Breaking Barriers in Bob Racing with Cutting-Edge Sensor Technology

The German Bobsleigh and luge association grapples with challenges in digitalization and sensor integration for training and performance enhancement. These hurdles include the need for reliable, specialized sensors adaptable to extreme conditions, data privacy concerns, and integrating real-time feedback into training routines.

The German Bobsleigh, Luge, and Skeleton Federation seek to revolutionise the professional bobsleigh sport by incorporating sensor technology onto the sport equipment to measure control, balance and speed impulses with real time data and enhance the professional performance.

The integration of sensors to measure control, balance and speed steering impulses serves as a pivotal initiative to guide the sport into a new era of precision and performance optimisation. As of now, performance is primarily measured through precise timekeeping, capturing the duration of teams' runs from start to finish. Intermediate times are taken at various points for in-depth analysis. Speed is tracked using radar or sensors, aiding in understanding velocity profiles. Biometric sensors monitor heart rate, acceleration, and G-forces to assess athlete strain. Video analysis aids technique refinement. Through this digital transformation of the sled and the athlete, the association aims to capture real-time data on athletes' steering techniques, providing valuable insights for performance analysis and enhancement.

Digital transformation needs: Until now, such control and steering techniques are being carried out regarding the athletes in the sled, as the athletes steer the bob by shifting their weight). According to the federation and its performance sports department, insights into Internet-of-Things options, especially sensor technology based techniques, will provide valuable knowledge for developing new data-based products and training services to be used in the future for the Olympic racing sport

With the assistance of EDIH-CIMO, a feasibility and sensor technology performance test was conducted.

First, various tests were conducted to determine the most suitable sensor technology for measuring outdoor racing vehicles directly on the ice.

Secondly, the most efficient measurement location on the luge sled was tested to provide high-quality real-time data for professional analysis and control. Initially, the EDIH-CIMO research team, in collaboration with the customer, defined the testing objectives, outlining clear goals and performance metrics. Subsequently, through experiments in controlled environments (in the lab), the research team explored different systems to identify the optimal sensors and their placement on the luge for data collection. A key aspect of this process was the meticulous engineering of FSR sensors, designed to capture subtle changes in electrical resistance triggered by applied force.

In an iterative process, the quality of the collected data was assessed, ensuring it accurately represented steering impulses for further analysis. The data analysis approach involved segmenting it based on the curves of the track. Manual identification and recording of the beginning and ending points of each curve were performed in an Excel sheet for precise documentation. Each curve segment was then time-normalized to consist of 1000 data points, ensuring consistency in the analysis.

The final steps involved testing the system in a real environment (ice tube) to gather feedback from athletes and trainers on the sensor system. The rationale behind the investment required to finance this digital solution in professional luge sleds encompasses considerations related to innovation, sports performance enhancement, safety, economic benefits, and technological advancement.

Impact for EDIH customer (SME):

As of now, there is no information on the steering techniques of the athletes in the canal. The vision of the association is to connect different data sources (e.g., steering impulse, location of the athletes in the canal) and provide some kind of dashboard for training matters. By scrutinizing the timing and manner in which different athletes initiate steering maneuvers, scholars can delve deeper into the strategic approaches adopted by elite performers and the variations across athletes. This knowledge could then guide targeted training interventions aimed at optimizing steering techniques and elevating overall performance. Conducting measurements in real-life settings would facilitate the collection of data amidst the dynamic and intricate conditions of actual luge tracks, offering a more comprehensive grasp of the interplay among athletes, sleds, and tracks. 

Impact for EDIH Network:

EDIH Crowd in Motion can enhance their expertise in sensor system integration and measurement of real-time data in alpine sport technology. This can be further offered to other sport associations and sport product manufacturers that also aim to digitize their products and services. The network can be enlarged with the association and its partners, which strengthens the EDIH foci. The results of this good practice of this association can be discussed and presented as a best practice for events and presentations, e.g., it is planned for presentation in the next year within the newly established membership of the EDIH in the European Sport and Business network.

Public funding may come from governmental bodies or organizations, aiming to support innovation and technological advancement in sports.

Private funding often comes from corporations, sponsors, or technology firms investing in research, development, and implementation of digital solutions. These investments cover expenses related to technology development, sensor integration, data analysis tools, and training programs.

The return on investment (ROI) and financial benefits of these digital solutions can be significant, but are not yet measurable, since the EDIH project was a first step in this research and analysis. Improved athlete performance, enhanced training methodologies, and streamlined data analytics can lead to better competitive outcomes and success in international competitions. 

Overall, the financial benefits expected from investing in digital solutions for bobsleigh include increased efficiency, improved performance, enhanced competitiveness, and potentially higher revenue generation, making it a worthwhile investment for both public and private stakeholders. Conversations about next steps in a collaborative project and/or a direct acquisition project with relevant stakeholders (e.g. International Association for Bobsleigh and Skeleton) are currently underway.

Process Learnings:

The project demonstrated the value of bringing together diverse expertise from different fields, including sports science, engineering, and technology development. Clear communication channels facilitated productive exchanges of ideas and knowledge sharing, leading to innovative solutions.

Additionally, the project highlighted the importance of stakeholder engagement and active involvement throughout the process. 

Furthermore, the collaboration fostered a culture of openness and flexibility, allowing for adaptability to changing circumstances and requirements. 

Overall, the positive lessons learned underscore the importance of collaborative, interdisciplinary approaches, stakeholder engagement, and flexibility in achieving successful project outcomes in the realm of sports technology innovation.

Technical Learnings: Sensors were placed on parts that are relevant for steering interaction (shoulders, handles, kufons). The data that was generated during an internal hackathon showed promising results: The prototype's deployment yielded significant findings, particularly in correlations (r > 0.7) between sensors tracking movements in the same steering direction. However, challenges arose with the handle sensors, where correlations between handles did not align with theoretical expectations of asymmetric steel friction essential for effective steering. This discrepancy suggests a misplacement of sensors, which, when wedged between the handle and the bridge, skewed the data. Further compounding this issue, the calibration process before sensor placement likely contributed to unrealistic maximum force readings, indicating a need for post-implementation calibration to ensure data accuracy. For future measurements the callibration should be done after the sensor placement. This innovation project already benefits from the strong research and business stakeholder network from the EDIH CIMO in alpine technologies, data science and innovation methods.