Some experimental studies of subthreshold summation between sinusoidal grating components have been interpreted as showing very narrow channel bandwidths in human visions. This paper discusses an alternative interpretation of these experiments based on consideration of probability-summation effects among spatially distributed detectors. We conclude that frequency-selective channels must still be hypothesized in order to fit the data, but the channel bandwidth may be much wider than earlier interpretations suggest.
Mobile health is gaining increasing importance for society and the quest for new power efficient devices sampling biosignals is becoming critical. We discuss a new scheme called Variable Pulse Width Finite Rate of Innovation (VPW-FRI) to model and compress ECG signals. This technique generalizes classical FRI estimation to enable the use of a sum of asymmetric Cauchy-based pulses for modeling electrocardiogram (ECG) signals. We experimentally show that VPW-FRI indeed models ECG signals with increased accuracy compared to current standards. In addition, we study the compression efficiency of the method: compared with various widely used compression schemes, we showcase improvements in terms of compression efficiency as well as sampling rate.
Abstract-Recent work has developed a modeling method applicable to certain types of signals having a "finite rate of innovation" (FRI). Such signals contain a sparse collection of time-or frequency-limited pulses having a restricted set of allowable pulse shapes. A limitation of past work on FRI is that all of the pulses must have the same shape. Many real signals, including electrocardiograms, consist of pulses with varying widths and asymmetry, and therefore are not well fit by the past FRI methods. We present an extension of FRI allowing pulses having variable pulse width (VPW) and asymmetry. We show example results for electrocardiograms and discuss the possibility of application to signal compression and diagnostics.
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