Adaptive spatio-temporal filtration of bioelectrical signals

Author

Östlund, N. ; Wiklund, U. ; Yu, J. ; Karlsson, J.S.

Author_Institution

Dept. of Biomedical Eng. & Informatics, Univ. Hosp., Umea

fYear

2006

Firstpage

5983

Lastpage

5986

Abstract

In this paper we show how independent component analysis (ICA) algorithms can be used to perform spatio-temporal filtration of electromyographic (EMG) and electrocardiographic (ECG) signals. The technique was used to decompose the EMG signals into motor unit action potential (MUAP) trains. From the 88 outputs of the adaptive spatio-temporal filtration, three groups of different MUAP train patterns were found. The technique was also used to obtain a fetus´ ECG and showed better result compared to using ICA

Keywords

adaptive filters; electrocardiography; electromyography; independent component analysis; medical signal processing; obstetrics; spatiotemporal phenomena; ECG; EMG; ICA; MUAP train patterns; adaptive spatiotemporal filtration; bioelectrical signals; electrocardiography; electromyography; fetus; independent component analysis; motor unit action potential; signal decomposition; Bioelectric phenomena; Biomedical engineering; Electrocardiography; Electrodes; Electromyography; Fetus; Filters; Filtration; Hardware; Pregnancy; Adaptive filter; ECG, EMG;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the

Conference_Location

Shanghai

Print_ISBN

0-7803-8741-4

Type

conf

DOI

10.1109/IEMBS.2005.1615854

Filename

1615854