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Proceedings ArticleDOI

Real-time vision based respiration monitoring system

TLDR
A vision based contactless method of monitoring respiration rate that involves image and signal processing techniques to extract chest and abdominal movements' information from a sequence of video images recorded using a single video camera confirmed its effectiveness.
Abstract
Respiration rate is an important indicator of an individual's health. Existing respiration monitoring systems are usually contact based, and so the sensing device is attached to the subject's body. This creates discomfort to the patient and can interfere with normal breathing. This paper presents a vision based contactless method of monitoring respiration rate. The method involves image and signal processing techniques to extract chest and abdominal movements' information from a sequence of video images recorded using a single video camera. The system provided a real-time respiration monitoring information consisting of a plot of respiration signal and the value of respiration rate. The respiration data could also be stored to allow for off-line analysis to be performed. A caparison of the developed method against a number of contact-based respiration monitoring systems confirmed its effectiveness. The system is currently being further developed to make its operation more robust.

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Citations
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Proceedings ArticleDOI

Detecting Pulse from Head Motions in Video

TL;DR: This method tracks features on the head and performs principal component analysis (PCA) to decompose their trajectories into a set of component motions and chooses the component that best corresponds to heartbeats based on its temporal frequency spectrum.
Journal ArticleDOI

Respiration Rate Monitoring Methods: A Review

TL;DR: A review of respiration monitoring approaches (both contact and noncontact) is provided and a description of thermal imaging based and vision based noncontact respiration Monitoring approaches currently developing is provided.
Journal ArticleDOI

A Survey of Healthcare Internet of Things (HIoT): A Clinical Perspective

TL;DR: This article surveys the existing and emerging technologies that can enable this vision for the future of healthcare, particularly, in the clinical practice of healthcare and discusses the emerging directions, open issues, and challenges.
Proceedings ArticleDOI

Camera-based system for contactless monitoring of respiration

TL;DR: A camera-based monitoring system to reliably measure respiration rate without any body contact is proposed and a computationally efficient algorithm to extract raw breathing signals from the video stream has been developed and implemented.
Journal ArticleDOI

Video-based respiration monitoring with automatic region of interest detection.

TL;DR: A video-based respiration monitoring method that automatically detects a respiratory region of interest (RoI) and signal using a camera and seems to provide a valid solution to ECG in confined motion scenarios, though precision may be reduced for neonates.
References
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Journal ArticleDOI

Breathing Detection: Towards a Miniaturized, Wearable, Battery-Operated Monitoring System

TL;DR: The main challenges associated with noninvasive, continuous, wearable, and long-term breathing monitoring are analyzed and an algorithm has been devised to detect breathing, suitable for a miniature sensor device.
Proceedings ArticleDOI

Touchless monitoring of breathing function

TL;DR: A novel method based on statistical modeling of dynamic thermal data captured through an infrared imaging system for noncontact measurement of breathing function that is expected to find applications in the next generation of touchless polygraphy and in preventive health care.
Journal ArticleDOI

An improved algorithm for respiration signal extraction from electrocardiogram measured by conductive textile electrodes using instantaneous frequency estimation

TL;DR: An improved algorithm for the extraction of respiration signal from the ECG-derived respiration (EDR) signal acquisition using conductive textile electrodes located in bed, and an optimal EDR signal among the three EDR signals derived from each lead is selected.
Proceedings ArticleDOI

Validation of an ECG-derived respiration monitoring method

TL;DR: The method proposed here includes automatic optimal lead(s) selection from multiple lead systems, calculates the EDR-values from QRS-area variations and obtains a respiratory waveform through interpolation, identifying the respiratory cycles on the wave form through a min-max detection method.
Proceedings ArticleDOI

Tracking human breath in infrared imaging

TL;DR: A novel tracker to capture the human breathing signal through an infrared imaging method that can handle significant head movement and object occlusion and mean shift localization-based particle filtering is proposed.
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