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Vertical Jump Data from Inertial and Optical Motion Tracking Systems

Author

Listed:
  • Mateo Rico-Garcia

    (Facultad de Ingeniería, Institución Universitaria Pascual Bravo, Calle 73 No. 73A-226, Medellin 050034, Colombia)

  • Juan Botero-Valencia

    (Grupo Sistemas de Control y Robótica, Facultad de Ingenierías, Instituto Tecnológico Metropolitano—ITM, Calle 73 No. 76A-354, Medellin 050034, Colombia)

  • Ruber Hernández-García

    (Research Center for Advanced Studies of Maule (CIEAM), Universidad Católica del Maule, Avenida San Miguel 3605, Talca 3480094, Chile)

Abstract

Motion capture (MOCAP) is a widely used technique to record human, animal, and object movement for various applications such as animation, biomechanical assessment, and control systems. Different systems have been proposed based on diverse technologies, such as visible light cameras, infrared cameras with passive or active markers, inertial systems, or goniometer-based systems. Each system has pros and cons that make it usable in different scenarios. This paper presents a dataset that combines Optical Motion and Inertial Systems, capturing a well-known sports movement as the vertical jump. As a reference system, the optical motion capture consists of six Flex 3 Optitrack cameras with 100 FPS. On the other hand, we developed an inertial system consisting of seven custom-made devices based on the IMU MPU-9250, which includes a three-axis magnetometer, accelerometer and gyroscope, and an embedded Digital Motion Processor (DMP) attached to a microcontroller mounted on a Teensy 3.2 with an ARM Cortex-M4 processor with wireless operation using Bluetooth. The purpose of taking IMU data with a low-cost and customized system is the deployment of applications that can be performed with similar hardware and can be adjusted to different areas. The developed measurement system is flexible, and the acquisition format and enclosure can be customized. The proposed dataset comprises eight jumps recorded from four healthy humans using both systems. Experimental results on the dataset show two usage examples for measuring joint angles and COM position. The proposed dataset is publicly available online and can be used in comparative algorithms, biomechanical studies, skeleton reconstruction, sensor fusion techniques, or machine learning models.

Suggested Citation

  • Mateo Rico-Garcia & Juan Botero-Valencia & Ruber Hernández-García, 2022. "Vertical Jump Data from Inertial and Optical Motion Tracking Systems," Data, MDPI, vol. 7(8), pages 1-16, August.
  • Handle: RePEc:gam:jdataj:v:7:y:2022:i:8:p:116-:d:890107
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    References listed on IDEAS

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    1. Justin Trautmann & Lin Zhou & Clemens Markus Brahms & Can Tunca & Cem Ersoy & Urs Granacher & Bert Arnrich, 2021. "TRIPOD—A Treadmill Walking Dataset with IMU, Pressure-Distribution and Photoelectric Data for Gait Analysis," Data, MDPI, vol. 6(9), pages 1-19, August.
    2. Manuel Stein & Halldór Janetzko & Daniel Seebacher & Alexander Jäger & Manuel Nagel & Jürgen Hölsch & Sven Kosub & Tobias Schreck & Daniel A. Keim & Michael Grossniklaus, 2017. "How to Make Sense of Team Sport Data: From Acquisition to Data Modeling and Research Aspects," Data, MDPI, vol. 2(1), pages 1-23, January.
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