» Articles » PMID: 33348827

Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration

Overview
Journal Sensors (Basel)
Publisher MDPI
Specialty Biotechnology
Date 2020 Dec 22
PMID 33348827
Citations 9
Authors
Affiliations
Soon will be listed here.
Abstract

Assessment of respiratory function allows early detection of potential disorders in the respiratory system and provides useful information for medical management. There is a wide range of applications for breathing assessment, from measurement systems in a clinical environment to applications involving athletes. Many studies on pulmonary function testing systems and breath monitoring have been conducted over the past few decades, and their results have the potential to broadly impact clinical practice. However, most of these works require physical contact with the patient to produce accurate and reliable measures of the respiratory function. There is still a significant shortcoming of non-contact measuring systems in their ability to fit into the clinical environment. The purpose of this paper is to provide a review of the current advances and systems in respiratory function assessment, particularly camera-based systems. A classification of the applicable research works is presented according to their techniques and recorded/quantified respiration parameters. In addition, the current solutions are discussed with regards to their direct applicability in different settings, such as clinical or home settings, highlighting their specific strengths and limitations in the different environments.

Citing Articles

Contactless monitoring to prevent self-harm and suicide in custodial settings: Protocol for a global scoping review.

Bosworth R, Everett B, Breen P, Klein J, Psillakis E, Abbott P BMJ Open. 2024; 14(10):e087925.

PMID: 39461865 PMC: 11529512. DOI: 10.1136/bmjopen-2024-087925.


For a clinical application of optical triangulation to assess respiratory rate using an RGB camera and a line laser.

Jeong Y, Song C, Lee S, Son J BMC Med Imaging. 2024; 24(1):274.

PMID: 39390449 PMC: 11468289. DOI: 10.1186/s12880-024-01448-5.


Respiratory motion tracking of the thoracoabdominal surface based on defect-aware point cloud registration.

Wang X, Liu T, Mai S Biomed Eng Lett. 2024; 14(5):1057-1068.

PMID: 39220029 PMC: 11362397. DOI: 10.1007/s13534-024-00390-3.


Extrinsic Calibration for a Modular 3D Scanning Quality Validation Platform with a 3D Checkerboard.

Kaiser M, Brusa T, Bertsch M, Wyss M, Cukovic S, Meixner G Sensors (Basel). 2024; 24(5).

PMID: 38475112 PMC: 10934973. DOI: 10.3390/s24051575.


A Differential Inertial Wearable Device for Breathing Parameter Detection: Hardware and Firmware Development, Experimental Characterization.

De Fazio R, Greco M, De Vittorio M, Visconti P Sensors (Basel). 2022; 22(24).

PMID: 36560322 PMC: 9787627. DOI: 10.3390/s22249953.


References
1.
Aoki H, Nakamura H . Non-Contact Respiration Measurement during Exercise Tolerance Test by Using Kinect Sensor. Sports (Basel). 2018; 6(1). PMC: 5969190. DOI: 10.3390/sports6010023. View

2.
Yao H, Ge C, Xue J, Zheng N . A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light. Sensors (Basel). 2017; 17(4). PMC: 5422166. DOI: 10.3390/s17040805. View

3.
Seppenwoolde Y, Berbeco R, Nishioka S, Shirato H, Heijmen B . Accuracy of tumor motion compensation algorithm from a robotic respiratory tracking system: a simulation study. Med Phys. 2007; 34(7):2774-84. DOI: 10.1118/1.2739811. View

4.
Roomkham S, Lovell D, Cheung J, Perrin D . Promises and Challenges in the Use of Consumer-Grade Devices for Sleep Monitoring. IEEE Rev Biomed Eng. 2018; 11:53-67. DOI: 10.1109/RBME.2018.2811735. View

5.
Kwasniewska A, Szankin M, Ruminski J, Kaczmarek M . Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery. Annu Int Conf IEEE Eng Med Biol Soc. 2020; 2019:2744-2747. DOI: 10.1109/EMBC.2019.8857764. View