Abstract
As a new signal processing tool, a Modified frequency slice wavelet transform (MFSWT) is proposed for physiological signal time-frequency analysis in this study. The transform generates time-frequency representation from the frequency domain, and the reconstruction is independent of frequency slice function (FSF). To realize accurate time-frequency location of signal components, a bound signal-adaptive FSF was introduced to serve as a dynamic frequency filter for the transform. This method avoids troublesome parameter selection, is signal-adaptive and easy to use. The results of two case studies demonstrate the validity of the proposed method, which has good interpretability with high time-frequency resolution, and hence has significant potential for bio-signal time-frequency analysis.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2017 Chinese Automation Congress, CAC 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3441-3444 |
| Number of pages | 4 |
| Volume | 2017-January |
| ISBN (Electronic) | 9781538635247 |
| ISBN (Print) | 9781538635254 |
| DOIs | |
| Publication status | Published - 29 Dec 2017 |
| Event | 2017 Chinese Automation Congress, CAC 2017 - Jinan, China Duration: 20 Oct 2017 → 22 Oct 2017 |
Conference
| Conference | 2017 Chinese Automation Congress, CAC 2017 |
|---|---|
| Country/Territory | China |
| City | Jinan |
| Period | 20/10/17 → 22/10/17 |
Keywords
- frequency slice wavelet transform
- Physiological signal processing
- spectrogram
- time-frequency analysis
ASJC Scopus subject areas
- Artificial Intelligence
- Control and Optimization
- Modelling and Simulation
- Computer Science Applications