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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Baldassarre, L. Aprile, C. Shoaran, M. Leblebici, Y. Cevher, V. |
| Copyright Year | 2015 |
| Description | Author affiliation: Microelectron. Syst. Lab., EPFL, Lausanne, Switzerland (Leblebici, Y.) || Lab. for Inf. & Inference Syst., EPFL, Lausanne, Switzerland (Baldassarre, L.; Aprile, C.; Cevher, V.) || Dept. of Electr. Eng., California Inst. of Technol., Pasadena, CA, USA (Shoaran, M.) |
| Abstract | Wireless implantable devices capable of monitoring the electrical activity of the brain are becoming an important tool for understanding, and potentially treating, mental diseases such as epilepsy and depression. Compressive sensing (CS) is emerging as a promising approach to directly acquire compressed signals, allowing to reduce the power consumption associated with data transmission. To this end, we propose an efficient CS scheme which exploits the structure of the intracranial EEG signals, both in sampling and recovery. Our structure-aware approach is conceptually simple to implement in hardware and yields state-of-the-art compression rates up to 32× with high reconstruction quality, as illustrated on two human iEEG datasets. |
| Starting Page | 269 |
| Ending Page | 272 |
| File Size | 554326 |
| Page Count | 4 |
| File Format | |
| e-ISBN | 9781479919635 |
| DOI | 10.1109/CAMSAP.2015.7383788 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-12-13 |
| Publisher Place | Mexico |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wavelet transforms Wavelet domain Conferences Signal reconstruction Optimization Compressed sensing |
| Content Type | Text |
| Resource Type | Article |
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