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Vertical jump data from inertial and optical motion tracking systems
| dc.contributor.author | Rico-Garcia, Mateo | |
| dc.contributor.author | Botero-Valencia, Juan | |
| dc.contributor.author | Hernández-García, Ruber | |
| dc.date.accessioned | 2022-10-19T18:32:36Z | |
| dc.date.available | 2022-10-19T18:32:36Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | http://repositorio.ucm.cl/handle/ucm/4109 | |
| dc.description.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. | es_CL |
| dc.language.iso | en | es_CL |
| dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Chile | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/cl/ | * |
| dc.source | Data, 7(8), 116 | es_CL |
| dc.subject | Biomechanics | es_CL |
| dc.subject | Inertial measurement units-imu | es_CL |
| dc.subject | Motion capture system-mocap | es_CL |
| dc.subject | Sports | es_CL |
| dc.subject | Vertical jump | es_CL |
| dc.title | Vertical jump data from inertial and optical motion tracking systems | es_CL |
| dc.type | Article | es_CL |
| dc.ucm.indexacion | Scopus | es_CL |
| dc.ucm.uri | www.mdpi.com/2306-5729/7/8/116 | es_CL |
| dc.ucm.doi | doi.org/10.3390/data7080116 | es_CL |
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