Markerless Respiratory Motion Tracking Using Single Depth Camera

Abstract

The aim of this study is to propose a novel system that has an ability to detect intra-fractional motion during radiotherapy treatment in real-time using three-dimensional surface taken by a depth camera, Microsoft Kinect v1. Our approach introduces three new aspects for three-dimensional surface tracking in radiotherapy treatment. The first aspect is a new algorithm for noise reduction of depth values. Ueda's algorithm was implemented and enabling a fast least square regression of depth values. The second aspect is an application for detection of patient's motion at multiple points in thracoabdominal regions. The third aspect is an estimation of three-dimensional surface from multiple depth values. For evaluation of noise reduction by Ueda's algorithm, two respiratory patterns are measured by the Kinect as well as a laser range meter. The resulting cross correlation coefficients between the laser range meter and the Kinect were 0.982 for abdominal respiration and 0.995 for breath holding. Moreover, the mean cross correlation coefficients between the signals of our system and the signals of Anzai with respect to participant's respiratory motion were 0.90 for thoracic respiration and 0.93 for abdominal respiration, respectively. These results proved that the performance of the developed system was comparable to existing motion monitoring devices. Reconstruction of three-dimensional surface also enabled us to detect the irregular motion and breathing arrest by comparing the averaged depth with predefined threshold values.

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study

“…However, the resulting cross correlation coefficient of the proposed system for all scenarios was 0.9812 which is considered suitable for biomedical applications. When compared to other studies conducted on respiratory monitoring, our correlation coefficient was better than 0.96 [ 31 ], 0.98 [ 36 ], 0.8656 [ 38 ] and 0.90, 0.93 [ 39 ].…”

“…However, this study did not focus on the movement of the diaphragm as well as being prone to some errors in the 3D reconstruction due to a design limitation of the sensors that are unsynchronized in time and frequency. Other studies [ 39 , 40 ] utilized a Kinect-based system to solve issues related to patient set-up misalignment and respiratory motion during radiotherapy. They used depth map information for patient set-up and breathing motion management using several ROIs within the abdominal-thoracic area.…”

“…It can provide a body tracking, 3D body reconstruction, skeletal tracking, joint tracking and human recognition based on information obtained from the depth and colour sensors at any ambient temperature. Because Kinect v2 is commercially available, has specific features at a low cost, and designed for the sustained commercial use, it is an attractive device for many biomedical applications in both domestic and clinical environments [ 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. Figure 1 shows the external view of the Microsoft Kinect v2 sensor.…”

Non-Contact Infrared-Depth Camera-Based Method for Respiratory Rhythm Measurement While Driving

“…2b. The averaged distances are modulated by the movement of the thorax hence related to the respiration of the subject [20]. This final part of the algorithm is based on the patent Respiratory Signal Extraction [10] published in 2018 with number: WO/2018/121861 which has been validated in [21] versus other two video sources and a reference system for respiratory rhythm measurement.…”

Detection of Cardiopulmonary Activity and Related Abnormal Events Using Microsoft Kinect Sensor

“…A study by Tahavori et al [ 20 ] assessed how the Kinect depth sensor might be used to solve the problems associated with patient setup misalignment and respiratory motion management that may be a significant source of error in radiotherapy. Kumagai et al [ 21 ] proposed a non-contact motion tracking system to detect respiratory signals at multiple points on the abdominal-thoracic region based on the Kinect depth sensor. However, there was only one accurate position, which was when a subject faces the Kinect sensor.…”