Development and Validation of remote Photoplethysmography (rPPG) Technology for Blood Pressure and Hemoglobin Level Assessment in the Preoperative Assessment Setting (Preprint)
Authors: Tan Selene YL , Chai Jia Xin , Choi Minwoo , Javaid Umair , Tan Brenda Pei Yi , Chow Belinda Si Ying , Abdullah Hairil Rizal 
Published: June 2024

BACKGROUND

Various studies have been written about noninvasive, remote photoplethysmography-based measurement of blood pressure (BP) and, to a lesser extent, hemoglobin (Hb) concentration. Widespread applicability has yet to be achieved due to limitations with agreement and correlation. There is also limited data on rPPG BP and Hb measurement evaluation in representative populations at the preoperative evaluation clinic (PEC) setting, such as hypertensive patients and patients with diverse, varying skin tones.

OBJECTIVE

We assessed the accuracy of rPPG technology in noninvasive systolic BP (SBP) and diastolic BP (DBP) measurements compared to automated cuffed blood pressure measuring devices (BPMD). Additionally, we compared the accuracy of rPPG Hb concentration measurement to that of clinical laboratory testing.

METHODS

Nervotec rPPG telehealth and smartphone software utilizes the principle that reflected light from various skin areas is affected by the volume of blood under the skin, which varies according to arterial pulsations and blood flow. This principle allows for an optical measurement technique that measures these variations. The measurements are then analyzed with signal processing algorithms which generate physiological measurements such as BP and Hb. The study was conducted at Singapore General Hospital (SGH) from 15 February 2023 to 6 December 2024. The participants were recruited in two phases. The first group, used for training and evaluating the algorithm, consisted of 100 patients with a mean age of 52.9 ± 13.1 years. In this group, 59% of patients had concomitant medical diseases such as hypertension (HTN) and diabetes mellitus (DM). The second group, used for validation of the algorithm, consisted of 65 patients with a mean age of 55.15 ± 17.27 years. 43% of the patients had concomitant medical conditions such as HTN, DM and ischemic heart disease (IHD). Both groups had an even distribution of males and females, as well as a diverse range of skin tones (1-10) classified according to the Monk Skin Tone (MST) scale. The primary analysis was focused on assessing the accuracy of rPPG BP measurements compared to BPMD BP measurements. The secondary analysis aimed to evaluate the accuracy of rPPG Hb concentration measurement compared to clinical laboratory testing.

RESULTS

Our study demonstrated an accuracy of 83.84% for SBP and 90.55% for DBP, with mean absolute percentage errors (MAPE) of 16.16% for SBP and 9.45% for DBP. Furthermore, the model could predict Hb concentration with an accuracy of 88.41%. MAPE was 11.59%, with an error bias of 0.54 g/dL and an error SD of 1.82 g/dL.

CONCLUSIONS

Our study is the first to evaluate contactless rPPG BP and Hb concentration measurements in a diverse, heterogeneous study population. The model achieved a DBP accuracy rate of 90.55% with a MAPE of 9.45%. We recorded a MAPE of 16.16% for SBP, and a MAPE of 11.59% for Hb concentration. Quartile evaluation indicated stronger correlations in mid-quartile ranges for DBP (70-74 mmHg) and Hb (13.2 - 14.4 g/dL), confirming the model’s reliability in detecting moderate deviations from normal physiological states. Our current model performance carries potential as a triaging tool within both hospital and population health settings.

CLINICALTRIAL

The study was approved by the SingHealth Centralised Institutional Review Board (CIRB Ref: 2023/2042) from 15 February 2023 to 6 December 2024 and is registered on ClinicalTrials.gov (Trial number: NCT06320847).