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Related Concept Videos

Basic Continuous Time Signals01:22

Basic Continuous Time Signals

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Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
The unit step function, denoted u(t), is zero for negative time values and one for positive time values, exhibiting a discontinuity at t=0. This function often represents abrupt changes, such as the step voltage introduced when turning a car's...
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Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

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In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
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Continuous -time Fourier Transform01:11

Continuous -time Fourier Transform

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The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...
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BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

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System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
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Flame Photometry: Overview01:02

Flame Photometry: Overview

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Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
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Flame Photometry: Lab01:16

Flame Photometry: Lab

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In a flame photometer, when a solution like potassium chloride is aspirated into the flame, the solvent evaporates, leaving behind dehydrated salt. This salt dissociates into free gaseous atoms in their ground state. Some of these atoms absorb energy from the flame, leading to their excitation. The excited atoms return to the ground state, emitting photons at characteristic wavelengths. Because only electronic transitions are involved, the resulting emission lines are very narrow. The intensity...
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Related Experiment Video

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A Wireless Fiber Photometry System Based on a High-Precision CMOS Biosensor With Embedded Continuous-Time Modulation.

Mehdi Noormohammadi Khiarak, Ekaterina Martianova, Cyril Bories

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    This study introduces a novel biophotometry sensor that merges a low-noise front-end with a continuous-time modulator for high-sensitivity, energy-efficient photo-sensing. The compact, wireless device enables precise brain activity monitoring in mice.

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    Area of Science:

    • Biomedical Engineering
    • Photonics
    • Integrated Circuits

    Background:

    • Fluorescence biophotometry demands high dynamic range (DR) and sensitivity.
    • Challenges include resolving small fluorescence variations amidst noise and tissue autofluorescence.
    • Need for compact, linear, sensitive, and energy-efficient detectors.

    Purpose of the Study:

    • To present a novel biophotometry sensor integrating a low-noise front-end and a continuous-time modulator (CTSDM).
    • To achieve high-sensitivity and high energy-efficiency in photo-sensing.
    • To enable miniature, wireless biophotometry for in-vivo measurements.

    Main Methods:

    • Merged a differential CMOS photodetector and capacitive transimpedance amplifier front-end with a 1-bit CTSDM.
    • Employed a hardware sharing strategy for simplified implementation and reduced power consumption.
    • Integrated the CMOS biosensor into a miniature wireless head-mountable prototype.

    Main Results:

    • Achieved a peak dynamic range exceeding 50-dB with a 20-Hz sampling rate.
    • Demonstrated a sensitivity of 24 mV/nW and a minimum detectable current of 2.46-pA.
    • The sensor operates from a 1.8-V supply in 0.18-µm CMOS technology.

    Conclusions:

    • The proposed sensor offers a solution for high-sensitivity, energy-efficient biophotometry.
    • The integrated design simplifies hardware and reduces power consumption.
    • The wireless prototype enables in-vivo brain biophotometry in live mice.