Automatic non-contact monitoring of the respiratory rate of neonates using a structured light camera

This paper introduces an automatic non-contact monitoring method for measuring the respiratory rate of neonates using a structured light camera. The current monitoring bears several issues causing pressure marks, skin irritations and eczema. A structured light camera provides distance data. Our non-contact approach detects the thorax area automatically using a plane segmentation and calculates the respiratory rate from the movement of the thorax. Our method was tested and validated using the baby simulator SimBaby by Laerdal. We used different breathing rates corresponding to preterm neonates, mature neonates and babies aged up to nine months as well as two different breathing modes with differing breathing strokes. Furthermore, measurements were taken of two positions: the baby lying on its back and on its stomach.

[1]  Soon-Yong Park,et al.  Real-Time External Respiratory Motion Measuring Technique Using an RGB-D Camera and Principal Component Analysis † , 2017, Sensors.

[2]  E. Graves,et al.  Radar remote monitoring of vital signs , 2009, IEEE Microwave Magazine.

[3]  Lorenzo Scalise,et al.  Non contact measurement of heart and respiration rates based on Kinect™ , 2014, 2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA).

[4]  Sandy Rihana,et al.  Kinect2 — Respiratory movement detection study , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[5]  L. Tarassenko,et al.  Continuous non-contact vital sign monitoring in neonatal intensive care unit , 2014, Healthcare technology letters.

[6]  Changzhi Li,et al.  Verification of a non-contact vital sign monitoring system using an infant simulator , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[7]  Ales Procházka,et al.  Breathing Analysis Using Thermal and Depth Imaging Camera Video Records , 2017, Sensors.

[8]  Steffen Leonhardt,et al.  Intelligent neonatal monitoring based on a virtual thermal sensor , 2014, BMC Medical Imaging.

[9]  E. Chadwick,et al.  Tidal breathing parameters measured by structured light plethysmography in children aged 2–12 years recovering from acute asthma/wheeze compared with healthy children , 2018, Physiological reports.

[10]  Joachim Hornegger,et al.  Robust real-time 3D respiratory motion detection using time-of-flight cameras , 2008, International Journal of Computer Assisted Radiology and Surgery.

[11]  P. A. Gorry General least-squares smoothing and differentiation by the convolution (Savitzky-Golay) method , 1990 .

[12]  Rafik A. Goubran,et al.  The detection of breathing behavior using Eulerian-enhanced thermal video , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[13]  Robert Weigel,et al.  Six-Port Radar Sensor for Remote Respiration Rate and Heartbeat Vital-Sign Monitoring , 2013, IEEE Transactions on Microwave Theory and Techniques.

[14]  Albert van der Veen,et al.  Development of a baby friendly non-contact method for measuring vital signs: First results of clinical measurements in an open incubator at a neonatal intensive care unit , 2014, Photonics West - Biomedical Optics.

[15]  Rainer Stiefelhagen,et al.  Breathing Rate Monitoring during Sleep from a Depth Camera under Real-Life Conditions , 2017, 2017 IEEE Winter Conference on Applications of Computer Vision (WACV).

[16]  Steffen Leonhardt,et al.  Estimation of respiratory rate from thermal videos of preterm infants , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[17]  G. Matthews,et al.  A non-contact vital signs monitor. , 2000, Critical reviews in biomedical engineering.

[18]  O. Boric-Lubecke,et al.  Non-contact respiratory rate measurement validation for hospitalized patients , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[19]  A S Malik,et al.  Novel health monitoring method using an RGB camera. , 2017, Biomedical optics express.

[20]  Wassim Bouachir,et al.  Computerized Medical Imaging and Graphics 3 D imaging system for respiratory monitoring in pediatric intensive care environment , 2018 .

[21]  Ali Al-Naji,et al.  Remote respiratory monitoring system based on developing motion magnification technique , 2016, Biomed. Signal Process. Control..

[22]  Wassim Bouachir,et al.  A computer vision method for respiratory monitoring in intensive care environment using RGB-D cameras , 2017, 2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA).

[23]  Emanuele Frontoni,et al.  Non-Contact Monitoring of Preterm Infants Using RGB-D Camera , 2015 .

[24]  S. Longhi,et al.  Respiratory rate detection algorithm based on RGB-D camera: theoretical background and experimental results. , 2014, Healthcare technology letters.

[25]  B. Cooper,et al.  Mini review shows that structured light plethysmography provides a non‐contact method for evaluating breathing patterns in children , 2019, Acta paediatrica.

[26]  Min-Hyung Choi,et al.  WiKiSpiro: non-contact respiration volume monitoring during sleep , 2016, S3@MobiCom.

[27]  Abbas K. Abbas,et al.  Neonatal non-contact respiratory monitoring based on real-time infrared thermography , 2011, Biomedical engineering online.

[28]  Ales Procházka,et al.  Microsoft Kinect Visual and Depth Sensors for Breathing and Heart Rate Analysis , 2016, Sensors.

[29]  L. Tarassenko,et al.  Non-contact video-based vital sign monitoring using ambient light and auto-regressive models , 2014, Physiological measurement.

[30]  G. Piacentini,et al.  Structured Light Plethysmography (SLP): Management and follow up of a paediatric patient with pneumonia , 2017, Respiratory medicine case reports.

[31]  Robert Weigel,et al.  A contactless system for continuous vital sign monitoring in palliative and intensive care , 2018, 2018 Annual IEEE International Systems Conference (SysCon).

[32]  Steffen Leonhardt,et al.  A novel ultra-wideband 80 GHz FMCW radar system for contactless monitoring of vital signs , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).