Camera-Based Vital Signs Monitoring During Sleep – A Proof of Concept Study

Gastel, Mark van; Stuijk, Sander; Overeem, Sebastiaan; Dijk, Hans van; Gilst, Merel M van; Haan, G. de

doi:10.1109/jbhi.2020.3045859

Cited by 28 publications

(28 citation statements)

References 16 publications

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“…Beyond the vital parameters, camera-based systems based upon digital images analysis are still not much applied to specific domains of clinical practice. Among others, given the possibility to record the respiratory waveforms (Section "Respiratory Frequency and Other Respiratory Parameters") and SpO 2 values (Section "Blood Pressure"), these systems could enable the investigation of some respiratory disorders (e.g., identification of obtrusive sleep apnea; van Gastel et al, 2021) without requiring cumbersome instrumentation. By levering the multi-point measurement that can be carried out with a single uncalibrated camera or calibrated one (Heikkila and Silven, 1997;Zhang and Member, 2000;Scaramuzza et al, 2006;Urban et al, 2015), digital videos could be used for assessing respiratory biomechanics and to evaluate eventual thoraco-abdominal asynchronies and abnormalities that are pretty common in clinical practice and of interest in athletes (Black and Millard, 2001).…”

Section: Discussionmentioning

confidence: 99%

Contactless Vital Signs Monitoring From Videos Recorded With Digital Cameras: An Overview

et al. 2022

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The measurement of physiological parameters is fundamental to assess the health status of an individual. The contactless monitoring of vital signs may provide benefits in various fields of application, from healthcare and clinical setting to occupational and sports scenarios. Recent research has been focused on the potentiality of camera-based systems working in the visible range (380–750 nm) for estimating vital signs by capturing subtle color changes or motions caused by physiological activities but invisible to human eyes. These quantities are typically extracted from videos framing some exposed body areas (e.g., face, torso, and hands) with adequate post-processing algorithms. In this review, we provided an overview of the physiological and technical aspects behind the estimation of vital signs like respiratory rate, heart rate, blood oxygen saturation, and blood pressure from digital images as well as the potential fields of application of these technologies. Per each vital sign, we provided the rationale for the measurement, a classification of the different techniques implemented for post-processing the original videos, and the main results obtained during various applications or in validation studies. The available evidence supports the premise of digital cameras as an unobtrusive and easy-to-use technology for physiological signs monitoring. Further research is needed to promote the advancements of the technology, allowing its application in a wide range of population and everyday life, fostering a biometrical holistic of the human body (BHOHB) approach.

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Section: Discussionmentioning

confidence: 99%

Contactless Vital Signs Monitoring From Videos Recorded With Digital Cameras: An Overview

et al. 2022

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“…In contrast, cuffs may be awkward and bulky, inducing arm soreness or rashes after multiple daily uses ( 78 ). Although a smartphone may not be used at night when the user is asleep, video cameras with infrared light can monitor vital signs using similar techniques as those developed for the smartphone ( 79 ).…”

Section: Discussion Perspectives and Future Outlookmentioning

confidence: 99%

Smartphones and Video Cameras: Future Methods for Blood Pressure Measurement

Steinman

Barszczyk

Sun

et al. 2021

Front. Digit. Health

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Regular blood pressure (BP) monitoring enables earlier detection of hypertension and reduces cardiovascular disease. Cuff-based BP measurements require equipment that is inconvenient for some individuals and deters regular home-based monitoring. Since smartphones contain sensors such as video cameras that detect arterial pulsations, they could also be used to assess cardiovascular health. Researchers have developed a variety of image processing and machine learning techniques for predicting BP via smartphone or video camera. This review highlights research behind smartphone and video camera methods for measuring BP. These methods may in future be used at home or in clinics, but must be tested over a larger range of BP and lighting conditions. The review concludes with a discussion of the advantages of the various techniques, their potential clinical applications, and future directions and challenges. Video cameras may potentially measure multiple cardiovascular metrics including and beyond BP, reducing the risk of cardiovascular disease.

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“…If RF is not visible in the thermal videos due to one of the discussed reasons, RM would anyway be visible in most of the recordings [ 33 ], implying that the information available for apnea identification would be similar to the current one, i.e., CI. It should be specified that bradycardia and desaturation need to be also detected in the case of a COB of 10 s to define it an apnea, therefore, for a future complete unobtrusive monitoring of apneas in the NICU these vitals (heartbeat and oxygen saturation) need to be included as well [ 9 ].…”

Section: Discussionmentioning

confidence: 99%

“…Numerous technologies are being researched for the unobtrusive monitoring of respiration: radars [ 6 , 7 ], RGB and Near-Infrared (NIR) cameras [ 8 , 9 ], thermal cameras or infrared thermography [ 10 , 11 , 12 ], pressure-sensitive mattresses [ 13 , 14 ], and vision systems with depth sensing [ 15 , 16 ]. All these techniques, apart from thermal cameras, can monitor only respiratory motion.…”

Section: Introductionmentioning

confidence: 99%

Automatic Separation of Respiratory Flow from Motion in Thermal Videos for Infant Apnea Detection

Lorato

Stuijk

Meftah

et al. 2021

Sensors

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Both Respiratory Flow (RF) and Respiratory Motion (RM) are visible in thermal recordings of infants. Monitoring these two signals usually requires landmark detection for the selection of a region of interest. Other approaches combine respiratory signals coming from both RF and RM, obtaining a Mixed Respiratory (MR) signal. The detection and classification of apneas, particularly common in preterm infants with low birth weight, would benefit from monitoring both RF and RM, or MR, signals. Therefore, we propose in this work an automatic RF pixel detector not based on facial/body landmarks. The method is based on the property of RF pixels in thermal videos, which are in areas with a smooth circular gradient. We defined 5 features combined with the use of a bank of Gabor filters that together allow selection of the RF pixels. The algorithm was tested on thermal recordings of 9 infants amounting to a total of 132 minutes acquired in a neonatal ward. On average the percentage of correctly identified RF pixels was 84%. Obstructive Apneas (OAs) were simulated as a proof of concept to prove the advantage in monitoring the RF signal compared to the MR signal. The sensitivity in the simulated OA detection improved for the RF signal reaching 73% against the 23% of the MR signal. Overall, the method yielded promising results, although the positioning and number of cameras used could be further optimized for optimal RF visibility.

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Camera-Based Vital Signs Monitoring During Sleep – A Proof of Concept Study

Cited by 28 publications

References 16 publications

Contactless Vital Signs Monitoring From Videos Recorded With Digital Cameras: An Overview

Contactless Vital Signs Monitoring From Videos Recorded With Digital Cameras: An Overview

Smartphones and Video Cameras: Future Methods for Blood Pressure Measurement

Automatic Separation of Respiratory Flow from Motion in Thermal Videos for Infant Apnea Detection

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