Analysis of the effect of machine learning methods on the correction of rr intervals and impact on HRV parameters

I need to write an introduction and literature review for a research paper on analyzing the impact of machine learning and deep learning methods for correcting RR intervals for noise present and missing data for HRV parameter estimation.

The paper has two objectives:
1- Correction of RR intervals using ML models
2- Investigate the effect of machine learning methods by analyzing HRV parameter estimation methods and compare them with state-of-the-art methods in the literature
The literature review should mention the following:
1- The similar existing studies
2- The traditional methods investigated for this task, such as bootstrapping and interpolation methods (nearest neighbor, linear, cubic spline, and piecewise cubic Hermite).
 Analyzed the effect of the error on HRV:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7240322/

Some useful resources for this part:
Analyzed the effect of correction algorithms on HRV:
https://www.sciencedirect.com/science/article/pii/S0169260710002877?via%3Dihub
https://www.mdpi.com/1424-8220/19/14/3163
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8927864/
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0240220
https://ieeexplore.ieee.org/document/6418424
https://pubmed.ncbi.nlm.nih.gov/360020/
https://www.sciencedirect.com/science/article/pii/S1959031823000258
https://www.researchgate.net/publication/313419861_Heart_Rate_Variability_A_Comparison_of_Artefact_Correction_Methods
https://www.researchgate.net/publication/281743756_Comparison_of_HRV_Parameters_Derived_from_Photoplethysmography_and_Electrocardiography_Signals
https://paulogentil.com/pdf/Heart%20Rate%20Variability%20During%20Exercise%20-%20A%20Comparison%20of%20Artefact%20Correction%20Methods.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679245/
https://journals.physiology.org/doi/epdf/10.1152/japplphysiol.00927.2016
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679245/
https://pubmed.ncbi.nlm.nih.gov/21194782/

The introduction should contain the following topics:
1- Heart Rate Variability (HRV) and its research significance
2- Wearable Devices and Their Implications for HRV Measurement
4- Benefit of machine learning method over traditional methods
3- The objective of the paper that is to analyze the effects of machine learning imputation techniques on the treatment of errors series and compare it with state-of-the-art methods

In the introduction, make sure to mention more than 10% of beats recorded contain error cite:
https://www.mdpi.com/1424-8220/19/14/3163
also discusses error amount using various devices: https://www.mdpi.com/1424-8220/21/4/1061, https://mhealth.jmir.org/2019/3/e10828/
https://pubmed.ncbi.nlm.nih.gov/29668452/

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