IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · Mar 2003
Analysis of heart rate variability in the presence of ectopic beats using the heart timing signal.
The time-domain signals representing the heart rate variability (HRV) in the presence of an ectopic beat exhibit a sharp transient at the position of the ectopic beat, which corrupts the signal, particularly the power spectral density (PSD) of the HRV. Consequently, there is a need for correction of this type of beat prior to any HRV analysis. This paper deals with the PSD estimation of the HRV by means of the heart timing (HT) signal when ectopic beats are present. ⋯ By using both, a white noise driven autoregressive model of the HRV signal with artificially introduced ectopic beats and actual heart rate series including ectopic beats, the more usual methods of HRV spectral estimation are compared. Results of the PSD estimation error function of the number of ectopic beats are presented. These results demonstrate that the proposed method has one order of magnitude lower error than usual ectopic beats removal strategies in preserving PSD, thus, this strategy better recovers the original clinical indexes of interest.
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The capability for multisite stimulation is one of the biggest potential advantages of microelectrode arrays (MEAs). There remain, however, several technical problems which have hindered the development of a practical stimulation system. An important design goal is to allow programmable multisite stimulation, which produces minimal interference with simultaneous extracellular and patch or whole cell clamp recording. ⋯ In addition, the vibration-free solid-state switching made it possible to record whole-cell synaptic currents in one neuron, evoked from multiple sites in the network. We have used this system to visualize spatial propagation patterns of evoked responses in cultured networks of cortical neurons. This MEA-based stimulation system is a useful tool for studying neuronal signal processing in biological neuronal networks, as well as the process of synaptic integration within single neurons.
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IEEE Trans Biomed Eng · Dec 2002
Comparative StudyIn vitro electrical properties for iridium oxide versus titanium nitride stimulating electrodes.
Stimulating electrode materials must be capable of supplying high-density electrical charge to effectively activate neural tissue. Platinum is the most commonly used material for neural stimulation. Two other materials have been considered: iridium oxide and titanium nitride. ⋯ The charge injection limit for titanium nitride was 0.87 mC/cm2, contradicting other reports estimating that titanium nitride was capable of injecting 22 mC/cm2. Iridium oxide charge storage was 4 mC/cm2, which is comparable to other published values for iridium oxide. Electrode efficiency will lead to an overall more efficient and effective device.
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IEEE Trans Biomed Eng · Dec 2002
Comparative StudyExtracellular stimulation window explained by a geometry-based model of the neuron-electrode contact.
Extracellular stimulation of single cultured neurons which are completely sealing a microelectrode is usually performed using anodic or biphasic currents of at least 200 nA. However, recently obtained experimental data demonstrate the possibility to stimulate a neuron using cathodic current pulses with less amplitude. ⋯ Modulation of the voltage sensitive channels in the sealing part of the membrane appears to be the key to successful cathodic stimulation. Furthermore, the upper limit of the stimulation window can be explained as a normal consequence of the neuronal membrane electrophysiology.
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IEEE Trans Biomed Eng · Dec 2002
Clinical Trial Controlled Clinical TrialAutomated detection and elimination of periodic ECG artifacts in EEG using the energy interval histogram method.
An automated method for electrocardiogram (ECG)-artifact detection and elimination is proposed for application to a single-channel electroencephalogram (EEG) without a separate ECG channel for reference. The method is based on three characteristics of ECG artifacts: the spike-like property, the periodicity and the lack of correlation with the EEG. The method involves a two-step process: ECG artifact detection using the energy interval histogram (EIH) method and ECG artifact elimination using a modification of ensemble average subtraction. ⋯ As a postprocessing step, we used two types of threshold adjusting algorithms that were based on the periodicity of the ECG R-peaks. The technique was applied to four whole-night sleep EEG recordings from four subjects with severe obstructive sleep apnea syndrome, from which a total of 132878 heartbeats were monitored over 31.8 h. We found that ECG artifacts were successfully detected and eliminated with FP = 0.017 and FN = 0.074 for the epochs where the elimination process is necessarily required.