Distant pulse oximetry based on skin region extraction and multi-spectral measurement

Capturing vital signs, specifically heart rate and oxygen saturation, is essential in care situations. Clinical pulse oximetry solutions work contact-based by clips or otherwise fixed sensor units which have sometimes undesired impact on the patient. A typical example would be pre-term infants in neonatal care which require permanent monitoring and have a very fragile skin. This requires a regular change of the sensor unit location by the staff to avoid skin damage. To improve patient comfort and to reduce care effort, a feasibility study with a camera-based passive optical method for contactless pulse oximetry from a distance is performed. In contrast to most existing research on contactless pulse oximetry, a task-optimized multi-spectral sensor unit instead of a standard RGB-camera is proposed. This first allows to avoid the widely used green spectral range for distant heart rate measurement, which is unsuitable for pulse oximetry due to nearly equal spectral extinction coefficients of saturated oxy-hemoglobin and non-saturated hemoglobin. Second, it also better addresses the challenge of the worse signal-to-noise ratio than in the contact-based or active measurement, e.g., caused by background illumination. Signal noise from background illumination is addressed in several ways. The key part is an automated reference measurement of background illumination by automated patient localization in the acquired images by extraction of skin and background regions with a CNN-based detector. Due to the custom spectral ranges, the detector is trained and optimized for this specific setup. Altogether, allowing a contactless measurement, the studied concept promises to improve the care of patients where skin contact has negative effects.

[1]  E. Gratton,et al.  Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry , 1995 .

[2]  Thomas B. Moeslund,et al.  Estimation of Heartbeat Peak Locations and Heartbeat Rate from Facial Video , 2017, SCIA.

[3]  T. Ward,et al.  Noncontact simultaneous dual wavelength photoplethysmography: a further step toward noncontact pulse oximetry. , 2007, The Review of scientific instruments.

[4]  E. Bresch,et al.  Calibration of Contactless Pulse Oximetry , 2016, Anesthesia and analgesia.

[5]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[6]  W. Verkruysse,et al.  Non-contact heart rate monitoring utilizing camera photoplethysmography in the neonatal intensive care unit - a pilot study. , 2013, Early human development.

[7]  Kwang Suk Park,et al.  Validation of heart rate extraction using video imaging on a built-in camera system of a smartphone , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  F. Mastik,et al.  Contactless Multiple Wavelength Photoplethysmographic Imaging: A First Step Toward “SpO2 Camera” Technology , 2005, Annals of Biomedical Engineering.

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

[10]  T. Ward,et al.  A CMOS Camera-Based Pulse Oximetry Imaging System , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

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

[12]  B. Li,et al.  Non-contact detection of oxygen saturation based on visible light imaging device using ambient light. , 2013, Optics express.