Techniques in Data Compression for Electroencephalograms
- Cornelius T. Leondes
Information theory is applied to data compression in many fields, to efficiently store or transmit texts, sounds, images and signals. In this chapter, different techniques for Electroencephalograph (EEG) and Dynamic or Holter EEG data compression will be discussed, with the requirement that compression should not prevent perfect reconstruction of the original information from the compressed one (such compression techniques are called “lossless”).
The present work was performed in cooperation with the Neurological Department of the Santa Chiara Hospital in Trento where the hardware acquires up to 32 channels, with 8 bit accuracy, at a maximum sampling rate of 1 kHz. However, in everyday practice, a minor number of channels and a lower sampling rate suffice. All results reported are referred to 128 Hz sampling rate per channel, 8 bit accuracy, 20 channels (20,480 bps data stream), which is considered sufficient to achieve a good EEG signal quality. Lossy compressions can preserve relevan ...
Reference Work Entry Metrics
- Techniques in Data Compression for Electroencephalograms
- Reference Work Title
- Computational Methods in Biophysics, Biomaterials, Biotechnology and Medical Systems
- Reference Work Subtitle
- Algorithm Development, Mathematical Analysis, and Diagnostics
- pp 1200-1220
- Print ISBN
- Online ISBN
- Springer US
- Copyright Holder
- Kluwer Academic Publishers
- Additional Links
- Industry Sectors
To view the rest of this content please follow the download PDF link above.