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Continual vital sign assessment on the general care, medical-surgical floor is expected to provide early indication of patient deterioration and increase the effectiveness of rapid response teams. However, there is concern that continual, multi-parameter vital sign monitoring will produce alarm fatigue. The objective of this study was the development of a methodology to help care teams optimize alarm settings. An on-body wireless monitoring system was used to continually assess heart rate, respiratory rate, SpO2 and noninvasive blood pressure in the general ward of ten hospitals between April 1, 2014 and January 19, 2015. These data, 94,575 h for 3430 patients are contained in a large database, accessible with cloud computing tools. Simulation scenarios assessed the total alarm rate as a function of threshold and annunciation delay (s). The total alarm rate of ten alarms/patient/day predicted from the cloud-hosted database was the same as the total alarm rate for a 10 day evaluation (1550 h for 36 patients) in an independent hospital. Plots of vital sign distributions in the cloud-hosted database were similar to other large databases published by different authors. The cloud-hosted database can be used to run simulations for various alarm thresholds and annunciation delays to predict the total alarm burden experienced by nursing staff. This methodology might, in the future, be used to help reduce alarm fatigue without sacrificing the ability to continually monitor all vital signs.Electronic supplementary materialThe online version of this article (doi:10.1007/s10877-015-9790-8) contains supplementary material, which is available to authorized users.

The goal of this study is to measure left ventricular stroke volume (SV) from the brachial artery (BA) using electrical bioimpedance. Doppler-derived SV was used for comparison. Twenty-nine healthy adults were recruited for study. Doppler echocardiographic-derived SV was obtained from the product of distal left ventricular outflow tract cross-sectional area and systolic velocity integral. SV from the BA was obtained by transbrachial electrical bioimpedance velocimetry (TBEV). Application of a current field across the left brachium was effected by injection of a constant magnitude, high frequency, low amperage, alternating current. Therein, a static voltage (U(0)) and pulsatile voltage change (ΔU(t)) were measured and converted to their corresponding impedances, Z(0) and ΔZ(t). TBEV-derived SV was obtained by multiplying a square root value of the normalized, acceleration-based, peak first time derivative of ΔZ(t) by a volume conductor and systolic flow time. Inter-method agreement was determined by the Bland-Altman method. To assess the contribution of blood resistivity variations to ΔZ(t), BA diameters were measured at end-diastole and peak systolic expansion. Results indicate that since the BA demonstrates parabolic, laminar flow, with minimal diameter changes, blood resistivity variations are likely responsible for the derived impedance changes. Bland-Altman analysis shows that SV is obtainable by TBEV from healthy humans at rest.

Abstract:The Research Resource for Complex Physiologic Signals, supported by the National Institutes of Health (NIH), is intended to promote and facilitate investigations in the study of cardiovascular and other complex biomedical signals. The resource website (www.physionet.org) has 3 interdependent components: 1) PhysioBank is an archive of well-characterized digital recordings of physiologic signals and related data, including databases of electrocardiogram and heart rate time series from patients with heart failure, coronary disease, sleep apnea syndromes, and cardiac arrhythmias; 2) PhysioToolkit is a library of open-source software for physiologic signal processing and analysis; and 3) PhysioNet, for which the resource is named, is an on-line forum for dissemination and exchange of recorded biomedical signals and open-source software for analyzing them. PhysioNet, in cooperation with the annual Computers in Cardiology conference, hosts a series of challenges inviting participants to tackle clinically interesting problems that are either unsolved or not well solved. PhysioNet invites contributions of databases and software from the biomedical community.

Stroke volume (SV) is the quantity of blood ejected by the cardiac ventricles per each contraction. When SV is multiplied by heart rate, cardiac output is the result. Cardiac output (CO), in conjunction with hemoglobin concentration and arterial oxygen saturation are the cornerstones of oxygen transport. Measurement of CO is important, especially in sick humans suffering from decompensated heart disease and systemic diseases affecting the contractility or loading conditions of the heart. Although reasonably accurate invasive cardiac output methods are available, their use is restricted to those individuals hospitalized in the intensive care units. Thus, a robust noninvasive alternative is considered desirable. Impedance cardiography (ICG) is one such method, but in patients with severe heart disease and/or excess extravascular lung water, the method is inaccurate. This paper concerns the introduction of a new method, transbrachial electrical bioimpedance velocimetry (TBEV). The technique involves passage of a constant magnitude, high frequency, and low amperage ac from the upper arm to the antecubital fossa. In all other respects, the operational aspects of TBEV are consistent with ICG. There is good evidence suggesting that the TBEV waveform and its derivatives are generated by blood resistivity changes only.

The ability to monitor arterial blood pressure continuously with unobtrusive body worn sensors may provide a unique and potentially valuable assessment of a patient's cardiovascular health. Pulse wave velocity (PWV) offers an attractive method to continuously monitoring blood pressure. However, PWV technologies based on timing measurements between the ECG and a distal PPG suffer from inaccuracies on mobile patients due to the confounding influence of pre-ejection period (PEP). In this paper, we presented a wearable, continuous blood pressure monitor (ViSi Mobile) that can measure and track changes in PEP. PEP is determined from precordial vibrations captured by an accelerometer coupled to the patient's sternum. The performance of the PEP measurements was evaluated on test subjects with postural change and patient activity. Results showed potential to improve cNIBP accuracy in active patients.

The Lomb periodogram and discrete Fourier transform are described and applied to harmonic analysis of two typical data sets, one air quality time series and one water quality time series. The air quality data is a 13 year series of 24 hour average particulate elemental carbon data from the IMPROVE station in Washington, D.C. The water quality data are from the stormwater monitoring network in Milwaukee, WI and cover almost 2 years of precipitation events. These data have irregular sampling periods and missing data that preclude the straightforward application of the fast Fourier transform (FFT). In both cases, an anthropogenic periodicity is identified; a 7-day weekday/ weekend effect in the Washington elemental carbon series and a 1 month cycle in several constituents of stormwater. Practical aspects of application of the Lomb periodogram are discussed, particularly quantifying the effects of random noise. The proper application of the FFT to data that are irregularly spaced with missing values is demonstrated on the air quality data. Recommendations are given when to use the Lomb periodogram and when to use the FFT.

The goal of this study is to validate a new, continuous, noninvasive stroke volume (SV) method, known as transbrachial electrical bioimpedance velocimetry (TBEV). TBEV SV was compared to SV obtained by cardiac magnetic resonance imaging (cMRI) in normal humans devoid of clinically apparent heart disease. Thirty-two (32) volunteers were enrolled in the study. Each subject was evaluated by echocardiography to assure that no aortic or mitral valve disease was present. Subsequently, each subject underwent electrical interrogation of the brachial artery by means of a high frequency, low amplitude alternating current. A first TBEV SV estimate was obtained. Immediately after the initial TBEV study, subjects underwent cMRI, using steady-state precession imaging to obtain a volumetric estimate of SV. Following cMRI, the TBEV SV study was repeated. Comparing the cMRI-derived SV to that of TBEV, the two TBEV estimates were averaged and compared to the cMRI standard. CO was computed as the product of SV and heart rate. Statistical methods consisted of Bland–Altman and linear regression analysis. TBEV SV and CO estimates were obtained in 30 of the 32 subjects enrolled. Bland–Altman analysis of pre- and post-cMRI TBEV SV showed a mean bias of 2.87 % (2.05 mL), precision of 13.59 % (11.99 mL) and 95 % limits of agreement (LOA) of +29.51 % (25.55 mL) and −23.77 % (−21.45 mL). Regression analysis for pre- and post-cMRI TBEV SV values yielded y = 0.76x + 25.1 and r2 = 0.71 (r = 0.84). Bland–Altman analysis comparing cMRI SV with averaged TBEV SV showed a mean bias of −1.56 % (−1.53 mL), precision of 13.47 % (12.84 mL), 95 % LOA of +24.85 % (+23.64 mL) and −27.97 % (−26.7 mL) and percent error = 26.2 %. For correlation analysis, the regression equation was y = 0.82x + 19.1 and correlation coefficient r2 = 0.61 (r = 0.78). Bland–Altman analysis of averaged pre- and post-cMRI TBEV CO versus cMRI CO yielded a mean bias of 5.01 % (0.32 L min−1), precision of 12.85 % (0.77 L min−1), 95 % LOA of +30.20 % (+0.1.83 L min−1) and −20.7 % (−1.19 L min−1) and percent error = 24.8 %. Regression analysis yielded y = 0.92x + 0.78, correlation coefficient r2 = 0.74 (r = 0.86). TBEV is a novel, noninvasive method, which provides satisfactory estimates of SV and CO in normal humans.