Integrated software for multi-dimensional analysis of motion using tracking, electrophysiology, and sensor signals - Annavini, Eis; Boulland, Jean-Luc (Frontiers in Bioengineering and Biotechnology, 2023)
Tracking followed by analysis of specific point-of-interest from conventional or high-speed video recordings have been widely used 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, generate 2D and 3D animations, and analyze gait cycles, enabling swift and accurate analysis of multidimensional motion data. 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. 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.