Waveform

Summary

In electronics, acoustics, and related fields, the waveform of a signal is the shape of its graph as a function of time, independent of its time and magnitude scales and of any displacement in time. Periodic waveforms are those that vary periodically – they repeat regularly at consistent intervals. In electronics, the term is usually applied to periodically varying voltages, currents, or electromagnetic fields. In acoustics, it is usually applied to steady periodic sounds — variations of pressure in air or other media. In these cases, the waveform is an attribute that is independent of the frequency, amplitude, or phase shift of the signal. The term can also be used for non-periodic signals, like chirps and pulses. The waveform of an electrical signal can be visualized in an oscilloscope or any other device that can capture and plot its value at various times, with suitable scales in the time and value axes. The electrocardiograph is a medical device to record the waveform o

Official source

https://en.wikipedia.org/wiki/Waveform

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Little is known about the hemodynamic disturbances induced by the cerebral aneurysms in the parent artery and the effect of flow diverter stents (FDS) on these latter. A better understanding of the aneurysm-parent vessel complex relationship may aid our understanding of this disease and to optimize its treatment. The ability of volumetric flow rate (VFR) waveform to reflect the arterial compliance modifications is well known. By analyzing the VFR waveform and the pulsatility in the parent vessel, this study aimed to test the hypotheses that (1) intracranial aneurysms might disrupt the blood flow of the parent vessel and (2) the treatment by FDS might have measurable corrective effect on these changes. Ten patients followed for unruptured intracranial aneurysms treated by FDS and ten healthy volunteers as control group were included in this study. Two-dimensional quantitative phase-contrast magnetic resonance imaging (MRI) was performed on each patient on the ICA artery upstream and downstream to the aneurysm, and on each volunteer at similar locations. The aneurysms altered significantly the parent vessel pulsatility and this effect was correlated to their volume. The aneurysms treatment by FDS allowed for the restoration of a normally modulated flow and pulsatility correction in the parent vessel.

2015

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Triboelectric nanogenerators are establishing themselves as promising candidates for realizing high-efficient energy harvesting from largely available droplets. However, the conventional droplet-based liquid-solid triboelectric nanogenerator (DLS-TENG) has energy conversion efficiency of only ~ 2 × 10−5%. Here, an optimized structure of DLS-TENG with an additional top electrode is proposed aiming to increase the energy conversion from mechanical energy of sliding droplets into electricity. A peak short circuit current output is obtained up to 0.48 μA, which represents an increase of about 1000 times comparing to the same device working in single-electrode mode. The relationship between the time-domain current waveform and the movement of the droplet is analyzed in details using the equivalent circuit model to study the unique features of the electricity output from sliding motion. Critical parameters, including the dripping frequency, droplet releasing height and the liquid property, are discussed to reveal the dominant factor to maximize the triboelectric output from droplet sliding. Demonstrations of applications in droplet detecting with high accuracy and microfluidic sensor offer new significant insights into the design of triboelectric microfluidic and droplet sensors.

2022

Spatial covariance improves BCI performance for late ERPs components with high temporal variability

Ruslan Aydarkhanov, Ricardo Andres Chavarriaga Lozano, Lucian Andrei Gheorghe, Marija Uscumlic

Objective. Event Related Potentials (ERPs) reflecting cognitive response to external stimuli, are widely used in brain computer interfaces. ERP waveforms are characterized by a series of components of particular latency and amplitude. The classical ERP decoding methods exploit this waveform characteristic and thus achieve a high performance only if there is sufficient time- and phase-locking across trials. The required condition is not fulfilled if the experimental tasks are challenging or if it is needed to generalize across various experimental conditions. Features based on spatial covariances across channels can potentially overcome the latency jitter and delays since they aggregate the information across time. Approach. We compared the performance stability of waveform and covariance-based features as well as their combination in two simulated scenarios: 1) generalization across experiments on Error-related Potentials and 2) dealing with larger latency jitter across trials. Main results. The features based on spatial covariances provide a stable performance with a minor decline under jitter levels of up to ± 300 ms, whereas the decoding performance with waveform features quickly drops from 0.85 to 0.55 AUC. The generalization across ErrP experiments also resulted in a significantly more stable performance with covariance-based features. Significance. The results confirmed our hypothesis that covariance-based features can be used to: 1) classify more reliably ERPs with higher intrinsic variability in more challenging real-life applications and 2) generalize across related experimental protocols.

2020