The two papers are:
Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG via Block Sparse Bayesian Learning
Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao
IEEE Trans. on Biomedical Engineering, vol. 60, no. 2, pp. 300-309, 2013
[Remark: This paper used BSBL to reconstruct raw fetal ECG. It showed that BSBL can directly recover non-sparse correlated signals without using any dictionary matrix. It may be the first solid evidence showing that exploiting correlation is an effective way to reconstruct non-sparse signals in any domains.]
Compressed Sensing of EEG for Wireless Telemonitoring with Low Energy Consumption and Inexpensive Hardware
Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao
IEEE Trans. on Biomedical Engineering, vol. 60, no. 1, pp. 221-224, 2013[This paper applied BSBL to wireless telemonitoring of EEG, showing DCT coefficients can be recovered using block-structure model. Some explanations on why DCT dictionary matrix is effective for raw EEG are further given in my ST-SBL paper.]
