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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Milanesi, M. Martini, N. Vanello, N. Positano, V. Santarelli, M.F. Paradiso, R. De Rossi, D. Landini, L. |
| Copyright Year | 2006 |
| Description | Author affiliation: Interdepartmental Res. Center "E. Piaggio", Pisa Univ. (Milanesi, M.; Martini, N.; Vanello, N.) |
| Abstract | Electrocardiographic (ECG) signals are affected by several kinds of artifacts, that may hide vital signs of interest. Motion artifacts, due to the motion of the electrodes in relation to patient skin, are particularly frequent in bioelectrical signals acquired by wearable systems. In this paper we propose different approaches in order to get rid of motion confounds. The first approach we follow starts from measuring electrode motion provided by an accelerometer placed on the electrode and use this measurement in an adaptive filtering system to remove the noise present in the ECG. The second approach is based on independent component analysis methods applied to multichannel ECG recordings; we propose to use both instantaneous model and a frequency domain implementation of the convolutive model that accounts for different paths of the source signals to the electrodes |
| Sponsorship | IEEE EMB |
| Starting Page | 3391 |
| Ending Page | 3394 |
| File Size | 345359 |
| Page Count | 4 |
| File Format | |
| ISBN | 1424400325 |
| ISSN | 1557170X |
| DOI | 10.1109/IEMBS.2006.260464 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-08-30 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Electrodes Electrocardiography Motion measurement Noise measurement Skin Bioelectric phenomena Accelerometers Adaptive filters Independent component analysis Frequency domain analysis |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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