Contact-Free Respiration Rate Monitoring Using a Pan–Tilt Thermal Camera for Stationary Bike Telerehabilitation Sessions

Chauvin, Ronan; Hamel, Mathieu; Brière, Simon; Ferland, François; Grondin, François; Létourneau, Dominic; Tousignant, Michel; Michaud, François

doi:10.1109/jsyst.2014.2336372

Cited by 41 publications

(26 citation statements)

References 20 publications

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“…In contrast with other methods, which need a manual selection of the region of interest [12,22,25], our approach allows an automatic detection of the nose in the first frame. In addition, a flexible algorithm for robust estimation of local breath-to-breath intervals from IRT waveform was implemented.…”

Section: Introductionmentioning

confidence: 99%

Remote monitoring of breathing dynamics using infrared thermography

Pereira

Czaplik

et al. 2015

Biomed. Opt. Express

139

107

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Abstract:An atypical or irregular respiratory frequency is considered to be one of the earliest markers of physiological distress. In addition, monitoring of this vital parameter plays a major role in diagnosis of respiratory disorders, as well as in early detection of sudden infant death syndrome. Nevertheless, the current measurement modalities require attachment of sensors to the patient's body, leading to discomfort and stress. The current paper presents a new robust algorithm to remotely monitor breathing rate (BR) by using thermal imaging. This approach permits to detect and to track the region of interest (nose) as well as to estimate BR. In order to study the performance of the algorithm, and its robustness against motion and breathing disorders, three different thermal recordings of 11 healthy volunteers were acquired (sequence 1: normal breathing; sequence 2: normal breathing plus arbitrary head movements; and sequence 3: sequence of specific breathing patterns). Thoracic effort (piezoplethysmography) served as "gold standard" for validation of our results. An excellent agreement between estimated BR and ground truth was achieved. Whereas the mean correlation for sequence 1-3 were 0.968, 0.940 and 0.974, the mean absolute BR errors reached 0.33, 0.55 and 0.96 bpm (breaths per minute), respectively. In brief, this work demonstrates that infrared thermography is a promising, clinically relevant alternative for the currently available measuring modalities due to its performance and diverse remarkable advantages.

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Section: Introductionmentioning

confidence: 99%

Remote monitoring of breathing dynamics using infrared thermography

Pereira

Czaplik

et al. 2015

Biomed. Opt. Express

139

107

View full text Add to dashboard Cite

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“…Statistical modeling of dynamic thermal data captured. It works by capturing the information contained in the thermal signal emitted from major superficial vessels [15], [36], [37].…”

Section: Related Workmentioning

confidence: 99%

“…The two well-known state-of-the-art (SOA) wireless vitals monitoring methods are based on radio-frequency (RF) (radar) [2], [3], [5], [7]- [9] and imaging (camera) [4], [10]- [15]. However, these efforts are in their infancy and can present safety (RF signal penetration through the body) and privacy (camera) concerns.…”

Section: Introductionmentioning

confidence: 99%

Non-Contact Vital Signs Monitoring Through Visible Light Sensing

Abuella

Ekin

2020

IEEE Sensors J.

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In this paper, we present a wireless system for monitoring human vital signs like breathing and heartbeat via visible light sensing (VLS). Typical techniques for tracking heathcondition require body contact and most of these techniques are intrusive in nature. Body contact might irritate the patient's skin and he/she might feel uncomfortable while sensors are touching their body. However, in this method, we can estimate the breathing and heartbeat rates without any body contact using a photo-detector. Vitals monitoring using VLS make use of the idea that reflected light signal off the human body received at the photo-detector will be affected by the chest motion during heartbeats and breathing. We implemented the system using off-the-shelf photo-detector and a signal acquisition system and obtained the results for different people and in different scenarios. We found out that the accuracy of our system compared to FDA approved equipment to measure heartbeats and breathing rate is 94%. This system can be used in various domains and applications in medical facilities and in residential homes.A provisional patent (US#62/639,524) has been obtained for this work.

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“…THE GRAY RECTANGLE INDICATES THE ULTRASOUND (US) PLANE, WHILE LIGHT GRAY OBJECT INDICATES US PROBE. tumor position based on the linear accumulation of extern signals. In view of the nonlinear respiratory motion, Kalman Filter was adapted for introducing weak nonlinearity into predictive model [11,13,14,15]. But, the heavy computation load and weak linearity limit their further application.…”

Section: B Related Workmentioning

confidence: 99%

Real-time Tumor Tracking with Respiratory Motion Based on Short-term Prediction

Tian¹,

Song²,

Ren³

2017

Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

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Abstract-The purpose of this study is to design a 3D navigation strategy with 2D ultrasonic images, with the assumption that the internal target trajectory could be evaluated with extern surrogate signals. This paper first proposes a simple 3D navigation strategy and then designs a fast tumor tracking system that exploits learning based methods, which learns the mapping relation between the external surrogate signals and the internal tumor trajectory. This paper uses our own retrospective clinical data to test the developed system. The experimental results show that this system has the potential to implementing high accuracy tumor tracking and navigation.

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Contact-Free Respiration Rate Monitoring Using a Pan–Tilt Thermal Camera for Stationary Bike Telerehabilitation Sessions

Cited by 41 publications

References 20 publications

Remote monitoring of breathing dynamics using infrared thermography

Remote monitoring of breathing dynamics using infrared thermography

Non-Contact Vital Signs Monitoring Through Visible Light Sensing

Real-time Tumor Tracking with Respiratory Motion Based on Short-term Prediction

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