Evaluating the robustness of a contact-less mHealth solution for personal and remote monitoring of blood oxygen saturation

Casalino, Gabriella; Castellano, Giovanna; Zaza, Gianluca

doi:10.1007/s12652-021-03635-6

Cited by 22 publications

(7 citation statements)

References 37 publications

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“…In addition, the T&A method may overcome issues caused by movement. Casalino and colleagues [ 37 ] have described a method for measurement of oxygen saturation using rPPG in which 3 ROIs are used for measurement and a fourth to track head movements. We are exploring the impact of movement on rPPG, whether this differs between healthy volunteers and sick patients, and how T&A may address issues caused by movement during the video recording.…”

Section: Discussionmentioning

confidence: 99%

Dynamic Region of Interest Selection in Remote Photoplethysmography: Proof-of-Concept Study

Barham¹,

Wegerif²,

Petronzio³

2023

JMIR Form Res

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Background Remote photoplethysmography (rPPG) can record vital signs (VSs) by detecting subtle changes in the light reflected from the skin. Lifelight (Xim Ltd) is a novel software being developed as a medical device for the contactless measurement of VSs using rPPG via integral cameras on smart devices. Research to date has focused on extracting the pulsatile VS from the raw signal, which can be influenced by factors such as ambient light, skin thickness, facial movements, and skin tone. Objective This preliminary proof-of-concept study outlines a dynamic approach to rPPG signal processing wherein green channel signals from the most relevant areas of the face (the midface, comprising the cheeks, nose, and top of the lip) are optimized for each subject using tiling and aggregation (T&A) algorithms. Methods High-resolution 60-second videos were recorded during the VISION-MD study. The midface was divided into 62 tiles of 20×20 pixels, and the signals from multiple tiles were evaluated using bespoke algorithms through weighting according to signal-to-noise ratio in the frequency domain (SNR-F) score or segmentation. Midface signals before and after T&A were categorized by a trained observer blinded to the data processing as 0 (high quality, suitable for algorithm training), 1 (suitable for algorithm testing), or 2 (inadequate quality). On secondary analysis, observer categories were compared for signals predicted to improve categories following T&A based on the SNR-F score. Observer ratings and SNR-F scores were also compared before and after T&A for Fitzpatrick skin tones 5 and 6, wherein rPPG is hampered by light absorption by melanin. Results The analysis used 4310 videos recorded from 1315 participants. Category 2 and 1 signals had lower mean SNR-F scores than category 0 signals. T&A improved the mean SNR-F score using all algorithms. Depending on the algorithm, 18% (763/4212) to 31% (1306/4212) of signals improved by at least one category, with up to 10% (438/4212) improving into category 0, and 67% (2834/4212) to 79% (3337/4212) remaining in the same category. Importantly, 9% (396/4212) to 21% (875/4212) improved from category 2 (not usable) into category 1. All algorithms showed improvements. No more than 3% (137/4212) of signals were assigned to a lower-quality category following T&A. On secondary analysis, 62% of signals (32/52) were recategorized, as predicted from the SNR-F score. T&A improved SNR-F scores in darker skin tones; 41% of signals (151/369) improved from category 2 to 1 and 12% (44/369) from category 1 to 0. Conclusions The T&A approach to dynamic region of interest selection improved signal quality, including in dark skin tones. The method was verified by comparison with a trained observer’s rating. T&A could overcome factors that compromise whole-face rPPG. This method’s performance in estimating VS is currently being assessed. Trial Registration ClinicalTrials.gov NCT04763746; https://clinicaltrials.gov/ct2/show/NCT04763746

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Section: Discussionmentioning

confidence: 99%

Dynamic Region of Interest Selection in Remote Photoplethysmography: Proof-of-Concept Study

Barham¹,

Wegerif²,

Petronzio³

2023

JMIR Form Res

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“…The use of mobile devices for measurement of VSs presents some challenges compared with controlled laboratory scenarios, for example [ 32 ]. To mitigate some of these challenges, we have compared VSs that were measured simultaneously by using SOC methods and Lifelight.…”

Section: Discussionmentioning

confidence: 99%

Measurement of Vital Signs Using Lifelight Remote Photoplethysmography: Results of the VISION-D and VISION-V Observational Studies

Heiden¹,

Jones²,

Maczka³

et al. 2022

JMIR Form Res

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Background The detection of early changes in vital signs (VSs) enables timely intervention; however, the measurement of VSs requires hands-on technical expertise and is often time-consuming. The contactless measurement of VSs is beneficial to prevent infection, such as during the COVID-19 pandemic. Lifelight is a novel software being developed to measure VSs by remote photoplethysmography based on video captures of the face via the integral camera on mobile phones and tablets. We report two early studies in the development of Lifelight. Objective The objective of the Vital Sign Comparison Between Lifelight and Standard of Care: Development (VISION-D) study (NCT04763746) was to measure respiratory rate (RR), pulse rate (PR), and blood pressure (BP) simultaneously by using the current standard of care manual methods and the Lifelight software to iteratively refine the software algorithms. The objective of the Vital Sign Comparison Between Lifelight and Standard of Care: Validation (VISION-V) study (NCT03998098) was to validate the use of Lifelight software to accurately measure VSs. Methods BP, PR, and RR were measured simultaneously using Lifelight, a sphygmomanometer (BP and PR), and the manual counting of RR. Accuracy performance targets for each VS were defined from a systematic literature review of the performance of state-of-the-art VSs technologies. Results The VISION-D data set (17,233 measurements from 8585 participants) met the accuracy targets for RR (mean error 0.3, SD 3.6 vs target mean error 2.3, SD 5.0; n=7462), PR (mean error 0.3, SD 4.0 vs mean error 2.2, SD 9.2; n=10,214), and diastolic BP (mean error −0.4, SD 8.5 vs mean error 5.5, SD 8.9; n=8951); for systolic BP, the mean error target was met but not the SD (mean error 3.5, SD 16.8 vs mean error 6.7, SD 15.3; n=9233). Fitzpatrick skin type did not affect accuracy. The VISION-V data set (679 measurements from 127 participants) met all the standards: mean error −0.1, SD 3.4 for RR; mean error 1.4, SD 3.8 for PR; mean error 2.8, SD 14.5 for systolic BP; and mean error −0.3, SD 7.0 for diastolic BP. Conclusions At this early stage in development, Lifelight demonstrates sufficient accuracy in the measurement of VSs to support certification for a Level 1 Conformité Européenne mark. As the use of Lifelight does not require specific training or equipment, the software is potentially useful for the contactless measurement of VSs by nonclinical staff in residential and home care settings. Work is continuing to enhance data collection and processing to achieve the robustness and accuracy required for routine clinical use. International Registered Report Identifier (IRRID) RR2-10.2196/14326

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“…This was obtained by comparing red and blue wavelength bands. However these researches [37], [157], [128], only used a 0.5m range, which is short for a realistic scenario [37], [157], [128].…”

Section: B Remote Spo 2 Measurementmentioning

confidence: 99%

Remote Photoplethysmography (rPPG): A State-of-the-Art Review

Pirzada,

Wilde,

Doherty

et al. 2023

Preprint

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Peripheral oxygen saturation (SpO2) and heart rate (HR) are critical physiological measures that clinicians need to observe to decide on an emergency intervention. These measures are typically determined using a contact-based pulse oximeter. This approach may pose difficulties in many cases, such as with young children, patients with burnt or sensitive skin, cognitive impairments, and those undergoing certain medical procedures or severe illnesses. Remote Photoplethysmography (rPPG) allows for unobtrusive sensing of these vital signs in a variety of settings for health monitoring systems. Several research studies have been conducted to use rPPG for this purpose; however, there is still not a commercially available, clinically validated system that overcomes the concerns highlighted in this paper. We present a state-of-the-art review of rPPG-related research conducted including related processes and techniques, such as regions of interest (ROI) selection, extracting the raw signal, pre-processing data, applying noise reduction algorithms, Fast Fourier transforms (FFT), filtering and extracting these vital signs. Further, we present a detailed, critical evaluation of available rPPG systems. Limitations and future directions have also been identified to aid rPPG researchers in further advancing this field.

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Evaluating the robustness of a contact-less mHealth solution for personal and remote monitoring of blood oxygen saturation

Cited by 22 publications

References 37 publications

Dynamic Region of Interest Selection in Remote Photoplethysmography: Proof-of-Concept Study

Dynamic Region of Interest Selection in Remote Photoplethysmography: Proof-of-Concept Study

Measurement of Vital Signs Using Lifelight Remote Photoplethysmography: Results of the VISION-D and VISION-V Observational Studies

Remote Photoplethysmography (rPPG): A State-of-the-Art Review

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