99 research outputs found

    Contact Surface Area: A Novel Signal for Heart Rate Estimation in Smartphone Videos

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    We consider the problem of smartphone video-based heart rate estimation, which typically relies on measuring the green color intensity of the user's skin. We describe a novel signal in fingertip videos used for smartphone-based heart rate estimation: fingertip contact surface area. We propose a model relating contact surface area to pressure, and validate it on a dataset of 786 videos from 62 participants by demonstrating a statistical correlation between contact surface area and green color intensity. We estimate heart rate on our dataset with two algorithms, a baseline using the green signal only and a novel algorithm based on both color and area. We demonstrate lower rates of substantial errors (>10 beats per minute) using the novel algorithm (4.1%), compared both to the baseline algorithm (6.4%) and to published results using commercial color-based applications (>6%)

    A Classification-based Approach for Approximate Reachability

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    Hamilton-Jacobi (HJ) reachability analysis has been developed over the past decades into a widely-applicable tool for determining goal satisfaction and safety verification in nonlinear systems. While HJ reachability can be formulated very generally, computational complexity can be a serious impediment for many systems of practical interest. Much prior work has been devoted to computing approximate solutions to large reachability problems, yet many of these methods may only apply to very restrictive problem classes, do not generate controllers, and/or can be extremely conservative. In this paper, we present a new method for approximating the optimal controller of the HJ reachability problem for control-affine systems. While also a specific problem class, many dynamical systems of interest are, or can be well approximated, by control-affine models. We explicitly avoid storing a representation of the reachability value function, and instead learn a controller as a sequence of simple binary classifiers. We compare our approach to existing grid-based methodologies in HJ reachability and demonstrate its utility on several examples, including a physical quadrotor navigation task

    UDP-Galactose 4β€²-Epimerase Activities toward UDP-Gal and UDP-GalNAc Play Different Roles in the Development of Drosophila melanogaster

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    In both humans and Drosophila melanogaster, UDP-galactose 4β€²-epimerase (GALE) catalyzes two distinct reactions, interconverting UDP-galactose (UDP-gal) and UDP-glucose (UDP-glc) in the final step of the Leloir pathway of galactose metabolism, and also interconverting UDP-N-acetylgalactosamine (UDP-galNAc) and UDP-N-acetylglucosamine (UDP-glcNAc). All four of these UDP-sugars serve as vital substrates for glycosylation in metazoans. Partial loss of GALE in humans results in the spectrum disorder epimerase deficiency galactosemia; partial loss of GALE in Drosophila melanogaster also results in galactose-sensitivity, and complete loss in Drosophila is embryonic lethal. However, whether these outcomes in both humans and flies result from loss of one GALE activity, the other, or both has remained unknown. To address this question, we uncoupled the two activities in a Drosophila model, effectively replacing the endogenous dGALE with prokaryotic transgenes, one of which (Escherichia coli GALE) efficiently interconverts only UDP-gal/UDP-glc, and the other of which (Plesiomonas shigelloides wbgU) efficiently interconverts only UDP-galNAc/UDP-glcNAc. Our results demonstrate that both UDP-gal and UDP-galNAc activities of dGALE are required for Drosophila survival, although distinct roles for each activity can be seen in specific windows of developmental time or in response to a galactose challenge. By extension, these data also suggest that both activities might play distinct and essential roles in humans
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