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Items: 1 to 20 of 205

1.

Removal of artifacts in knee joint vibroarthrographic signals using ensemble empirical mode decomposition and detrended fluctuation analysis.

Wu Y, Yang S, Zheng F, Cai S, Lu M, Wu M.

Physiol Meas. 2014 Mar;35(3):429-39. doi: 10.1088/0967-3334/35/3/429. Epub 2014 Feb 12.

PMID:
24521557
2.

Representation of fluctuation features in pathological knee joint vibroarthrographic signals using kernel density modeling method.

Yang S, Cai S, Zheng F, Wu Y, Liu K, Wu M, Zou Q, Chen J.

Med Eng Phys. 2014 Oct;36(10):1305-11. doi: 10.1016/j.medengphy.2014.07.008. Epub 2014 Aug 3.

PMID:
25096412
3.

Adaptive cancellation of muscle contraction interference in vibroarthrographic signals.

Zhang YT, Rangayyan RM, Frank CB, Bell GD.

IEEE Trans Biomed Eng. 1994 Feb;41(2):181-91.

PMID:
8026851
4.

Adaptive time-frequency analysis of knee joint vibroarthrographic signals for noninvasive screening of articular cartilage pathology.

Krishnan S, Rangayyan RM, Bell GD, Frank CB.

IEEE Trans Biomed Eng. 2000 Jun;47(6):773-83.

PMID:
10833852
5.

Parametric representation and screening of knee joint vibroarthrographic signals.

Rangayyan RM, Krishnan S, Bell GD, Frank CB, Ladly KO.

IEEE Trans Biomed Eng. 1997 Nov;44(11):1068-74.

PMID:
9353986
6.

Strict 2-Surface Proximal Classification of Knee-joint Vibroarthrographic Signals.

Mu T, Nandi AK, Rangayyan RM.

Conf Proc IEEE Eng Med Biol Soc. 2007;2007:4911-4.

PMID:
18003107
7.

Computer-aided diagnosis of knee-joint disorders via vibroarthrographic signal analysis: a review.

Wu Y, Krishnan S, Rangayyan RM.

Crit Rev Biomed Eng. 2010;38(2):201-24.

PMID:
20932239
8.

An enhanced algorithm for knee joint sound classification using feature extraction based on time-frequency analysis.

Kim KS, Seo JH, Kang JU, Song CG.

Comput Methods Programs Biomed. 2009 May;94(2):198-206. doi: 10.1016/j.cmpb.2008.12.012. Epub 2009 Feb 13.

PMID:
19217685
9.

Arrhythmia ECG noise reduction by ensemble empirical mode decomposition.

Chang KM.

Sensors (Basel). 2010;10(6):6063-80. doi: 10.3390/s100606063. Epub 2010 Jun 17.

10.

Ensemble Empirical Mode Decomposition based methodology for ultrasonic testing of coarse grain austenitic stainless steels.

Sharma GK, Kumar A, Jayakumar T, Purnachandra Rao B, Mariyappa N.

Ultrasonics. 2015 Mar;57:167-78. doi: 10.1016/j.ultras.2014.11.008. Epub 2014 Nov 28.

PMID:
25488024
11.

Screening of vibroarthrographic signals via adaptive segmentation and linear prediation modeling.

Moussavi ZM, Rangayyan RM, Bell GD, Frank CB, Ladly KO, Zhang YT.

IEEE Trans Biomed Eng. 1996 Jan;43(1):15-23.

PMID:
8567002
12.

Modeling and classification of knee-joint vibroarthrographic signals using probability density functions estimated with Parzen windows.

Rangayyan RM, Wu Y.

Conf Proc IEEE Eng Med Biol Soc. 2008;2008:2099-102. doi: 10.1109/IEMBS.2008.4649607.

PMID:
19163110
13.

Analysis of vibroarthrographic signals with features related to signal variability and radial-basis functions.

Rangayyan RM, Wu Y.

Ann Biomed Eng. 2009 Jan;37(1):156-63. doi: 10.1007/s10439-008-9601-1. Epub 2008 Nov 18.

PMID:
19015987
14.

Discriminating brain activity from task-related artifacts in functional MRI: fractal scaling analysis simulation and application.

Lee JM, Hu J, Gao J, Crosson B, Peck KK, Wierenga CE, McGregor K, Zhao Q, White KD.

Neuroimage. 2008 Mar 1;40(1):197-212. doi: 10.1016/j.neuroimage.2007.11.016. Epub 2007 Nov 22.

15.

Screening of knee-joint vibroarthrographic signals using statistical parameters and radial basis functions.

Rangayyan RM, Wu YF.

Med Biol Eng Comput. 2008 Mar;46(3):223-32. Epub 2007 Oct 25.

PMID:
17960443
16.

Baseline drift removal and denoising of MCG data using EEMD: role of noise amplitude and the thresholding effect.

Mariyappa N, Sengottuvel S, Parasakthi C, Gireesan K, Janawadkar MP, Radhakrishnan TS, Sundar CS.

Med Eng Phys. 2014 Oct;36(10):1266-76. doi: 10.1016/j.medengphy.2014.06.023. Epub 2014 Jul 26.

PMID:
25074650
17.

A data-driven noise reduction method and its application for the enhancement of stress wave signals.

Feng HL, Fang YM, Xiang XQ, Li J, Li GH.

ScientificWorldJournal. 2012;2012:353081. doi: 10.1100/2012/353081. Epub 2012 Nov 20.

18.

The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique.

Sweeney KT, McLoone SF, Ward TE.

IEEE Trans Biomed Eng. 2013 Jan;60(1):97-105. doi: 10.1109/TBME.2012.2225427. Epub 2012 Oct 18.

PMID:
23086501
19.
20.

Automatic de-noising of knee-joint vibration signals using adaptive time-frequency representations.

Krishnan S, Rangayyan RM.

Med Biol Eng Comput. 2000 Jan;38(1):2-8.

PMID:
10829383
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