IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · Sep 2004
Comparative Study Clinical TrialClassification of anatomical structures in MR brain images using fuzzy parameters.
We present an algorithm that automatically segments and classifies the brain structures in a set of magnetic resonance (MR) brain images using expert information contained in a small subset of the image set. The algorithm is intended to do the segmentation and classification tasks mimicking the way a human expert would reason. The algorithm uses a knowledge base taken from a small subset of semiautomatically classified images that is combined with a set of fuzzy indexes that capture the experience and expectation a human expert uses during recognition tasks. ⋯ The algorithm uses low-level image processing techniques on a pixel basis for the segmentations, then validates or corrects the segmentations, and makes the final classification decision using higher level criteria measured by the set of fuzzy indexes. We use single-echo MR images because of their high volumetric resolution; but even though we are working with only one image per brain slice, we have multiple sources of information on each pixel: absolute and relative positions in the image, gray level value, statistics of the pixel and its three-dimensional neighborhood and relation to its counterpart pixels in adjacent images. We have validated our algorithm for ease of use and precision both with clinical experts and with measurable error indexes over a Brainweb simulated MR set.
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IEEE Trans Biomed Eng · Sep 2004
Comparative StudyExtracellular recordings from patterned neuronal networks using planar microelectrode arrays.
Neuronal cell networks have been reconstructed on planar microelectrode arrays (MEAs) from dissociated hippocampal pyramidal neurons. Microcontact printing (microCP) and a photoresist-liftoff method were used to selectively localize poly-L-lysine (PLL) on the surface of MEAs. ⋯ Bursting activity with spike amplitude attenuation was observed, and multichannel recordings detected instances of coincident firing activity. Finally, we present here an extracellular recording from a approximately 2 microm bundle of guided neurites.
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IEEE Trans Biomed Eng · Sep 2004
Comparative StudyChronic measurement of the stimulation selectivity of the flat interface nerve electrode.
The flat interface nerve electrode (FINE) is an attempt to improve the stimulation selectivity of extraneural electrodes. By reshaping peripheral nerves into elliptical cylinders, central fibers are moved closer to the nerve-electrode interface, and additional surface area is created for contact placement. The goals of this study were to test the hypothesis that greater nerve reshaping leads to improved selectivity and to examine the chronic recruitment properties of the FINE. ⋯ Both the selectivity measurements and the recruitment curve characteristics were stable throughout the implant period. From an electrophysiological standpoint, the FINE is a viable alternative for neuroprosthetic devices. A histological analysis of the nerves is under way to evaluate the safety of the FINE.
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IEEE Trans Biomed Eng · Aug 2004
Comparative Study Clinical TrialAssessment of average muscle fiber conduction velocity from surface EMG signals during fatiguing dynamic contractions.
In this paper, we propose techniques of surface electromyographic (EMG) signal detection and processing for the assessment of muscle fiber conduction velocity (CV) during dynamic contractions involving fast movements. The main objectives of the study are: 1) to present multielectrode EMG detection systems specifically designed for dynamic conditions (in particular, for CV estimation); 2) to propose a novel multichannel CV estimation method for application to short EMG signal bursts; and 3) to validate on experimental signals different choices of the processing parameters. Linear adhesive arrays of electrodes are presented for multichannel surface EMG detection during movement. ⋯ The method proposed is applied to signals detected from the vastus laterialis and vastus medialis muscles during cycling at 60 cycles/min. Ten subjects were investigated during a 4-min cycling task. The method provided reliable assessment of muscle fatigue for these subjects during dynamic contractions.
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IEEE Trans Biomed Eng · Jul 2004
Comparative StudyAutomatic classification of heartbeats using ECG morphology and heartbeat interval features.
A method for the automatic processing of the electrocardiogram (ECG) for the classification of heartbeats is presented. The method allocates manually detected heartbeats to one of the five beat classes recommended by ANSI/AAMI EC57:1998 standard, i.e., normal beat, ventricular ectopic beat (VEB), supraventricular ectopic beat (SVEB), fusion of a normal and a VEB, or unknown beat type. Data was obtained from the 44 nonpacemaker recordings of the MIT-BIH arrhythmia database. ⋯ This assessment resulted in a sensitivity of 75.9%, a positive predictivity of 38.5%, and a false positive rate of 4.7% for the SVEB class. For the VEB class, the sensitivity was 77.7%, the positive predictivity was 81.9%, and the false positive rate was 1.2%. These results are an improvement on previously reported results for automated heartbeat classification systems.