DocumentCode :
1079419
Title :
Improved maximum frequency estimation with application to instantaneous mean frequency estimation of surface electromyography
Author :
Östlund, Nils ; Yu, Jun ; Karlsson, J. Stefan
Author_Institution :
Dept. of Biomed. Eng. & Informatics, Univ. Hosp., Umea, Sweden
Volume :
51
Issue :
9
fYear :
2004
Firstpage :
1541
Lastpage :
1546
Abstract :
The purpose of this study was to improve the maximum-frequency estimation. Three methods to estimate the maximum frequency of a bandlimited signal with additive white noise were compared. Two existing methods, the threshold-crossing method (TCM) and the hybrid method, were modified for time-frequency representations. A novel approach, the running-block threshold method (RBTM), was introduced. Based on calculation of detection probability (sensitivity) the RBTM improved the maximum-frequency estimate as compared with the TCM. The maximum-frequency estimation methods were also used to determine the integration interval for instantaneous mean-frequency (IMNF) estimation from synthesized surface electromyography containing white noise. Results showed that the IMNF estimate was improved by using any of the three methods and that the RBTM gave the best IMNF estimate.
Keywords :
AWGN; electromyography; frequency estimation; medical signal processing; signal representation; time-frequency analysis; additive white noise; bandlimited signal; detection probability; hybrid method; improved maximum frequency estimation; instantaneous mean frequency estimation; running-block threshold method; surface electromyography; threshold-crossing method; Additive white noise; Biomedical engineering; Biomedical informatics; Electromyography; Ergonomics; Frequency estimation; Physics; Signal processing; Signal to noise ratio; Time frequency analysis; Action Potentials; Algorithms; Animals; Computer Simulation; Diagnosis, Computer-Assisted; Electromyography; Humans; Models, Neurological; Models, Statistical; Muscle, Skeletal; Reproducibility of Results; Sensitivity and Specificity;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2004.827930
Filename :
1325814
Link To Document :
بازگشت