Baseline drift vector of multiple points on body surface using a near-infrared camera

Area of Science:

• Biomechanics
• Biomedical Engineering
• Motion Analysis

Background:

• Accurate tracking of body surface movement is crucial for understanding physiological processes and biomechanical analysis.
• Existing methods may be costly or invasive, limiting widespread application.

Purpose of the Study:

• To develop and validate a low-cost, non-invasive system for extracting the three-dimensional (3D) baseline drift vector (BDV) from multiple body surface points.
• To demonstrate the importance of 3D tracking for analyzing subtle body surface displacements.

Main Methods:

• Utilized a near-infrared camera (Kinect V2) and custom software to track 30 markers placed on the body surface of 8 healthy volunteers for 30 minutes.
• Developed a technique to extract the BDV from acquired 3D coordinates and analyzed BDV per minute to assess movement exceeding tolerance levels.
• Investigated correlations among BDVs from different body sites.

Main Results:

• Successfully extracted the BDV for the sternum, rib, and abdomen.
• Observed longitudinal baseline drift in healthy volunteers, with a maximum probability of 30% for BDV exceeding 1mm/min and 15% for exceeding 2mm/min.
• Correlations among BDVs suggested the potential to differentiate whole-body translational movement from respiratory motion.

Conclusions:

• A cost-effective, non-invasive 3D tracking system for multiple body surface points was successfully constructed.
• The established method for BDV extraction and the observed longitudinal drift underscore the necessity of 3D tracking in body surface analysis.