Quantitative Assessment of Spontaneous Breathing in Children: Evaluation of a Depth Camera System

Rehouma, Haythem; Noumeir, Rita; Essouri, Sandrine; Jouvet, Philippe

doi:10.1109/tim.2019.2951889

Cited by 14 publications

(20 citation statements)

References 28 publications

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“…Respiratory rate seems to be one the most attractive parameters using the non-contact methods and has been addressed in a variety of conferences and journal papers divided as follows: [ 19 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 ] (over the period 2010–2015), [ 9 , 11 , 12 , 29 , 32 , 42 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 53 , 55 , 61 , 69 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 ,…”

Section: Resultsmentioning

confidence: 99%

“…Monitoring of pulmonary function such as tidal volume, minute ventilation, forced vital capacity, and forced expiratory volume has been studied in many works as well in [ 65 , 116 , 117 , 118 , 119 , 120 ] (2010–2015), [ 6 , 7 , 8 , 9 , 32 , 46 , 52 , 88 , 91 , 92 , 100 , 103 , 110 , 121 , 122 , 123 , 124 ] (2016–2020).…”

Section: Resultsmentioning

confidence: 99%

“…Many contactless optical systems, based on RGB-D cameras have been previously described by our group in [ 32 , 46 , 91 , 160 ]. The experiments were performed for simulated breathing scenarios and for a mechanically ventilated 4-month and 20-day old female, weighing 6.6 kg [ 91 ].…”

Section: Discussionmentioning

confidence: 99%

“…Research approaches were moving towards investigation of many types of imaging data such as color [ 10 , 113 ], depth [ 91 , 111 , 112 ], and infrared [ 107 , 108 , 114 , 115 , 159 , 247 ] images. This trend resulted from the emergence of new affordable acquisition devices, such as, Kinect depth sensor [ 32 , 46 ], Orbbec Astra mobile 3D cameras [ 48 , 240 ], RealSense technology [ 105 ], and FLIR thermic cameras [ 48 , 239 ]. Such devices are unlocking the next level computer vision applications.…”

Section: Discussionmentioning

confidence: 99%

“…Even if some of these barriers were overcome, it is very important to develop and document more synthetic databases. Simulated data are possible and easy to acquire, and results based on them are important to report [ 46 , 160 ].…”

Section: Discussionmentioning

confidence: 99%

See 4 more Smart Citations

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

Rehouma

Noumeir

Essouri

et al. 2020

Sensors

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 3 more Smart Citations

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

Rehouma

Noumeir

Essouri

et al. 2020

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

Continuous non‐contact respiratory rate and tidal volume monitoring using a Depth Sensing Camera

Addison

Smit

Jacquel

et al. 2021

J Clin Monit Comput

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The monitoring of respiratory parameters is important across many areas of care within the hospital. Here we report on the performance of a depth-sensing camera system for the continuous non-contact monitoring of Respiratory Rate (RR) and Tidal Volume (TV), where these parameters were compared to a ventilator reference. Depth sensing data streams were acquired and processed over a series of runs on a single volunteer comprising a range of respiratory rates and tidal volumes to generate depth-based respiratory rate (RRdepth) and tidal volume (TVdepth) estimates. The bias and root mean squared difference (RMSD) accuracy between RRdepth and the ventilator reference, RRvent, across the whole data set was found to be -0.02 breaths/min and 0.51 breaths/min respectively. The least squares fit regression equation was determined to be: RRdepth = 0.96 × RRvent + 0.57 breaths/min and the resulting Pearson correlation coefficient, R, was 0.98 (p < 0.001). Correspondingly, the bias and root mean squared difference (RMSD) accuracy between TVdepth and the reference TVvent across the whole data set was found to be − 0.21 L and 0.23 L respectively. The least squares fit regression equation was determined to be: TVdepth = 0.79 × TVvent—0.01 L and the resulting Pearson correlation coefficient, R, was 0.92 (p < 0.001). In conclusion, a high degree of agreement was found between the depth-based respiration rate and its ventilator reference, indicating that RRdepth is a promising modality for the accurate non-contact respiratory rate monitoring in the clinical setting. In addition, a high degree of correlation between depth-based tidal volume and its ventilator reference was found, indicating that TVdepth may provide a useful monitor of tidal volume trending in practice. Future work should aim to further test these parameters in the clinical setting.

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A real-time camera-based adaptive breathing monitoring system

Lee

Syakura

Khalil

et al. 2021

Med Biol Eng Comput

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Breathing is one of the vital signs used to assess the physical health of a subject. Non-contact-based measurements of both breathing rate and changes in breathing rate help monitor health condition of subjects more flexibly. In this paper, we present an improved real-time camera-based adaptive breathing monitoring system, which includes real time (1) adaptive breathing motion detection, (2) adaptive region of interest detection to eliminate environmental noise, (3) breathing and body movement classification, (4) respiration rate estimation, (5) monitor change in respiration rate to examine overall health of an individual, and (6) online adaptation to lighting. The proposed system does not pose any positional and postural constraint. For evaluation, 30 videos of 15 animals are tested with drugs to simulate various medical conditions and breathing patterns, and the results from the proposed system are compared with the outputs of an existing FDA-approved invasive medical system for patient monitoring. The results show that the proposed method performs significantly correlated RR results to the reference medical device with the correlation coefficient equal to 0.92 and p -value less than 0.001, and more importantly the proposed video-based method is demonstrated to produce alarms 10 to 20 s earlier than the benchmark medical device. Graphical abstract The proposed system flowchart to extract the respiratory pattern from video.

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Quantitative Assessment of Spontaneous Breathing in Children: Evaluation of a Depth Camera System

Cited by 14 publications

References 28 publications

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

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

Continuous non‐contact respiratory rate and tidal volume monitoring using a Depth Sensing Camera

A real-time camera-based adaptive breathing monitoring system

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