A validation standard for Area of Habitat maps for terrestrial birds and mammals

Area of Habitat (AOH) is a deductive model which maps the distribution of suitable habitat at suitable altitudes for a species inside its broad geographical range. AOH maps have been validated using presence-only data for small subsets of species for different taxonomic groups, but no standard validation method exists when absence data are not available. We develop a novel two-step validation protocol for AOH which includes first a model-based evaluation of model prevalence (i.e, the proportion of suitable habitat within a species’ range), and second a validation using species point localities (presence-only) data. We applied the protocol to AOH maps of terrestrial birds and mammals. In the first step we built logistic regression models to predict expected model prevalence (the proportion of the range retained as AOH) as a function of each species’ elevation range, mid-point of elevation range, number of habitats, realm and, for birds, seasonality. AOH maps with large difference between observed and predicted model prevalence were identified as outliers and used to identify a number of sources of systematic error which were then corrected when possible. For the corrected AOH, only 1.7 % of AOH maps for birds and 2.3 % of AOH maps for mammals were flagged as outliers in terms of the difference between their observed and predicted model prevalence. In the second step we calculated point prevalence, the proportion of point localities of a species falling in pixels coded as suitable in the AOH map. We used 48,336,141 point localities for 4889 bird species and 107,061 point localities for 420 mammals. Where point prevalence exceeded model prevalence, the AOH was a better reflection of species’ distribution than random. We also found that 4689 out of 4889 (95.9 %) AOH maps for birds, and 399 out of 420 (95.0 %) AOH maps for mammals were better than random. Possible reasons for the poor performance of a small proportion of AOH maps are discussed.

A validation standard for Area of Habitat maps for terrestrial birds and mammals

Area of Habitat (AOH) is a deductive model which maps the distribution of suitable habitat at suitable altitudes for a species inside its broad geographical range. AOH maps have been validated using presence-only data for small subsets of species for different taxonomic groups, but no standard validation method exists when absence data are not available. We develop a novel two-step validation protocol for AOH which includes first a model-based evaluation of model prevalence (i.e, the proportion of suitable habitat within a species' range), and second a validation using species point localities (presence-only) data. We applied the protocol to AOH maps of terrestrial birds and mammals. In the first step we built logistic regression models to predict expected model prevalence (the proportion of the range retained as AOH) as a function of each species' elevation range, mid-point of elevation range, number of habitats, realm and, for birds, seasonality. AOH maps with large difference between observed and predicted model prevalence were identified as outliers and used to identify a number of sources of systematic error which were then corrected when possible. For the corrected AOH, only 1.7% of AOH maps for birds and 2.3% of AOH maps for mammals were flagged as outliers in terms of the difference between their observed and predicted model prevalence. In the second step we calculated point prevalence, the proportion of point localities of a species falling in pixels coded as suitable in the AOH map. We used 48,336,141 point localities for 4889 bird species and 107,061 point localities for 420 mammals. Where point prevalence exceeded model prevalence, the AOH was a better reflection of species' distribution than random. We also found that 4689 out of 4889 (95.9%) AOH maps for birds, and 399 out of 420 (95.0%) AOH maps for mammals were better than random. Possible reasons for the poor performance of a small proportion of AOH maps are discussed.

Assessing the Accuracy of Popular Commercial Technologies That Measure Resting Heart Rate and Heart Rate Variability

Commercial off-the shelf (COTS) wearable devices continue development at unprecedented rates. An unfortunate consequence of their rapid commercialization is the lack of independent, third-party accuracy verification for reported physiological metrics of interest, such as heart rate (HR) and heart rate variability (HRV). To address these shortcomings, the present study examined the accuracy of seven COTS devices in assessing resting-state HR and root mean square of successive differences (rMSSD). Five healthy young adults generated 148 total trials, each of which compared COTS devices against a validation standard, multi-lead electrocardiogram (mECG). All devices accurately reported mean HR, according to absolute percent error summary statistics, although the highest mean absolute percent error (MAPE) was observed for CameraHRV (17.26%). The next highest MAPE for HR was nearly 15% less (HRV4Training, 2.34%). When measuring rMSSD, MAPE was again the highest for CameraHRV [112.36%, concordance correlation coefficient (CCC): 0.04], while the lowest MAPEs observed were from HRV4Training (4.10%; CCC: 0.98) and OURA (6.84%; CCC: 0.91). Our findings support extant literature that exposes varying degrees of veracity among COTS devices. To thoroughly address questionable claims from manufacturers, elucidate the accuracy of data parameters, and maximize the real-world applicative value of emerging devices, future research must continually evaluate COTS devices.

P801Continuous cuff-less blood pressure monitoring using vascular elasticity model on photoplethysmogram

Background Hypertension is a well-known risk factor for potentially cardiovascular diseases, which is underdiagnosis and treatment. Clinical evidence suggests that periodic and continuous monitoring of blood pressure (BP) is helpful for the early detection of hypertension to reduce the cardiovascular risk. Photoplethysmogram (PPG) is a simple and non-invasive technique to measure the instantaneous blood flow in capillaries. This study proposes a miniaturized PPG sensor, which is feasible to integrate into smartphone, to estimate cuff-less BP and heart rate (HR). Methods A miniaturized PPG sensor, provided by FocalTech Smart Sensors Co., Ltd., was used to collect reflective finger PPG signal. The methodology of BP estimation from PPG was using a vascular elasticity model which estimating the physiological parameters from PPG features Simultaneously, we utilized oscillometric blood pressure monitors to obtain automated BP readings as the validation standard. Result Seventy-one subjects were recruited in this validation study. By using our PPG algorithm, an accuracy of ± 11.9 mmHg for systolic BP and ± 8.0 mmHg for diastolicBP was observed at 71 subjects. There was a good linear correlation (CC) between PPG-estimating BP and automated BP (systolic BP, CC=0.4; diastolic BP, CC=0/.45).Likewise, slopes of the liner fit on the Bland Altman plots for both systolic BP (slope = −0.23) and diastolic BP (slope = −0.11) indicated there was no particular bias in predicting high or low BP. Subjects characteristics Parameters Total number (subjects) 71 Entry BP range Normal 21 Prehypertension 27 Stage 1 hypertension 17 Stage 2 hypertension 6 Sex Male 37 Female 34 Age (years) Mean ± standard deviation 55±12 Range 27–77 Conclusion In this study, the feasibility of mobile based cuff-less BP measurement using a vascular elasticity model on finger PPG signal was demonstrated with a level of acceptable accuracy. Based on mobile-based and easy-to-use features of our sensor/device, the incorporation this real-time measurement into the monitoring of BP could be helpful for the management of hypertension.

Invasive Validation of Antares, a New Algorithm to Calculate Central Blood Pressure from Oscillometric Upper Arm Pulse Waves

Background: Antares is an algorithm for pulse wave analysis (PWA) by oscillometric blood pressure (BP) monitors in order to estimate central (aortic) blood pressure (cBP). Antares aims to enable brachial cuff-based BP monitors to be type II-devices, determining absolute cBP values independently of potential peripheral BP inaccuracies. The present study is an invasive validation of the Antares algorithm in the custo screen 400. Methods: We followed entirely the 2017 ARTERY protocol for validation of non-invasive cBP devices, the 2013 American National Standards Institute, Inc./Association for the Advancement of Medical Instrumentation/International Organization for Standardization (ANSI/AAMI/ISO) 81060-2 and 2018 AAMI/European Society of Hypertension (ESH)/ISO validation standard protocols. In total, 191 patients undergoing cardiac catheterization were included, of which 145 patients entered analysis. Invasive cBP recordings were compared to simultaneous non-invasive cBP estimations using the Antares algorithm, integrated into an oscillometric BP monitor. Results: Mean difference between invasive and non-invasively estimated systolic cBP was 0.71 mmHg with standard deviation of 5.95 mmHg, fulfilling highest validation criteria. Conclusion: Antares is the first algorithm for estimation of cBP that entirely fulfills the 2017 ARTERY and AAMI/ESH/ISO validation protocols. The Antares algorithm turns the custo screen 400 BP monitor into a type II-device. Integration of Antares into commercially available BP monitors could make it possible to measure PWA parameters in virtually every practice in future.

Probabilistic Vision-Based Full-Field Displacement and Strain Measurement via Uncertainty Propagation

This paper presents formulations that enable the vision-based measurement of displacement and strain fields extensively in a probabilistic manner. The proposed formulations are built on the dot centroid tracking (DCT) method by digital cameras, which measures the darkness of each pixel in gray scale, identify dots marked on a specimen, derives dot centroids using pixel darkness information and derives displacement and strain fields by tracking the centroids and interpolating the nodal displacements and strains. Under the Gaussian assumption, the proposed formulations analytically propagate the standard deviation of uncertainty in darkness measurement and estimate that in the displacement and strain field measurement. As the first step, the formulations were completed for continuous field measurement with triangular elements. Most advantageously, the proposed formulations allow discussion on measurement error bounds, which also enables the quantitative comparison of the DCT method to the other measurement techniques. For numerical validation, standard deviations of nodal displacements and strains estimated from the known darkness uncertainty were compared to those derived from large samples created with the same darkness uncertainty. The results show the validity of the proposed formulations and their potential in measurement with reliability.