DocumentCode
2107497
Title
Power line interference cancellation in in-vivo neural recording
Author
Keshtkaran, Mohammad Reza ; Zhi Yang
Author_Institution
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
fYear
2012
fDate
Aug. 28 2012-Sept. 1 2012
Firstpage
5214
Lastpage
5217
Abstract
This paper presents an algorithm for removing power line interference in neural recording experiments. It does not require any interference reference signal and can reliably track interference changes in frequency, phase, and amplitude. The method includes three major steps. First, it employs a robust frequency estimator to obtain the fundamental frequency of the interference. Second, a series of discrete-time oscillators are used to generate interference harmonics, where harmonic phase and amplitude are obtained using the recursive least squares (RLS) algorithm. Third, the estimated interference harmonics are removed without distorting the neural signals at the interference frequencies. The simple structure and adequate numerical behavior of the algorithm renders it suitable for realtime implementation. Extensive experiments based on both in-vivo and synthesized data have been performed, where a reliable performance has been observed.
Keywords
electrocardiography; frequency estimation; harmonic generation; interference (signal); least squares approximations; medical signal processing; neurophysiology; recursive estimation; ECG; discrete-time oscillators; harmonic amplitude; harmonic phase; in-vivo neural recording; interference frequency; interference harmonic estimation; interference harmonic generation; neural signals; power line interference algorithm; power line interference cancellation; real-time implementation; recursive least squares algorithm; robust frequency estimator; Frequency estimation; Harmonic analysis; Interference cancellation; Oscillators; Reliability; Time frequency analysis; Action Potentials; Algorithms; Artifacts; Diagnosis, Computer-Assisted; Electricity; Electroencephalography; Neurons; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location
San Diego, CA
ISSN
1557-170X
Print_ISBN
978-1-4244-4119-8
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/EMBC.2012.6347169
Filename
6347169
Link To Document