the process of choosing a TS method by evaluating the accuracy and precision of the methodologies previously used in literature and to assess the influence of the sensor type. Optoelectronic motion capture, inertial measurement units, pressure insoles, portable force plates, and electromyography signals were recorded during indoor treadmill skiing. All TS methodologies were replicated as stated in their respective publications. The method proposed by Supej assessed with optoelectronic motion capture was used as a comparison reference. TS time differences between the reference and each methodology were used to assess accuracy and precision. All the methods analyzed showed an accuracy within 0.25 s, and ten of them within 0.05 s. The precision ranged from ~0.10 s to ~0.60 s. The TS methodologies with the best performance (accuracy and precision) were Klous Video, Spörri PI (pressure insoles), Martinez CTD (connected boot), and Yamagiwa IMU (inertial measurement unit). In the future, the specific TS methodology should be chosen with respect to sensor selection, performance, and intended purpose.

Search for Available Biomechanical Technologies Suitable for Use in Physical Education Classes

Introduction: One of the most important physical education tasks in school is to learn motor actions. Biomechanical technologies can promote to this process. A school lesson is different from a sports training, so it is necessary keep in mind its specifics. The purpose of the article is to analyse the existing professional biomechanical complexes for their suitability for use in physical education classes. Methods: We studied articles on sports biomechanics and selected 20 professional biomechanical complexes. These complexes can be divided into four technological groups: Optoelectronic Measurement Systems (OMSs), Electromagnetic Measurement Systems (EMSs), Image Processing Systems (IMSs), Inertial Sensory Systems (IMUs). Besides that, we identified 10 crucial categories to estimate opportunity to use biomechanical complexes in school lessons: cost, complexity of setting up and using, assistance need, portability, universality, room volume, construction traumatic, place for using, promptness, volume of data. Thus, each complex was evaluated according to 10 criteria. The biomechanical complex was excluded from further consideration if it got a critical limitation at least one of the criteria. Results: None of the professional biomechanical complexes can be considered suitable for use in physical education classes. As alternative we propose using free biomechanical software and smartphone camera with slow-motion caption.

Differences in Motion Accuracy of Baduanjin between Novice and Senior Students on Inertial Sensor Measurement Systems

This study aimed to evaluate the motion accuracy of novice and senior students in Baduanjin (a traditional Chinese sport) using an inertial sensor measurement system (IMU). Study participants were nine novice students, 11 senior students, and a teacher. The motion data of all participants were measured three times with the IMU. Using the motions of the teacher as the standard motions, we used dynamic time warping to calculate the distances between the motion data of the students and the teacher to evaluate the motion accuracy of the students. The distances between the motion data of the novice students and the teacher were higher than that between senior students and the teacher (p < 0.05 or p < 0.01). These initial results showed that the IMU and the corresponding mathematical methods could effectively distinguish the differences in motion accuracy between novice and senior students of Baduanjin.

Are Existing Monocular Computer Vision-Based 3D Motion Capture Approaches Ready for Deployment? A Methodological Study on the Example of Alpine Skiing

In this study, we compared a monocular computer vision (MCV)-based approach with the golden standard for collecting kinematic data on ski tracks (i.e., video-based stereophotogrammetry) and assessed its deployment readiness for answering applied research questions in the context of alpine skiing. The investigated MCV-based approach predicted the three-dimensional human pose and ski orientation based on the image data from a single camera. The data set used for training and testing the underlying deep nets originated from a field experiment with six competitive alpine skiers. The normalized mean per joint position error of the MVC-based approach was found to be 0.08 ± 0.01m. Knee flexion showed an accuracy and precision (in parenthesis) of 0.4 ± 7.1° (7.2 ± 1.5°) for the outside leg, and -0.2 ± 5.0° (6.7 ± 1.1°) for the inside leg. For hip flexion, the corresponding values were -0.4 ± 6.1° (4.4° ± 1.5°) and -0.7 ± 4.7° (3.7 ± 1.0°), respectively. The accuracy and precision of skiing-related metrics were revealed to be 0.03 ± 0.01 m (0.01 ± 0.00 m) for relative center of mass position, -0.1 ± 3.8° (3.4 ± 0.9) for lean angle, 0.01 ± 0.03 m (0.02 ± 0.01 m) for center of mass to outside ankle distance, 0.01 ± 0.05 m (0.03 ± 0.01 m) for fore/aft position, and 0.00 ± 0.01 m² (0.01 ± 0.00 m²) for drag area. Such magnitudes can be considered acceptable for detecting relevant differences in the context of alpine skiing.

Experimental Evaluation of UWB Indoor Positioning for Indoor Track Cycling

Accurate radio frequency (RF)-based indoor localization systems are more and more applied during sports. The most accurate RF-based localization systems use ultra-wideband (UWB) technology; this is why this technology is the most prevalent. UWB positioning systems allow for an in-depth analysis of the performance of athletes during training and competition. There is no research available that investigates the feasibility of UWB technology for indoor track cycling. In this paper, we investigate the optimal position to mount the UWB hardware for that specific use case. Different positions on the bicycle and cyclist were evaluated based on accuracy, received power level, line-of-sight, maximum communication range, and comfort. Next to this, the energy consumption of our UWB system was evaluated. We found that the optimal hardware position was the lower back, with a median ranging error of 22 cm (infrastructure hardware placed at 2.3 m). The energy consumption of our UWB system is also taken into account. Applied to our setup with the hardware mounted at the lower back, the maximum communication range varies between 32.6 m and 43.8 m. This shows that UWB localization systems are suitable for indoor positioning of track cyclists.

Dataset:http://dx.doi.org/10.17632/fkhfjfspkr.1

Accuracy of human motion capture systems for sport applications; state-of-the-art review

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).

An Inertial Sensor-Based Method for Estimating the Athlete's Relative Joint Center Positions and Center of Mass Kinematics in Alpine Ski Racing

For the purpose of gaining a deeper understanding of the relationship between external training load and health in competitive alpine skiing, an accurate and precise estimation of the athlete's kinematics is an essential methodological prerequisite. This study proposes an inertial sensor-based method to estimate the athlete's relative joint center positions and center of mass (CoM) kinematics in alpine skiing. Eleven inertial sensors were fixed to the lower and upper limbs, trunk, and head. The relative positions of the ankle, knee, hip, shoulder, elbow, and wrist joint centers, as well as the athlete's CoM kinematics were validated against a marker-based optoelectronic motion capture system during indoor carpet skiing. For all joints centers analyzed, position accuracy (mean error) was below 110 mm and precision (error standard deviation) was below 30 mm. CoM position accuracy and precision were 25.7 and 6.7 mm, respectively. Both the accuracy and precision of the system to estimate the distance between the ankle of the outside leg and CoM (measure quantifying the skier's overall vertical motion) were found to be below 11 mm. Some poorer accuracy and precision values (below 77 mm) were observed for the athlete's fore-aft position (i.e., the projection of the outer ankle-CoM vector onto the line corresponding to the projection of ski's longitudinal axis on the snow surface). In addition, the system was found to be sensitive enough to distinguish between different types of turns (wide/narrow). Thus, the method proposed in this paper may also provide a useful, pervasive way to monitor and control adverse external loading patterns that occur during regular on-snow training. Moreover, as demonstrated earlier, such an approach might have a certain potential to quantify competition time, movement repetitions and/or the accelerations acting on the different segments of the human body. However, prior to getting feasible for applications in daily training, future studies should primarily focus on a simplification of the sensor setup, as well as a fusion with global navigation satellite systems (i.e., the estimation of the absolute joint and CoM positions).