Data Integration for Medical Information Management

Authors:
Mingui Sun;Yun Q. Shi;Qiang Liu;Robert J. Sclabassi
Affiliations:
Departments of Neurosurgery, Electrical Engineering and Bioengineering, Laboratory for Computational Neuroscience, University of Pittsburgh, Pittsburg, USA 15260;Departments of Neurosurgery and Electrical Engineering, University of Pittsburgh, Pittsburg, USA 15260;Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newyork, USA 07102;Departments of Neurosurgery, Electrical Engineering and Bioengineering, Laboratory for Computational Neuroscience, University of Pittsburgh, Pittsburg, USA 15260
Venue:
Journal of VLSI Signal Processing Systems
Year:
2005

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Abstract

We present a new method for data integration and security by mixing medical waveforms and images with encrypted patient identifiers and unencrypted ancillary information, such as acquisition parameters, diagnostic comments and notes in textual, pictorial, and voice forms. We vary the sampling rate according to the instantaneous frequency of the signal. Redundant samples (or pixels) are eliminated and replaced by associative data which are labeled using a status string encoded based on the Huffman and run-length techniques. This method achieves both data compression and integration simultaneously, allows synchronized presentation of information from different sources by using multimedia technology, and provides data security features.