Abstract
Compression of electrocardiograms (ECG) in wireless environments, with diagnostic quality, has shown limited potential. This lack of quality preservation, using Wavelet Transform (WT), is due to the fact that the multiple levels of detail that can be achieved in the time domain are not exploited. In the present work, we propose to fully exploit the wavelet capability to operate at different levels of signal detail at different time scales. WT with an appropriate Compressed Sensing (CS) matrix is used in the electrode nodes of body sensor networks to encode and compress the ECG. Then, the signal is reconstructed using a basis pursuit denoise algorithm. Preservation of the diagnostic quality by means of standardized metrics is then tested for multiple wavelet bases and levels. High quality ECGs from 50 healthy patients are used to statistically show that diagnostic quality preservation is possible even at high compression rates. In these cases suitable ECG wavelets are required.
| Original language | English |
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| Title of host publication | 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings : (ICASSP 2016) |
| Number of pages | 5 |
| Volume | 2016 |
| Publisher | IEEE |
| Publication date | 18 May 2016 |
| Pages | 6255-6259 |
| Article number | 7472880 |
| ISBN (Electronic) | 978-1-4799-9988-0 |
| DOIs | |
| Publication status | Published - 18 May 2016 |
| Event | IEEE International Conference on Acoustics, Speech and Signal Processing 2016 - Shanghai, China Duration: 20 Mar 2016 → 25 Mar 2016 Conference number: 41 http://www.icassp2016.org/ |
Conference
| Conference | IEEE International Conference on Acoustics, Speech and Signal Processing 2016 |
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| Number | 41 |
| Country/Territory | China |
| City | Shanghai |
| Period | 20/03/2016 → 25/03/2016 |
| Internet address |
Keywords
- Body Sensor Networks
- Compressed Sensing
- ECG
- Wavelet Transform