Accuracy of blood pressure measurement across BMI categories using the OptiBP™ mobile application.

PURPOSE: Obesity is a clear risk factor for hypertension. Blood pressure (BP) measurement in obese patients may be biased by cuff size and upper arm shape which may affect the accuracy of measurements. This study aimed to assess the accuracy of the OptiBP smartphone application for three different body mass index (BMI) categories (normal, overweight and obese). MATERIALS AND METHODS: Participants with a wide range of BP and BMI were recruited at Lausanne University Hospital's hypertension clinic in Switzerland. OptiBP estimated BP by recording an optical signal reflecting light from the participants' fingertips into a smartphone camera. Age, sex and BP distribution were collected to fulfil the AAMI/ESH/ISO universal standards. Both auscultatory BP references and OptiBP BP were measured and compared using the simultaneous opposite arms method, as described in the 81060-2:2018 ISO norm. Subgroup analyses were performed for each BMI category. RESULTS: We analyzed 414 recordings from 95 patients: 34 were overweight and 15 were obese. The OptiBP application had a performance acceptance rate of 82%. The mean and standard deviation (SD) differences between the optical BP estimations and the auscultatory reference rates (criterion 1) were respected in all subgroups: SBP mean value was 2.08 (SD 7.58); 1.32 (6.44); -2.29 (5.62) respectively in obese, overweight and normal weight subgroup. For criterion 2, which investigates the precision errors on an individual level, the threshold for systolic BP in the obese group was slightly above the requirement for this criterion. CONCLUSION: This study demonstrated that the OptiBP application is easily applicable to overweight and obese participants. Differences between the reference measure and the OptiBP estimation were within ISO limits (criterion 1). In obese participants, the SD of mean error was outside criterion 2 limits. Whether auscultatory measurement, due to arm morphology or the OptiBP is associated with increasing bias in obese still needs to be studied.

What is the context? • Hypertension and obesity have a major impact on population health and costs. • Obesity is a chronic disease characterized by abnormal or excessive fat accumulation. • Obesity, in combination with other diseases like hypertension, is a major risk factor for cardiovascular and total death. • In Europe, the obesity rate is 21.5% for men and 24.5% for women. • Hypertension, which continues to increase in the population, is a factor that can be modified when well managed. • Blood pressure measurement by the usual method may be complicated in obese patients due to fat accumulation and the shape of the arm and can lead to measurement errors. In addition, the non-invasive blood pressure measurement can be constraining and uncomfortable.What is new? • Smartphone apps are gradually appearing and allow the measurement of blood pressure without a pressure cuff using photoplethysmography. • OptiBP is a smartphone application that provides an estimate of blood pressure that has been evaluated in the general population. • The objective of this study is to assess whether OptiBP is equally effective in obese and overweight patients.What is the impact? • The use of smartphones to estimate BP in overweight and obese patients may be a solution to the known bias associated with cuff measurement. • The acquisition of more and more data with a larger number of patients will allow the continuous improvement of the application's algorithm.

Smartphone based blood pressure measurement: accuracy of the OptiBP mobile application according to the AAMI/ESH/ISO universal validation protocol.

OBJECTIVE: The aim of this study was to assess the accuracy of the OptiBP mobile application based on an optical signal recorded by placing the patient's fingertip on a smartphone's camera to estimate blood pressure (BP). Measurements were carried out in a general population according to existing standards of the Association for the Advancement of Medical Instrumentation (AAMI), the European Society of Hypertension (ESH) and the International Organization for Standardization (ISO). METHODS: Participants were recruited during a scheduled appointment at the hypertension clinic of Lausanne University Hospital in Switzerland. Age, gender and BP distribution were collected to fulfill AAMI/ESH/ISO universal standards. Both auscultatory BP references and OptiBP were measured and compared using the opposite arm simultaneous method as described in the 81060-2:2018 ISO norm. RESULTS: A total of 353 paired recordings from 91 subjects were analyzed. For validation criterion 1, the mean ± SD between OptiBP and reference BP recordings was respectively 0.5 ± 7.7 mmHg and 0.4 ± 4.6 mmHg for SBP and DBP. For validation criterion 2, the SD of the averaged BP differences between OptiBP and reference BP per subject was 6.3 mmHg and 3.5 mmHg for SBP and DBP. OptiBP acceptance rate was 85%. CONCLUSION: The smartphone embedded OptiBP cuffless mobile application fulfills the validation requirements of AAMI/ESH/ISO universal standards in a general population for the measurement of SBP and DBP.

Blood pressure measurements with the OptiBP smartphone app validated against reference auscultatory measurements.

Mobile health diagnostics have been shown to be effective and scalable for chronic disease detection and management. By maximizing the smartphones' optics and computational power, they could allow assessment of physiological information from the morphology of pulse waves and thus estimate cuffless blood pressure (BP). We trained the parameters of an existing pulse wave analysis algorithm (oBPM), previously validated in anaesthesia on pulse oximeter signals, by collecting optical signals from 51 patients fingertips via a smartphone while simultaneously acquiring BP measurements through an arterial catheter. We then compared smartphone-based measurements obtained on 50 participants in an ambulatory setting via the OptiBP app against simultaneously acquired auscultatory systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean blood pressure (MBP) measurements. Patients were normotensive (70.0% for SBP versus 61.4% for DBP), hypertensive (17.1% vs. 13.6%) or hypotensive (12.9% vs. 25.0%). The difference in BP (mean ± standard deviation) between both methods were within the ISO 81,060-2:2018 standard for SBP (- 0.7 ± 7.7 mmHg), DBP (- 0.4 ± 4.5 mmHg) and MBP (- 0.6 ± 5.2 mmHg). These results demonstrate that BP can be measured with accuracy at the finger using the OptiBP smartphone app. This may become an important tool to detect hypertension in various settings, for example in low-income countries, where the availability of smartphones is high but access to health care is low.

On Computing Structural and Behavioral Complexities of Threshold Boolean Networks : Application to Biological Networks.

Various threshold Boolean networks (TBNs), a formalism used to model different types of biological networks (genes notably), can produce similar dynamics, i.e. share same behaviors. Among them, some are complex (according to Kolmogorov complexity), others not. By computing both structural and behavioral complexities, we show that most TBNs are structurally complex, even those having simple behaviors. For this purpose, we developed a new method to compute the structural complexity of a TBN based on estimates of the sizes of equivalence classes of the threshold Boolean functions composing the TBN.