ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking
Designing an ECG sensor circuit requires a comprehensive approach to detect, amplify, filter, and condition the weak electrical signals produced by the heart. To evaluate sensor performance under realistic conditions, diverse ECG signals with embedded watermarks are generated, enabling an assessment...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/7/2321 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849730213650366464 |
|---|---|
| author | Chih-Yu Hsu Chih-Yin Chang Yin-Chi Chen Jasper Wu Shuo-Tsung Chen |
| author_facet | Chih-Yu Hsu Chih-Yin Chang Yin-Chi Chen Jasper Wu Shuo-Tsung Chen |
| author_sort | Chih-Yu Hsu |
| collection | DOAJ |
| description | Designing an ECG sensor circuit requires a comprehensive approach to detect, amplify, filter, and condition the weak electrical signals produced by the heart. To evaluate sensor performance under realistic conditions, diverse ECG signals with embedded watermarks are generated, enabling an assessment of how effectively the sensor and its signal-conditioning circuitry handle these modified signals. A Variational Autoencoder (VAE) framework is employed to generate the watermarked ECG signals, addressing critical concerns in the digital era, such as data security, authenticity, and copyright protection. Three watermarking strategies are examined in this study: embedding watermarks in the mean (μ) of the VAE’s latent space, embedding them through the latent variable (z), and using post-reconstruction watermarking in the frequency domain. Experimental results demonstrate that watermarking applied through the mean (μ) and in the frequency domain achieves a low Mean Squared Error (MSE) while maintaining stable signal fidelity across varying watermark strengths (α), latent space dimensions, and noise levels. These findings indicate that the mean (μ) and frequency domain methods offer robust performance and are minimally affected by changes in these parameters, making them particularly suitable for preserving ECG signal quality. By contrasting these methods, this study provides insights into selecting the most appropriate watermarking technique for ECG sensor applications. Incorporating watermarking into sensor design not only strengthens data security and authenticity but also supports reliable signal acquisition in modern healthcare environments. Overall, the results underscore the effectiveness of combining VAEs with watermarking strategies to produce high-fidelity, resilient ECG signals for both sensor performance evaluation and the protection of digital content. |
| format | Article |
| id | doaj-art-eab4cedc8ac54ffabea482a7051b2b52 |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-eab4cedc8ac54ffabea482a7051b2b522025-08-20T03:08:56ZengMDPI AGSensors1424-82202025-04-01257232110.3390/s25072321ECG Sensor Design Assessment with Variational Autoencoder-Based Digital WatermarkingChih-Yu Hsu0Chih-Yin Chang1Yin-Chi Chen2Jasper Wu3Shuo-Tsung Chen4School of Transportation, Fujian University of Technology, Fuzhou 350118, ChinaDepartment of Medical Informatics, Chung Shan Medical University, Taichung 40201, TaiwanDepartment of Medical Informatics, Chung Shan Medical University, Taichung 40201, TaiwanKang Chiao International School, Linkou Campus, New Taipei City 244, TaiwanDepartment of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 807618, TaiwanDesigning an ECG sensor circuit requires a comprehensive approach to detect, amplify, filter, and condition the weak electrical signals produced by the heart. To evaluate sensor performance under realistic conditions, diverse ECG signals with embedded watermarks are generated, enabling an assessment of how effectively the sensor and its signal-conditioning circuitry handle these modified signals. A Variational Autoencoder (VAE) framework is employed to generate the watermarked ECG signals, addressing critical concerns in the digital era, such as data security, authenticity, and copyright protection. Three watermarking strategies are examined in this study: embedding watermarks in the mean (μ) of the VAE’s latent space, embedding them through the latent variable (z), and using post-reconstruction watermarking in the frequency domain. Experimental results demonstrate that watermarking applied through the mean (μ) and in the frequency domain achieves a low Mean Squared Error (MSE) while maintaining stable signal fidelity across varying watermark strengths (α), latent space dimensions, and noise levels. These findings indicate that the mean (μ) and frequency domain methods offer robust performance and are minimally affected by changes in these parameters, making them particularly suitable for preserving ECG signal quality. By contrasting these methods, this study provides insights into selecting the most appropriate watermarking technique for ECG sensor applications. Incorporating watermarking into sensor design not only strengthens data security and authenticity but also supports reliable signal acquisition in modern healthcare environments. Overall, the results underscore the effectiveness of combining VAEs with watermarking strategies to produce high-fidelity, resilient ECG signals for both sensor performance evaluation and the protection of digital content.https://www.mdpi.com/1424-8220/25/7/2321variational AutoEncoderFourier-simulated ECG datasetlatent variable spacewatermarking technology |
| spellingShingle | Chih-Yu Hsu Chih-Yin Chang Yin-Chi Chen Jasper Wu Shuo-Tsung Chen ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking Sensors variational AutoEncoder Fourier-simulated ECG dataset latent variable space watermarking technology |
| title | ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking |
| title_full | ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking |
| title_fullStr | ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking |
| title_full_unstemmed | ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking |
| title_short | ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking |
| title_sort | ecg sensor design assessment with variational autoencoder based digital watermarking |
| topic | variational AutoEncoder Fourier-simulated ECG dataset latent variable space watermarking technology |
| url | https://www.mdpi.com/1424-8220/25/7/2321 |
| work_keys_str_mv | AT chihyuhsu ecgsensordesignassessmentwithvariationalautoencoderbaseddigitalwatermarking AT chihyinchang ecgsensordesignassessmentwithvariationalautoencoderbaseddigitalwatermarking AT yinchichen ecgsensordesignassessmentwithvariationalautoencoderbaseddigitalwatermarking AT jasperwu ecgsensordesignassessmentwithvariationalautoencoderbaseddigitalwatermarking AT shuotsungchen ecgsensordesignassessmentwithvariationalautoencoderbaseddigitalwatermarking |