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Correction

Correction: Kim, M.-G.; Pan, S.B. A Study on User Recognition Using the Generated Synthetic Electrocardiogram Signal. Sensors 2021, 21, 1887

IT Research Institute, Chosun University, Gwangju 61452, Republic of Korea
*
Author to whom correspondence should be addressed.
Sensors 2024, 24(14), 4652; https://doi.org/10.3390/s24144652
Submission received: 4 July 2024 / Accepted: 10 July 2024 / Published: 18 July 2024
In the original publication [1], the “Acknowledgments” section was not included. This section should include the following paragraph:
The article was written based on the first author’s doctoral dissertation [22].

Front Matter Correction

The email address of first author has been changed from [email protected] to [email protected].

Text Correction

In the second paragraph of Section 3.1, the sentence “The structure of the ACGAN used in this study was designed to ensure that the generator and the discriminator have mutually different CNN models, as shown in Figure 4” has been updated to “The structure of the ACGAN used in this study was designed to ensure that the generator and the discriminator have mutually different CNN models, as shown in Figure 4 [22].”
In the last paragraph of Section 4, the sentence “As shown in Table 5, the performance of the proposed method was 99.6%, which was higher or similar to the previous studies.” has been updated to “As shown in Table 5, the performance of Kim [22] was 99.6%, which was higher or similar to the previous studies.”

Table Correction

Table 5 is updated as appear below:

References Correction

The newly added references appear below:
22. Kim, M.G. A Study on User Recognition System Based on Ensemble Convolutional Neural Networks Using Synthetic Electrocar-Diogram Generation. Doctoral Dissertation, Department of Control and Instrumentation Engineering, Chosun University, Gwangju, Republic of Korea, 2019.
The authors apologize for any convenience caused and state that the scientific conclusions are unaffected. With this correction, the order of some references has been adjusted accordingly. This correction was approved by the Academic Editor. The original article has been updated.

Reference

  1. Kim, M.-G.; Pan, S.B. A Study on User Recognition Using the Generated Synthetic Electrocardiogram Signal. Sensors 2021, 21, 1887. [Google Scholar] [CrossRef] [PubMed]
Table 5. Comparison of recognition performance with previous studied using MIT-BIH data.
Table 5. Comparison of recognition performance with previous studied using MIT-BIH data.
ClassifierWorkDatabaseTest SetAccuracySpecificitySensitivity
1D Ensemble NetworksKim [22]MIT-BIH database169299.6%0.990.99
2D CNNJun et al. [29]100,00099%0.990.97
Abdeldayem et al. [30]25098.8%--
1D CNNZhang et al. [31]25091.1%--
MLPSidek et al. [32]-94.4%0.990.94
RBF96.2%0.990.96
KNN97.9%0.990.97
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MDPI and ACS Style

Kim, M.-G.; Pan, S.B. Correction: Kim, M.-G.; Pan, S.B. A Study on User Recognition Using the Generated Synthetic Electrocardiogram Signal. Sensors 2021, 21, 1887. Sensors 2024, 24, 4652. https://doi.org/10.3390/s24144652

AMA Style

Kim M-G, Pan SB. Correction: Kim, M.-G.; Pan, S.B. A Study on User Recognition Using the Generated Synthetic Electrocardiogram Signal. Sensors 2021, 21, 1887. Sensors. 2024; 24(14):4652. https://doi.org/10.3390/s24144652

Chicago/Turabian Style

Kim, Min-Gu, and Sung Bum Pan. 2024. "Correction: Kim, M.-G.; Pan, S.B. A Study on User Recognition Using the Generated Synthetic Electrocardiogram Signal. Sensors 2021, 21, 1887" Sensors 24, no. 14: 4652. https://doi.org/10.3390/s24144652

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