Home // AICT 2014, The Tenth Advanced International Conference on Telecommunications // View article
Authors:
Hugo Oliveira
Arnaldo Silva
Igor Diniz
Gustavo Sampaio
Leonardo Batista
Keywords: data compression; telemedicine; polysomnographic signals; lossy compression; discrete cosine transform.
Abstract:
Data compression techniques for electrocardiographic and electroencephalographic exams have been widely reported in the literature over the last decades; but, there are no papers offering a unique solution for all biological signals typically present in polysomnographic records. Aiming to fill this gap, the present work proposes a method of lossy compression for polysomnographic signals based on optimal quantization of the coefficients obtained from the discrete cosine transform. The potentially grave distortions generated by the information loss are controlled by a compression parameter that may be configured to reach the desired Normalized Percent Root-mean-square Difference generating the optimum quantization vector with a minimization of the Lagrange parameter. The quantized signal is sent to a prediction by partial matching compressor, which works as the entropy coder of this compression strategy. The method was tested using the signals in the Polysomnographic database created by the Massachusetts Institute of Technology and Boston's Beth Israel Hospital, achieving compression ratios between 2.16:1 and 67.48:1 with distortion values between 1.0% and 4.0%.
Pages: 26 to 34
Copyright: Copyright (c) IARIA, 2014
Publication date: July 20, 2014
Published in: conference
ISSN: 2308-4030
ISBN: 978-1-61208-360-5
Location: Paris, France
Dates: from July 20, 2014 to July 24, 2014