Title :
Matrix-based linear predictive compression of multi-channel surface emg signals
Author :
Carotti, Elias S G ; De Martin, J.C. ; Merletti, Roberto ; Farina, Dario
Author_Institution :
DAUIN, Politec. di Torino, Turin
fDate :
March 31 2008-April 4 2008
Abstract :
We propose a linear predictive coding technique for multichannel electromyographic (EMG) recordings. The signals are acquired using two-dimensional grid of electrodes which generate strongly correlated signals. Previous work only considered spectral redundancy across the signal matrix. In this paper we exploit the correlation present in the residual signals, i.e., the signals after the short term prediction. The proposed technique achieves a compression ratio of about 1divide9, i.e., slightly better than spectral-only decorrelation methods, but with a strong increase of approximately 3.2 dB SNR in the quality of the reconstructed waveform.
Keywords :
biomedical electrodes; data compression; electromyography; linear predictive coding; medical signal processing; signal reconstruction; SNR; electrodes; electromyography; linear predictive coding; matrix-based linear predictive compression; multichannel surface EMG signals; spectral redundancy; waveform reconstruction; Decoding; Electrodes; Electromyography; Filters; Linear predictive coding; Muscles; Quantization; Sensor arrays; Speech coding; Surface reconstruction; Data compression; Electromyography; Linear predictive coding;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2008.4517654