The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Compressed Sensing System Considerations for ECG and EMG Wireless Biosensors
Abstract
Compressed sensing (CS) is an emerging signal processing paradigm that enables sub-Nyquist processing of sparse signals such as electrocardiogram (ECG) and electromyogram (EMG) biosignals. Consequently, it can be applied to biosignal acquisition systems to reduce the data rate to realize ultra-low-power performance. CS is compared to conventional and adaptive sampling techniques and several system-level design considerations are presented for CS acquisition systems including sparsity and compression limits, thresholding techniques, encoder bit-precision requirements, and signal recovery algorithms. Simulation studies show that compression factors greater than 16X are achievable for ECG and EMG signals with signal-to-quantization noise ratios greater than 60 dB.
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Cites
Goldberger, A. L., Amaral, L. A. N., Glass, L., Hausdorff, J. M., Ivanov, P. C., Mark, R. G., Mietus, J. E., Moody, G. B., Peng, C.-K., & Stanley, H. E. (2000) · Circulation · doi:10.1161/01.cir.101.23.e215 · Cited by 14,809
An Introduction To Compressive Sampling
Candes, E. J., & Wakin, M. B. (2008) · IEEE Signal Processing Magazine · doi:10.1109/msp.2007.914731 · Cited by 10,017
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Cavallari, R., Martelli, F., Rosini, R., Buratti, C., & Verdone, R. (2014) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2014.012214.00007 · Cited by 710
Zhang, Z., Jung, T.-P., Makeig, S., & Rao, B. D. (2013) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2012.2226175 · Cited by 340
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Uddin, M. A., Stranieri, A., Gondal, I., & Balasubramanian, V. (2018) · IEEE Access · doi:10.1109/access.2018.2846779 · Cited by 264
Energy-Efficient Multi-Mode Compressed Sensing System for Implantable Neural Recordings
Suo, Y., Zhang, J., Xiong, T., Chin, P. S., Etienne-Cummings, R., & Tran, T. D. (2014) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2014.2359180 · Cited by 47
Metadata
- Authors
- Dixon, A. M. R., Allstot, E. G., Gangopadhyay, D., & Allstot, D. J.
- Venue
- IEEE Transactions on Biomedical Circuits and Systems
- Published
- 2012-04
- Volume
- 6
- Issue
- 2
- Pages
- 156-166
- ISSN
- 1932-4545 (ISSN-L)
- 1940-9990
- OpenAlex
- W2134207998
- Cited by
- 311
- References
- 2
- FWCI
- 30.18
- Type
- journal article
- Language
- en
- Open access
- closed
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- Dixon, A. M. R., Allstot, E. G., Gangopadhyay, D., & Allstot, D. J. (2012). Compressed Sensing System Considerations for ECG and EMG Wireless Biosensors. IEEE Transactions on Biomedical Circuits and Systems. https://doi.org/10.1109/tbcas.2012.2193668
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