IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · Mar 2006
Clinical TrialAn integrated neighborhood correlation and hierarchical clustering approach of functional MRI.
Clustering analysis is a promising data-driven method for the analysis of functional magnetic resonance imaging (fMRI) time series, however, the huge computation load makes it difficult for practical use. In this paper, neighborhood correlation (NC) and hierarchical clustering (HC) methods are integrated as a new approach where fMRI data are processed first by NC to get a preliminary image of brain activations, and then by HC to remove some noises. ⋯ A simulation study and an application to visual fMRI data show that the brain activations can be effectively detected and that different response patterns can be discriminated. These results suggest that the proposed new integrated approach could be useful in detecting weak fMRI signals.
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Beamspace methods are applied to EEG/MEG source localization problems in this paper. Beamspace processing involves passing the data through a linear transformation that reduces the data dimension prior to applying a desired statistical signal processing algorithm. This process generally reduces the data requirements of the subsequent algorithm. ⋯ The performance improvement offered by the beamspace approach with limited data is demonstrated by bootstrapping somatosensory data to evaluate the variability of the source location estimates obtained with each algorithm. The quantitative benefits of beamspace processing depend on the algorithm, signal to noise ratio, and amount of data. Dramatic performance improvements are obtained in scenarios with low signal to noise ratio and a small number of independent data samples.
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IEEE Trans Biomed Eng · Mar 2006
Magnetic resonance compatibility of multichannel silicon microelectrode systems for neural recording and stimulation: design criteria, tests, and recommendations.
Magnetic resonance (MR) compatibility of biomedical implants and devices represents a challenge for designers and potential risks for users. This paper addresses these problems and presents the first MR-compatible multichannel silicon chronic microelectrode system, used for recording and electrical stimulation of the central nervous system for animal models. A standard chronic assembly, from the Center for Neural Communication Technology at the University of Michigan, was tested on a 2 Tesla magnet to detect forces, heating, and image distortions, and modified to minimize or eliminate susceptibility artifacts, tissue damage, and electrode displacement, maintaining good image quality and safety to the animals. ⋯ The final selection of this part was based on MR-compatibility, biocompatibility, durability, and mechanical and chemical stability. The required adaptor to interconnect the MR-compatible microelectrode with standard data acquisition systems was also designed and fabricated. The final design is fully MR-compatible and has been successfully tested on guinea pigs.
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IEEE Trans Biomed Eng · Feb 2006
Potential-biased, asymmetric waveforms for charge-injection with activated iridium oxide (AIROF) neural stimulation electrodes.
The use of potential biasing and biphasic, asymmetric current pulse waveforms to maximize the charge-injection capacity of activated iridium oxide (AIROF) microelectrodes used for neural stimulation is described. The waveforms retain overall zero net charge for the biphasic pulse, but employ an asymmetry in the current and pulse widths of each phase, with the second phase delivered at a lower current density for a longer period of time than the leading phase. ⋯ For anodal-first pulsing, a maximum charge capacity of 9.6 mC/cm2 was obtained with an asymmetry of 1:3 at an 0.1-V bias. These measurements were made in vitro in carbonate-buffered saline using microelectrodes with a 2000 microm2 surface area.
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IEEE Trans Biomed Eng · Feb 2006
Comparative StudyA single-lead ECG enhancement algorithm using a regularized data-driven filter.
We presented a novel way of deriving a subspace filter for enhancing a noisy electrocardiogram (ECG) signal contaminated by electromyogram (EMG). The new subspace filter was based on a multiple cycle prediction (MCP) modeling of a single-lead ECG. The adoption of an MCP model resulted in a data matrix more suitable for separating noise and signal subspaces than the linear prediction (LP) model that is implicitly assumed in many existing subspace filters. ⋯ To validate the new filter in a quantitative way, 12 clean realistic ECG segments with different degrees of heart rate variability generated using the ECGSyn program were mixed with different realizations of EMG noise in the MIT-BIH Noise Stress Test Database and locally acquired EMG at a typical 10-dB signal-to-noise ratio. The performance of the proposed method was compared to three existing ECG enhancement algorithms and achieved encouraging results. In addition, various ECG recordings from MIT-Arrythmia database were also mixed with EMG noise and subjected to the same four filters resulting in a qualitative comparison of them.