Name
Abstract | ||
|---|---|---|
This paper describes a full system-on-chip to automatically detect sleep spindle events from scalp EEG signals. These events, which are known to play an important role on memory consolidation during sleep, are also characteristic of a number of neurological diseases. The operation of the system is based on a previously reported algorithm, which used the Teager energy operator, together with the Sp... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TBCAS.2017.2690908 | IEEE Transactions on Biomedical Circuits and Systems |
Keywords | Field | DocType |
Sleep,Hardware,Cutoff frequency,Electroencephalography,Radiation detectors,Software,Complexity theory | Sleep spindle,System on a chip,Energy operator,Computer science,Electronic engineering,CMOS,Spectral edge frequency,Software,Cutoff frequency,Low-power electronics | Journal |
Volume | Issue | ISSN |
11 | 4 | 1932-4545 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Saam Iranmanesh | 1 | 1 | 1.04 |
| E Rodriguez-Villegas | 2 | 103 | 19.22 |