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A VLSI-Based Multi-Level ECG Compression Method forHealth Care Applications
Authors
1Student, VLSI Design, Department of Electronics and Communication, IES College of Engineering / APJ Abdul Kalam Technological University, Kerala, India. 2Assistant Professor, Department of Electronics and Communication, IES College of Engineering / APJ Abdul Kalam Technological University, Kerala, India.
Article Information
- DOI
- No DOI
- Organised By
- IES College of Engineering
- Conference Date
- 15 May 2023
- Pages
- 88-94
- Article Type
- Research Article
- Check for updates
- No DOI available for cross-reference
References
[1] F. Nasimi, M. R. Khayyambashi, N. Movahhedinia, and Y. W. Law, “Exploiting similar prior knowledge for compressing ECG
signals,” Biomed. Sig. Proc. Control, vol. 60, 2020, Art. no. 101960.
[2] R. F. Yazicioglu, S. Kim, T. Torfs, H. Kim, and C. Van Hoof, “A 30 μw analog signal processor ASIC for portable biopotential
signal monitoring,” IEEE J. Solid-State Circuits, vol. 46, no. 1, pp. 209–223, Jan. 2011.
[3] C. J. Deepu, X. Zhang, C. H. Heng, and Y. Lian, “A 3-lead ECG-on-Chip with QRS detection and lossless compression for wireless
sensors,” IEEE Trans. Circuits Syst. II: Exp. Briefs, vol. 63, no. 12, pp. 1151–1155, Dec. 2016.
[4] S.-L. Chen and J.-G. Wang, “VLSI implementation of low-power cost-efficient lossless ECG encoder design for wireless
healthcare monitoring application,” Electron. Lett., vol. 49, no. 2, pp. 91–93, 2013.
[5] S.-Y. Lin, H.-T. Lin, and Y.-Y. Lin, “Lossless and lossy direct compression design with multi-signal symptom detection for low-
temperature wearable devices,” IEEE Sensors J., vol. 19, no. 2, pp. 715–725, Jan. 2019.
[6] C.-H. Luo et al., “An ECG acquisition system prototype design with flexible PDMS dry electrodes and variable transform length
DCT-IV based compression algorithm,” IEEE Sensors J., vol. 16, no. 23, pp. 8244–8254, Dec. 2016.
[7] Y. Yin et al., “A 2.63 μw ECG processor with adaptive arrhythmia detection and data compression for implantable cardiac
monitoring device,” IEEE Trans. Biomed. Circuits Syst., vol. 15, no. 4, pp. 777–790, Aug. 2021.
[8] J. Ma, T. Zhang, and M. Dong, “A novel ECG data compression method using adaptive fourier decomposition with security guarantee
in e- health applications,” IEEE J. Biomed. Health Informat., vol. 19, no. 3, pp. 986–994, May 2015.
[9] T.-H. Tsai, N.-C. Tung, and D.-B. Lin, “VLSI implementation of multi-channel ECG lossless compression system,” IEEE Trans.
Circuits Syst. II: Exp. Briefs, vol. 68, no. 8, pp. 2962–2966, Aug. 2021.
[10] K. Li, Y. Pan, F. Chen, K.-T. Cheng, and R. Huan, “Real-time lossless ECG compression for low-power wearable medical devices
based on adaptive region prediction,” Electron. Lett., vol. 50, no. 25, pp. 1904–1906, 2015.
[11] T.-H. Tsai and M. A. Hussain, “VLSI implementation of lossless ECG compression algorithm for low power devices,” IEEE Trans.
Circuits Syst. II: Exp. Briefs, vol. 67, no. 12, pp. 3317–3321, Dec. 2020.
[12] N. Attarmoghaddam, S. H. Khayat, and M. Maymandi-Nejad, “FPGA implementation of power and area efficient compressed
sensing for multi-channel ECG compression,” in Proc. 24th Iranian Conf. Elect. Eng., 2016, pp. 1027–1032.
signals,” Biomed. Sig. Proc. Control, vol. 60, 2020, Art. no. 101960.
[2] R. F. Yazicioglu, S. Kim, T. Torfs, H. Kim, and C. Van Hoof, “A 30 μw analog signal processor ASIC for portable biopotential
signal monitoring,” IEEE J. Solid-State Circuits, vol. 46, no. 1, pp. 209–223, Jan. 2011.
[3] C. J. Deepu, X. Zhang, C. H. Heng, and Y. Lian, “A 3-lead ECG-on-Chip with QRS detection and lossless compression for wireless
sensors,” IEEE Trans. Circuits Syst. II: Exp. Briefs, vol. 63, no. 12, pp. 1151–1155, Dec. 2016.
[4] S.-L. Chen and J.-G. Wang, “VLSI implementation of low-power cost-efficient lossless ECG encoder design for wireless
healthcare monitoring application,” Electron. Lett., vol. 49, no. 2, pp. 91–93, 2013.
[5] S.-Y. Lin, H.-T. Lin, and Y.-Y. Lin, “Lossless and lossy direct compression design with multi-signal symptom detection for low-
temperature wearable devices,” IEEE Sensors J., vol. 19, no. 2, pp. 715–725, Jan. 2019.
[6] C.-H. Luo et al., “An ECG acquisition system prototype design with flexible PDMS dry electrodes and variable transform length
DCT-IV based compression algorithm,” IEEE Sensors J., vol. 16, no. 23, pp. 8244–8254, Dec. 2016.
[7] Y. Yin et al., “A 2.63 μw ECG processor with adaptive arrhythmia detection and data compression for implantable cardiac
monitoring device,” IEEE Trans. Biomed. Circuits Syst., vol. 15, no. 4, pp. 777–790, Aug. 2021.
[8] J. Ma, T. Zhang, and M. Dong, “A novel ECG data compression method using adaptive fourier decomposition with security guarantee
in e- health applications,” IEEE J. Biomed. Health Informat., vol. 19, no. 3, pp. 986–994, May 2015.
[9] T.-H. Tsai, N.-C. Tung, and D.-B. Lin, “VLSI implementation of multi-channel ECG lossless compression system,” IEEE Trans.
Circuits Syst. II: Exp. Briefs, vol. 68, no. 8, pp. 2962–2966, Aug. 2021.
[10] K. Li, Y. Pan, F. Chen, K.-T. Cheng, and R. Huan, “Real-time lossless ECG compression for low-power wearable medical devices
based on adaptive region prediction,” Electron. Lett., vol. 50, no. 25, pp. 1904–1906, 2015.
[11] T.-H. Tsai and M. A. Hussain, “VLSI implementation of lossless ECG compression algorithm for low power devices,” IEEE Trans.
Circuits Syst. II: Exp. Briefs, vol. 67, no. 12, pp. 3317–3321, Dec. 2020.
[12] N. Attarmoghaddam, S. H. Khayat, and M. Maymandi-Nejad, “FPGA implementation of power and area efficient compressed
sensing for multi-channel ECG compression,” in Proc. 24th Iranian Conf. Elect. Eng., 2016, pp. 1027–1032.
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