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Chest Wall Motion Tracking By Contactless Optical Single Camera-Based Method Using Virtual Markers, a Feasibility Study.

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Title: Chest Wall Motion Tracking By Contactless Optical Single Camera-Based Method Using Virtual Markers, a Feasibility Study.
Authors: Bijari, Mohammad Ali, Torshabi, Ahmad Eesmaili
Source: Frontiers in Biomedical Technologies; Winter2026, Vol. 13 Issue 1, p104-116, 13p
Subject Terms: RESPIRATORY mechanics, COMPUTER vision, DIGITAL cameras, COMPUTER-assisted image analysis (Medicine), MULTIPLE target tracking, CHEST (Anatomy)
Abstract: Purpose: Real-time motion tracking of the thorax region of patient's body is a main issue in various parts of medical fields, such as radiotherapy. Several strategies were proposed by using different monitoring hardware. In this work, a contactless method is proposed using an optical camera to trace breathing motion by implementing virtual markers defined on the chest area. A detailed algorithm has been developed to analyze the video frames and track each virtual point in real real-time fashion. Materials and Methods: In this work, Python program and its OpenCV library have been utilized for breathing motion, two-dimensionally. Database utilized in this work is motion data taken from the breathing motion of a real volunteer. The motion data was captured using a cellphone optical camera, and the gathered data was transferred to the in-room computer system by means of WiFi. It's worth mentioning that 15 virtual test points were determined using Artificial Intelligence concept of Python inside the chest area. Results: Final results show that the performance accuracy of the monitoring proposed idea is acceptable. The chest area is determined automatically and will be variable for each patient, uniquely. Various normal and deep breathings were tested in real time at different respiration frequencies. For example, two-dimensional motion displacements of a test point are 4.75 and 7.15 mm for normal and deep breathing, respectively. Conclusion: The main robustness of the proposed motion tracking method is simplicity, contactless, and using virtual markers determination, while real infra-red markers are currently used clinically by being located on patient's chest skin. [ABSTRACT FROM AUTHOR]
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Database: Biomedical Index
Description
Abstract:Purpose: Real-time motion tracking of the thorax region of patient's body is a main issue in various parts of medical fields, such as radiotherapy. Several strategies were proposed by using different monitoring hardware. In this work, a contactless method is proposed using an optical camera to trace breathing motion by implementing virtual markers defined on the chest area. A detailed algorithm has been developed to analyze the video frames and track each virtual point in real real-time fashion. Materials and Methods: In this work, Python program and its OpenCV library have been utilized for breathing motion, two-dimensionally. Database utilized in this work is motion data taken from the breathing motion of a real volunteer. The motion data was captured using a cellphone optical camera, and the gathered data was transferred to the in-room computer system by means of WiFi. It's worth mentioning that 15 virtual test points were determined using Artificial Intelligence concept of Python inside the chest area. Results: Final results show that the performance accuracy of the monitoring proposed idea is acceptable. The chest area is determined automatically and will be variable for each patient, uniquely. Various normal and deep breathings were tested in real time at different respiration frequencies. For example, two-dimensional motion displacements of a test point are 4.75 and 7.15 mm for normal and deep breathing, respectively. Conclusion: The main robustness of the proposed motion tracking method is simplicity, contactless, and using virtual markers determination, while real infra-red markers are currently used clinically by being located on patient's chest skin. [ABSTRACT FROM AUTHOR]
ISSN:23455829
DOI:10.18502/fbt.v13i1.20770