IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · Dec 2006
Mechanism of nerve conduction block induced by high-frequency biphasic electrical currents.
The mechanisms of nerve conduction block induced by high-frequency biphasic electrical currents were investigated using a lumped circuit model of the myelinated axon based on Frankenhaeuser-Huxley (FH) model or Chiu-Ritchie-Rogart-Stagg-Sweeney (CRRSS) model. The FH model revealed that the constant activation of potassium channels at the node under the block electrode, rather than inactivation of sodium channels, is the likely mechanism underlying conduction block of myelinated axons induced by high-frequency biphasic stimulation. However, the CRRSS model revealed a different blocking mechanism where the complete inactivation of sodium channels at the nodes next to the block electrode caused the nerve conduction block. ⋯ This frequency difference indicated that the constant activation of potassium channels might be the underlying mechanism of conduction block observed in animal experiments. Using the FH model, this study also showed that the axons could recover from conduction block within 1 ms after termination of the blocking stimulation, which also agrees very well with the animal experiments where nerve block could be reversed immediately once the blocking stimulation was removed. This simulation study, which revealed two possible mechanisms of nerve conduction block in myelinated axons induced by high-frequency biphasic stimulation, can guide future animal experiments as well as optimize stimulation waveforms for electrical nerve block in clinical applications.
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IEEE Trans Biomed Eng · Dec 2006
A novel ECG data compression method based on nonrecursive discrete periodized wavelet transform.
In this paper, a novel electrocardiogram (ECG) data compression method with full wavelet coefficients is proposed. Full wavelet coefficients involve a mean value in the termination level and the wavelet coefficients of all octaves. This new approach is based on the reversible round-off nonrecursive one-dimensional (1-D) discrete periodized wavelet transform (1-D NRDPWT), which performs overall stages decomposition with minimum register word length and resists truncation error propagation. ⋯ This quantization process can be performed without an extra divider. The two performance parameters, CR and percentage root mean square difference (PRD), are evaluated using the MIT-BIH arrhythmia database. Compared with the SPIHT scheme, the PRD is improved by 14.95% for 4 < or = CR < or = 12 and 17.6% for 14 < or = CR < or = 20.
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IEEE Trans Biomed Eng · Nov 2006
Simulation of surface EMG signals for a multilayer volume conductor with triangular model of the muscle tissue.
This study analytically describes surface electromyogram (sEMG) signals generated by a model of a triangular muscle, i.e., a muscle with fibers arranged in a fan shape. Examples of triangular muscles in the human body are the deltoid, the pectoralis major, the trapezius, the adductor pollicis. A model of triangular muscle is proposed. ⋯ As a representative example of application of the simulation model, the influence of the inhomogeneity of the volume conductor in conduction velocity (CV) estimation is addressed (for two channels; maximum likelihood and reference point methods). Different fiber depths, electrode placements and small misalignments of the detection system with respect to the fiber have been simulated. The error in CV estimation is large when the depth of the fiber increases, when the detection system is not aligned with the fiber and close to the innervation point and to the tendons.
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IEEE Trans Biomed Eng · Nov 2006
Comparative StudyCombined optimization of spatial and temporal filters for improving brain-computer interfacing.
Brain-computer interface (BCI) systems create a novel communication channel from the brain to an output device by bypassing conventional motor output pathways of nerves and muscles. Therefore they could provide a new communication and control option for paralyzed patients. ⋯ The evaluation of 60 experiments involving 22 different subjects demonstrates the significant superiority of the proposed algorithm over to its classical counterpart: the median classification error rate was decreased by 11%. Apart from the enhanced classification, the spatial and/or the spectral filter that are determined by the algorithm can also be used for further analysis of the data, e.g., for source localization of the respective brain rhythms.
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IEEE Trans Biomed Eng · Nov 2006
Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis.
Lempel-Ziv complexity (LZ) and derived LZ algorithms have been extensively used to solve information theoretic problems such as coding and lossless data compression. In recent years, LZ has been widely used in biomedical applications to estimate the complexity of discrete-time signals. ⋯ We have carried out an investigation aimed at gaining a better understanding of the LZ complexity itself, especially regarding its interpretability as a biomedical signal analysis technique. Our results indicate that LZ is particularly useful as a scalar metric to estimate the bandwidth of random processes and the harmonic variability in quasi-periodic signals.