Literature DB >> 22559638

A real-time respiratory motion monitoring system using KINECT: proof of concept.

Junyi Xia1, R Alfredo Siochi.   

Abstract

PURPOSE: The purpose of this study is to investigate the feasibility of a low-cost respiratory motion monitoring system based on the Microsoft KINECT sensor.
METHODS: The authors increased KINECT's inherent depth resolution from 1 cm to 1 mm via a motion magnification system. Using the KINECT software development kit, the authors programmed the KINECT to capture depth images and determine the average depth over a thoracic region of interest, viewed almost parallel to the subject's surface. KINECT respiratory traces (average depth vs time at a rate of 30 Hz) were acquired from four volunteers and compared with those simultaneously acquired using a commercially available strain gauge respiratory gating system.
RESULTS: The correlation coefficient (CC) between KINECT and strain gauge traces varied from 0.958 to 0.978, with a mean CC of 0.969. This strong correlation was also demonstrated by the joint probability distribution and visual inspection.
CONCLUSIONS: It is feasible to use the KINECT for respiratory motion tracking. Traces are similar to those of a clinically used strain gauge system. The KINECT-based system provides a new and economical way to monitor respiratory motion.

Mesh:

Year:  2012        PMID: 22559638     DOI: 10.1118/1.4704644

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  23 in total

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Journal:  IEEE J Transl Eng Health Med       Date:  2019-10-14       Impact factor: 3.316

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Journal:  Sensors (Basel)       Date:  2020-12-17       Impact factor: 3.576

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Journal:  Int J Radiat Oncol Biol Phys       Date:  2018-04-14       Impact factor: 7.038

5.  Simultaneous Tracking of Cardiorespiratory Signals for Multiple Persons Using a Machine Vision System With Noise Artifact Removal.

Authors:  Ali Al-Naji; Javaan Chahl
Journal:  IEEE J Transl Eng Health Med       Date:  2017-09-29       Impact factor: 3.316

6.  Contactless Monitoring of Breathing Pattern and Thoracoabdominal Asynchronies in Preterm Infants Using Depth Cameras: A Feasibility Study.

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Journal:  IEEE J Transl Eng Health Med       Date:  2022-03-21

7.  Respiratory rate detection algorithm based on RGB-D camera: theoretical background and experimental results.

Authors:  Flavia Benetazzo; Alessandro Freddi; Andrea Monteriù; Sauro Longhi
Journal:  Healthc Technol Lett       Date:  2014-09-29

8.  Effect of Virtual Reality-Based Rehabilitation on Physical Fitness in Patients with Chronic Obstructive Pulmonary Disease.

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Journal:  J Hum Kinet       Date:  2019-10-18       Impact factor: 2.193

9.  A real-time camera-based adaptive breathing monitoring system.

Authors:  Yu-Ching Lee; Abdan Syakura; Muhammad Adil Khalil; Ching-Ho Wu; Yi-Fang Ding; Ching-Wei Wang
Journal:  Med Biol Eng Comput       Date:  2021-06-08       Impact factor: 2.602

10.  Estimating soft tissue thickness from light-tissue interactions--a simulation study.

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Journal:  Biomed Opt Express       Date:  2013-06-14       Impact factor: 3.732

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