Development of a Low-Cost Markerless Optical Motion Capture System for Gait Analysis and Anthropometric Parameter Quantification

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 11; p. 3371
• Main Authors: Espitia-Mora, Laura Alejandra, Vélez-Guerrero, Manuel Andrés, Callejas-Cuervo, Mauro
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 24.05.2024; MDPI
• Subjects: Accuracy; Adult; Algorithms; Animation; Anthropometry; Anthropometry - methods; artificial intelligence; Biomechanical Phenomena; Biomechanics; Cameras; Computer animation; Computer programs; Computer vision; Data mining; Deep learning; depth sensors; Economic aspects; Electromyography; Gait; Gait - physiology; Gait Analysis - instrumentation; Gait Analysis - methods; Human performance; Humans; Machine vision; Male; Medical equipment; Medical research; Microelectromechanical systems; Motion Capture; Neural networks; optical analysis; Prostheses; R&D; RealSense; Rehabilitation; Research & development; Sensors; Trends; rehabilitation; sports; entertainment; computer vision; RealSense; depth sensors; optical analysis; lower limbs; motion capture; artificial intelligence
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24113371

Technological advancements have expanded the range of methods for capturing human body motion, including solutions involving inertial sensors (IMUs) and optical alternatives. However, the rising complexity and costs associated with commercial solutions have prompted the exploration of more cost-effective alternatives. This paper presents a markerless optical motion capture system using a RealSense depth camera and intelligent computer vision algorithms. It facilitates precise posture assessment, the real-time calculation of joint angles, and acquisition of subject-specific anthropometric data for gait analysis. The proposed system stands out for its simplicity and affordability in comparison to complex commercial solutions. The gathered data are stored in comma-separated value (CSV) files, simplifying subsequent analysis and data mining. Preliminary tests, conducted in controlled laboratory environments and employing a commercial MEMS-IMU system as a reference, revealed a maximum relative error of 7.6% in anthropometric measurements, with a maximum absolute error of 4.67 cm at average height. Stride length measurements showed a maximum relative error of 11.2%. Static joint angle tests had a maximum average error of 10.2%, while dynamic joint angle tests showed a maximum average error of 9.06%. The proposed optical system offers sufficient accuracy for potential application in areas such as rehabilitation, sports analysis, and entertainment.