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Sleep Analytics and Online Selective Anomaly Detection
Published on Oct 07, 20141656 Views
We introduce a new problem, the Online Selective Anomaly Detection (OSAD), to model a specific scenario emerging from research in sleep science. Scientists have segmented sleep into several stages and
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Chapter list
Sleep Analytics and Online Selective Anomaly Detection00:00
Selective Anomaly Detection ?00:24
what we propose03:34
Problem: Learning03:55
Problem: Design05:23
Solution: Dynamic Residue Model (DRM) - 106:30
Solution: Dynamic Residue Model (DRM) - 207:55
Z-transform as a design approach09:01
Theorem10:12
Eigen-Structure Assignment (EA) vs SVD11:44
Experiments: Sleep Staging and EEG12:32
Detection of Sleep Spindle and K-Complex - 112:51
Detection of Sleep Spindle and K-Complex - 213:02
On-Line Analysis13:28
Performance of Designed Residual for Sleep Spindle (SS)14:00
Conclusion14:45