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oBPM - Optical Blood Pressure Monitoring

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Martin Proença
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Martin Proença
added 3 research items
While hypertension globally affects two out of five adults worldwide, there exists no easily-scalable technology to measure blood pressure out of the clinics. The idea of using smartphone sensors to estimate blood pressure was already tackled in the past, but failed because of low accuracy. Based on data from a previous study (NCT02651558), we recently developed a library of algorithms that predicts blood pressure from optical signals: the Optical Blood Pressure Monitoring (OBPM) technology. In the current work, we studied the performances of this technology when applied to video sequences acquired by a commercial smartphone camera. We implemented a measurement campaign on 35 healthy volunteers that performed physical exercises. The volunteers were requested to apply their right forefinger on top of the camera of a commercial smartphone while video sequences were acquired. The video sequences were then processed by the OBPM algorithms, and the predicted blood pressure values were compared to reference oscillometric blood pressure readings. After a calibration procedure, the predicted diastolic blood pressure values showed to comply with the ISO81060-2 performance requirements with a mean error of 0.32 mmHg, and a standard deviation of the error of 7.02 mmHg. This study provides first experimental evidence to support that a commercial smartphone can be transformed into a blood pressure monitor by means of the OBPM technology.
Routine monitoring of blood pressure during general anesthesia relies on intermittent measurements with a non-invasive brachial cuff inflated every two to five minutes. While all these patients are equipped by a fingertip pulse oximeter, the acquired optical signals currently only provide SpO2 estimates. Our running clinical trial (NCT02651558) presents the first-ever demonstration that the optical signals acquired by a fingertip pulse oximeter can also be exploited to continuously detect blood pressure changes. Results from the first 8 enrolled patients show that the Optical Blood Pressure Monitoring (oBPM) algorithms can detect rapid blood pressure changes occurring during anesthesia with 94% of accuracy. The proposed solution is expected to allow major improvements in the safety of anesthetized patient's, allowing early detection of hemodynamic changes occurring in between two routine blood pressure measurements performed with brachial cuffs.
Background: Intraoperative hypotension is associated with postoperative complications and death. Oscillometric brachial cuffs are used to measure arterial pressure (AP) in most surgical patients but may miss acute changes in AP. We hypothesized that pulse oximeter waveform analysis may help to detect changes in systolic AP (SAP) and mean AP (MAP) during anesthesia induction. Methods: In 40 patients scheduled for an elective surgery necessitating general anesthesia and invasive AP monitoring, we assessed the performance of a pulse oximeter waveform analysis algorithm (optical blood pressure monitoring [oBPM]) to estimate SAP, MAP, and their changes during the induction of general anesthesia. Acute AP changes (>20%) in SAP and MAP assessed by the reference invasive method and by oBPM were compared using 4-quadrant and polar plots. The tracking ability of the algorithm was evaluated on changes occurring over increasingly larger time spans, from 30 seconds up to 5 minutes. The second objective of the study was to assess the ability of the oBPM algorithm to cope with the Association for the Advancement of Medical Instrumentation (AAMI) standards. The accuracy and precision of oBPM in estimating absolute SAP and MAP values compared to the invasive method was evaluated at various instants after algorithm calibration, from 30 seconds to 5 minutes. Results: Rapid changes (occurring over time spans of ≤60 seconds) in SAP and MAP assessed by oBPM were strongly correlated and showed excellent concordance with changes in invasive AP (worst-case Pearson correlation of 0.94 [0.88, 0.97] [95% confidence interval], concordance rate of 100% [100%, 100%], and angular concordance rate at ±30° of 100% [100%, 100%]). The trending ability tended to decrease progressively as the time span over which the changes occurred increased, reaching 0.89 (0.85, 0.91) (Pearson correlation), 97% (95%, 100%) (concordance rate), and 90% (85%, 94%) (angular concordance rate) in the worst case. Regarding accuracy and precision, oBPM-derived SAP values were shown to comply with AAMI criteria up to 2 minutes after calibration, whereas oBPM-derived MAP values were shown to comply with criteria at all times. Conclusions: Pulse oximeter waveform analysis was useful to track rapid changes in SAP and MAP during anesthesia induction. A good agreement with reference invasive measurements was observed for MAP up to at least 5 minutes after initial calibration. In the future, this method could be used to track changes in AP between intermittent oscillometric measurements and to automatically trigger brachial cuff inflation when a significant change in AP is detected.
Martin Proença
added 2 research items
The current non-invasive gold standard for the measurement of blood pressure (BP) is the oscillometric cuff at the upper arm, despite its known limitations. In particular, its poor adequacy with continuous monitoring and its measurement incommodity call for the development of simpler and more convenient solutions. Among these, solutions based on pulse wave analysis (PWA) and photoplethysmography (PPG) are of particular interest, due to their low-cost, strong patient compliance, and applicability in and out of clinical settings. In that context, we have recently disclosed a PPG-based PWA algorithm (oBPM TM) dedicated to the continuous monitoring of BP in patients undergoing induction of general anesthesia. As is standard with PPG-based BP monitoring techniques, an initial calibration procedure with a reference device is required to allow the estimation of absolute values of BP (in mmHg). However, due to their sensitivity to peripheral effects such as vasomotion, the applicability of PPG-based techniques is often limited by the constant need of re-calibration procedures, sometimes in matters of minutes. In the present study, we evaluated the long-term stability of the calibration for our algorithm by performing PPG measurements at irregular time intervals over a period of 3 months in 13 healthy volunteers. For each measurement, diastolic BP (DBP) was assessed by an oscillometric device and estimated by the oBPM TM algorithm. We found the calibration to remain stable over the entire 3-month period, with estimation errors remaining stable over time and complying with the ISO 81060-2:2018 standard. In addition, we verified-in 11 of our 13 subjects-the sensitivity of the oBPM TM algorithm to changes in DBP. This was done in a protocol involving static leg extension exercises. Excellent trending ability (average per-subject concordance rate of 97.7  5.2 %, and correlation coefficient of 0.98  0.02, p < 0.001) was found between cuff-derived DBP changes and our estimates. These findings provide a strong added value to the practical usability of the proposed PPG-based PWA approach to BP monitoring, particularly for the clinical management of hypertensive patients in and out of clinics, for whom a simple and comfortable continuous alternative to the oscillometric cuff would be strongly preferred.
Pulse wave analysis, or PWA, is a technique based on the morphological analysis of blood pressure waveforms, whose shape reflects crucial information on the properties of the arterial wall and blood pressure itself. Although the first historical developments of PWA date back to the nineteenth century, the technique started to prosper with the development of applanation tonometry in the 1960s. More recently, the approach has been increasingly applied to photoplethysmographic signals, due to the appeal in deriving blood pressure-related information from signals routinely measured in clinical settings. In this chapter, after an introduction on the historical and physiological background of PWA, a review of the waveform features most commonly encountered in the literature is given, followed by an overview of PWA-based clinical studies and an outlook on the clinical potential of the technique.
Martin Proença
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Damien Ferrario
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The terminology of cuffless Blood Pressure (BP) measuring techniques currently lacks an appropriate consensus, leading to repeated misunderstandings among researchers, clinicians and investors. Numerous techniques designed to measure BP in a continuous and cuffless manner have been disclosed in the past. However, most developments focus either on the sensors or the algorithms, but do not provide a full solution to the cuffless BP monitoring problem. This paper suggests a unified framework to systematically classify and describe BP monitoring techniques. Called the three-layer framework, it assumes that in order to perform a cuffless BP measurement the following layers are required: Layer #1-Sensing: the first step towards the estimation of a BP value consists in collecting a set of physiologically-relevant signals from the patient's body. Typical explored sensing technologies are electrocardiography, phonocardiography, impedance plethysmography, photoplethysmography, radio-frequency sensing, and tonometry. Layer #2 – Processing: the second step consists in extracting physiological information from the measured set of raw signals. Different families of algorithms have been suggested, ranging from physiology-based models (e.g., pulse wave velocity algorithms, and pulse wave analysis algorithms) to numerical cardiovascular models. In all cases, this algorithmic layer will translate the time series (of raw data expressed in mV from an analog-to-digital converter) into a feature, or set of features, that relates to the underlying BP. Layer #3-Calibration: the final step concerns the translation of the calculated feature(s) (expressed in arbitrary units) into a BP value (in mmHg). Numerous calibration strategies have been implemented in the past, including population-wise calibrations, and patient-dependent calibrations (based either on one-shot or intermittent measurements with a reference, on hydrostatic pressure changes, or on numerical models).
Damien Ferrario
added 2 project references
Damien Ferrario
added a research item
Cuffless blood pressure monitoring at the chest requires accurate detection of the arrival time of arterial pressure pulses at chest skin. A clinical trial was designed (NCT02651558) in order to assess the performance of single-and multi-channel reflective PPG sensors when no pressure is applied onto optical probe. Experimental setup involved invasive monitoring of reference hemodynamic variables. Results suggest that multi-channel PPG sensors are required in order to obtain accurate hemodynamic measurements at the chest, questioning the reliability of single-channel PPG sensors.