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Electromyogram data compression using single-tree and modified zero-tree wavelet encoding

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4 Author(s)
Wellig, P. ; Signal & Inf. Process. Lab., Fed. Inst. of Technol., Zurich, Switzerland ; Zhenlan Cheng ; Semling, M. ; Moschytz, George S.

The long-term analysis of the neuromuscular systems, and applications in telemedicine, make electromyogram (EMG) data compression a subject of great practical importance. However, in spite of the increasing demand, only a few studies have been published on this subject. In this paper, we present two wavelet-based lossy compression techniques for EMG data. We propose modifications to the so-called `embedded zero-tree wavelet coder', which yield very good results in ECG compression applications. We have implemented the algorithms in Matlab and C++ and tested then with several EMG recordings

Published in:

Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE  (Volume:3 )

Date of Conference:

29 Oct-1 Nov 1998