| Literature DB >> 2035908 |
Abstract
The large volume of digital data and the demanding processing task involved in electroencephalogram (EEG) analysis place stringent requirements on computer resources in terms of data transfer, computation speed, and temporary or permanent storage. The reduction of the database to a manageable size is therefore necessary for economical use of transmission channels and the storage media. The two criteria, waveform reproducibility and processing applications, must be analyzed and optimized in terms of signal-to-noise ratio (SNR) using the various factors affecting the coding. This analysis and optimization can become cumbersome, and a specialized workstation has been developed specifically for analysis of digital coding. Our interest in data compression stems from the study of the feasibility of predicting pilots' acceleration (Gz) tolerance during flight by processing both their uncoded and coded EEG.Mesh:
Year: 1991 PMID: 2035908 DOI: 10.1007/bf02368458
Source DB: PubMed Journal: Ann Biomed Eng ISSN: 0090-6964 Impact factor: 3.934