AUTHOR=Annavini Eis , Boulland Jean-Luc 

TITLE=Integrated software for multi-dimensional analysis of motion using tracking, electrophysiology, and sensor signals

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2023.1250102

DOI=10.3389/fbioe.2023.1250102

ISSN=2296-4185

ABSTRACT=Tracking and analysis of specific points -of- interest from conventional or high-speed video recordings have been a widely used method for decades in various scientific disciplines such as sport, physiotherapy, and behavioral science. Another method used to characterize movement in 3D involves the use of motion capture systems, which produce files containing a collection of 3D- coordinates and corresponding timestamps. When studying animal or human movement, combining motion tracking with other recording methods–like monitoring muscle activity or sensor signals–can yield valuable insights. However, manual analysis of data from these diverse sources can be time-consuming and prone to errors. To address this issue, this article introduces a new, free, and open-source software developed in MATLAB. This software can be used as-is, or developed further to meet specific requirements. Once the coordinates are imported, multiple tools can be used for data preprocessing, such as to correct mistakes that may have occurred during tracking because of software errors or suboptimal video quality. In addition, the software can import coordinates from multiple cameras and combine them into a unified data series. With these inputs, the software can automatically calculate kinematic parameters and descriptive statistics, enabling swift and accurate analysis of multidimensional motion data. The program can also generate 2D and 3D animations; it features a dedicated tool for analyzing gait cycles. Moreover, the software can import electrophysiology traces and sensor signals, which can be filtered, rectified, smoothed and correlated with the kinematic data in various ways. This approach provides valuable insights into the underlying physiology and biomechanics of the motion. Thanks to its user-friendly graphical user interface, the software is easy to navigate and can be used to analyze complex movements without any need for coding skills. This versatile tool is well-suited for a wide range of experimental contexts, making it a valuable resource for researchers across diverse scientific disciplines.