Signal Quality Assessment
==========================

This section covers the signal quality assessment techniques provided by the VitalDSP library. These methods are designed to evaluate and improve the quality of biomedical signals by estimating signal-to-noise ratios, detecting and removing artifacts, and separating sources.

Adaptive SNR Estimation
-----------------------
Methods for adaptively estimating the Signal-to-Noise Ratio (SNR) of signals, allowing for real-time adjustments to improve signal quality.

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Artifact Detection and Removal
------------------------------
Techniques for detecting and removing artifacts from signals, crucial for maintaining the integrity of biomedical signal analysis.

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Blind Source Separation
-----------------------
Methods for separating mixed signals into their original, independent sources without prior knowledge of the mixing process, often used in EEG and ECG analysis.

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Multi-Modal Artifact Detection
------------------------------
Techniques for detecting artifacts across multiple modalities, ensuring that combined signals are free from noise and other distortions.

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SNR Computation
---------------
Functions for computing the Signal-to-Noise Ratio (SNR) of signals, which is a critical metric in assessing the quality of biomedical signals.

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Signal Quality Index
--------------------
This module provides methods to calculate various signal quality indices (SQI), which help in assessing the reliability and usability of the recorded signals.

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Signal Quality
--------------
Comprehensive tools for assessing and enhancing the overall quality of signals. This includes both objective measures and methods for improving signal integrity.

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