MedWorm.com provides a medical RSS filtering service. Over 6000 RSS medical sources are combined and output via different filters. This feed contains the latest items from the 'EURASIP Journal on Advances in Signal Processing' source. Thu, 04 Nov 2010 21:20:30 +0100 http://www.medworm.com/index.php?rid=3934726&cid=s_38148_168_f&fid=38148&url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20806056%26dopt%3DAbstract We present an application of a modified Kalman-Filter (KF) framework for data fusion to the estimation of respiratory rate from multiple physiological sources which is robust to background noise. A novel index of the underlying signal quality of respiratory signals is presented and then used to modify the noise covariance matrix of the KF which discounts the effect of noisy data. The signal quality index, together with the KF innovation sequence, is also used to weight multiple independent estimates of the respiratory rate from independent KFs. The approach is evaluated on both a realistic artificial ECG model (with real additive noise), and on real data taken from 30 subjects with overnight polysomnograms, containing ECG, respiration and peripheral tonometry waveforms from which respirati... EURASIP Journal on Advances in Signal Processing journals http://www.medworm.com/rss/comments.php?id=3934726 Sun, 05 Sep 2010 12:21:09 +0100 3934726 http://www.medworm.com/index.php?rid=3900501&cid=s_38148_168_f&fid=38148&url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20730031%26dopt%3DAbstract Authors: Aviyente S, Bernat EM, Malone SM, Iacono WG Joint time-frequency representations offer a rich representation of event related potentials (ERPs) that cannot be obtained through individual time or frequency domain analysis. This representation, however, comes at the expense of increased data volume and the difficulty of interpreting the resulting representations. Therefore, methods that can reduce the large amount of time-frequency data to experimentally relevant components are essential. In this paper, we present a method that reduces the large volume of ERP time-frequency data into a few significant time-frequency parameters. The proposed method is based on applying the widely-used matching pursuit (MP) approach, with a Gabor dictionary, to principal components extracted from ... EURASIP Journal on Advances in Signal Processing journals http://www.medworm.com/rss/comments.php?id=3900501 Fri, 01 Jan 2010 00:00:00 +0100 3900501 http://www.medworm.com/index.php?rid=3457201&cid=s_38148_168_f&fid=38148&url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D20376204%26dopt%3DAbstract Authors: Tadepalli SC, Shivanna KH, Magnotta VA, Kallemeyn NA, Grosland NM Computational models of joint anatomy and function provide a means for biomechanists, physicians, and physical therapists to understand the effects of repetitive motion, acute injury, and degenerative diseases. Finite element models, for example, may be used to predict the outcome of a surgical intervention or to improve the design of prosthetic implants. Countless models have been developed over the years to address a myriad of orthopaedic procedures. Unfortunately, few studies have incorporated patient-specific models. Historically, baseline anatomic models have been used due to the demands associated with model development. Moreover, surgical simulations impose additional modeling challenges. Current meshing ... EURASIP Journal on Advances in Signal Processing journals http://www.medworm.com/rss/comments.php?id=3457201 Fri, 01 Jan 2010 00:00:00 +0100 3457201 http://www.medworm.com/index.php?rid=1926919&cid=s_38148_168_f&fid=38148&url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18784852%26dopt%3DAbstract Authors: Wang Z, Maier A, Logothetis NK, Liang H We propose an empirical mode decomposition (EMD-) based method to extract features from the multichannel recordings of local field potential (LFP), collected from the middle temporal (MT) visual cortex in a macaque monkey, for decoding its bistable structure-from-motion (SFM) perception. The feature extraction approach consists of three stages. First, we employ EMD to decompose nonstationary single-trial time series into narrowband components called intrinsic mode functions (IMFs) with time scales dependent on the data. Second, we adopt unsupervised K-means clustering to group the IMFs and residues into several clusters across all trials and channels. Third, we use the supervised common spatial patterns (CSP) approach to design spatial f... EURASIP Journal on Advances in Signal Processing journals http://www.medworm.com/rss/comments.php?id=1926919 Sun, 02 Nov 2008 18:58:04 +0100 1926919