Ballistocardiogram Signal Denoising Using Independent Component Analysis-Reference-Cited by-同舟云学术

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Ballistocardiogram Signal Denoising Using Independent Component Analysis

Published:2017-12-12 Issue: Volume: Page:259-267
ISSN:1876-1100
Container-title:Advances in Systems, Control and Automation
language:
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Author:

Manjula B. M.,sharma Chirag

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-10-4762-6_24

Reference16 articles.

1. Mahadevan, A., Acharya, S., Sheffer, D.B., Mugler, D.H.: Ballistocardiogram artifact removal in EEG-fMRI signals using discrete Hermite transforms. IEEE J. Sel. Top. Signal Process. 2(6), 839–853 (2008)

2. He, B., Baxter, B., Edelman, B.J., Cline, C.C., Ye, W.W.: Noninvasive brain-computer interfaces based on sensorimotor rhythms. Proc. IEEE 103(6), 907–925 (2015)

3. Menon, V., Crottaz-Herbette, S.: Combined EEG and fMRI studies of human brain function. Int. Rev. Neurobiol. 66, 291–320 (2005)

4. Hamaneh, M.B., Chitravas, N., Kaiboriboon, K., Lhatoo, S.D., Loparo, K.A.: Automated removal of EKG artifact from EEG data using independent component analysis and continuous wavelet transformation. IEEE Trans. Biomed. Eng. 61(6), 1634–1641 (2014)

5. Kidmose, P., Looney, D., Ungstrup, M., Rank, M.L., Mandic, D.P.: A study of evoked potentials from ear-EEG. IEEE Trans. Biomed. Eng. 60(10), 2824–2830 (2013)

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1. Making Noise - Improving Seismocardiography Based Heart Analysis With Denoising Autoencoders;Proceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence;2023-09-21

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