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SNAP Move-Toolbox

The core competence of the Move Toolbox lies in the collection and analysis of movement data and research projects with the support of AI.

Intelligent motion data analysis:
Move Toolbox drives education & research forward!

Our Move Toolbox offers a perfect combination of hardware and software that enables educational institutions and researchers to capture, analyze and use movement data. Best of all, no programming skills are required. With a user-friendly interface and intuitive application, you can get started right away to gain valuable insights - everything you need in a single toolset.


Well-known universities are already benefiting from the Move toolbox:


The Problem

Traditional teaching methods often lag behind in integrating the latest technologies and methods into the classroom. Students may not be adequately prepared for the demands of today's professional practice. Research and innovation in various disciplines may be limited due to the lack of advanced tools and technologies.

SNAP's solutions


Modernization of teaching


Application of AI in education


Practical training


Progressive research


Pioneer in education


Our IMU sensors (BlueKin) are portable and have integrated actuators (version IRGB20C000). For example, sensor acceleration, angular velocity, and orientation, as well as gyroscopes can be measured. The sensor is used, among other things, to detect movement. Each sensor-based module wirelessly transmits data from the inertial sensor to a receiver via Bluetooth Low Energy. The receiver can either be an app on a smartphone or a receiver on the work computer. The IMU sensors can be purchased from SNAP with or without software.


Module der Software

Software for data recording (Recording Tool)

  • Guided data recording: Individual movements can be recorded directly with labels. Labeled data is therefore directly available for AI training.

Software for AI training (training module)

  • The software allows AI training with neural networks and the labelled movement data.

  • Visualisation of the training results using learning curves and confusion matrix.

Inference module

  • Trained models can be used in real-time and offline inference
    Python interface for own use of real-time inference available.

Possible uses and application


Sports science



The Move toolbox offers advantages for...

  • Application of theoretical knowledge in practice with the Move Toolbox

  • Developing practical skills in recording and analyzing movement data

  • Promoting interdisciplinary collaboration for complex research projects

  • Cooperation between students from different disciplines

  • Focus on motion data and artificial intelligence

  • Broadening career prospects by using the Move Toolbox

  • Increased attractiveness for employers in various industries


  • Use of the Move toolbox in courses for innovative teaching methods

  • Promoting active student participation in the learning process
  • Expansion of research activities through integration of the Move Toolbox
  • Generating new insights in the areas of movement data and artificial intelligence
  • Use of advanced technologies strengthens the reputation of professors
  • Increasing the university's visibility in the research community


  • Differentiation from other universities through integration of the Move toolbox

  • Attracting students and increasing the attractiveness of the faculty

  • Strengthening the university's reputation by using the Move Toolbox

  • Increasing the attractiveness for potential students, researchers and partners

  • Building partnerships with companies and organizations

  • Potential for research and development projects, internships and career opportunities for students


“The collaboration with SNAP GmbH was constructive and goal-oriented right from the start. I was informed about the next steps at every stage and solutions were developed together when difficulties arose. I can imagine further joint projects with SNAP GmbH in the future."

Dr. Markus Schmidt, Institute of Sport and Sport Sciences, Dortmund University of Technology

Alexa Young, CA

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