Worcester Polytechnic Institute

About: Worcester Polytechnic Institute is a education organization based out in Worcester, Massachusetts, United States. It is known for research contribution in the topics: Computer science & Population. The organization has 6270 authors who have published 12704 publications receiving 332081 citations. The organization is also known as: WPI.

PULSE-SMART: Pulse-Based Arrhythmia Discrimination Using a Novel Smartphone Application

Abstract: Automated Arrhythmia Discrimination Using a SmartphoneBackground Atrial fibrillation (AF) is a common and dangerous rhythm abnormality. Smartphones are increasingly used for mobile health applications by older patients at risk for AF and may be useful for AF screening. Objectives To test whether an enhanced smartphone app for AF detection can discriminate between sinus rhythm (SR), AF, premature atrial contractions (PACs), and premature ventricular contractions (PVCs). Methods We analyzed two hundred and nineteen 2-minute pulse recordings from 121 participants with AF (n = 98), PACs (n = 15), or PVCs (n = 15) using an iPhone 4S. We obtained pulsatile time series recordings in 91 participants after successful cardioversion to sinus rhythm from preexisting AF. The PULSE-SMART app conducted pulse analysis using 3 methods (Root Mean Square of Successive RR Differences; Shannon Entropy; Poincare plot). We examined the sensitivity, specificity, and predictive accuracy of the app for AF, PAC, and PVC discrimination from sinus rhythm using the 12-lead EKG or 3-lead telemetry as the gold standard. We also administered a brief usability questionnaire to a subgroup (n = 65) of app users. Results The smartphone-based app demonstrated excellent sensitivity (0.970), specificity (0.935), and accuracy (0.951) for real-time identification of an irregular pulse during AF. The app also showed good accuracy for PAC (0.955) and PVC discrimination (0.960). The vast majority of surveyed app users (83%) reported that it was “useful” and “not complex” to use. Conclusion A smartphone app can accurately discriminate pulse recordings during AF from sinus rhythm, PACs, and PVCs.

A portmanteau test for self-exciting threshold autoregressive-type nonlinearity in time series

Abstract: SUMMARY A portmanteau test to detect self-exciting threshold autoregressive-type nonlinearity in time series data is proposed. The test is based on cumulative sums of standardized residuals from autoregressive fits to the data. Significance levels for the test under the hypothesis of linearity are obtain from the asymptotic distribution of the cumulative sums as Brownian motion. The performance of the test is evaluated for simulated data from linear, bilinear and self-exciting threshold autoregressive models. It is also compared with another test which has been suggested for detecting general nonlinearity. Features of the proposed test, which make it useful in identifying the autoregressive order and the lag in threshold models, are discussed.

Pixel-by-Pixel Spatiotemporal Progression of Focal Ischemia Derived Using Quantitative Perfusion and Diffusion Imaging

Abstract: Pixel-by-pixel spatiotemporal progression of focal ischemia (permanent occlusion) in rats was investigated using quantitative perfusion and diffusion magnetic resonance imaging every 30 minutes for 3 hours. The normal left-hemisphere apparent diffusion coefficient (ADC) was 0.76 +/- 0.03 x 10(-3) mm(2)/s and CBF was 0.7 +/- 0.3 mL x g(-1) x min(-1) (mean +/- SD, n=5). The ADC and CBF viability thresholds yielding the lesion volumes (LV) at 3 hours that best approximated the 2,3,5-triphenyltetrazolium chloride (TTC) infarct volumes (200 +/- 30 mm(3)) at 24 hours were 0.53 +/- 0.02 x 10(-3) mm(2)/s (30% +/- 2% reduction) and 0.30 +/- 0.09 mL x g(-1) x min(-1) (57% +/- 11% reduction), respectively. Temporal evolution of the ADC- and CBF-defined LV showed a significant "perfusion-diffusion mismatch" up to 2 hours (P < 0.05, n = 11), a potential therapeutic window. Based on the viability thresholds, three pixel clusters were identified on the CBF-ADC scatterplots: (1) a "normal" cluster with normal CBF and ADC, (2) an "ischemic core" cluster with markedly reduced CBF and ADC, and (3) a "mismatch" cluster with reduced CBF but slightly reduced ADC. These clusters were color-coded and mapped onto the image and CBF-ADC spaces. Lesions grew peripheral and medial to the initial ADC abnormality. In contrast to the CBF distribution, the ADC distribution in the ischemic hemisphere was bimodal; the relatively time-invariant bimodal-ADC minima were 0.57 +/- 0.02 x 10(-3) mm(2)/s (corresponding CBF 0.35 +/- 0.04 mL x g(-1) x min(-1)), surprisingly similar to the TTC-derived thresholds. Together, these results illustrate an analysis approach to systemically track the pixel-by-pixel spatiotemporal progression of acute ischemic brain injury.