Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
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Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Analysis of fractal electrodes for efficient neural stimulation.
Planar electrodes are increasingly used in a variety of neural stimulation techniques such as epidural spinal cord stimulation, epidural cortical stimulation, transcranial direct current stimulation and functional electric stimulation. Recently, optimized electrode geometries have been shown to increase the efficiency of neural stimulation by maximizing the variation of current density on the electrode surface. In the present work, a new family of modified fractal electrode geometries is developed to increase the neural activation function and enhance the efficiency of neural stimulation. ⋯ Rigorous finite element simulations were performed to compute the distribution of electric potential produced by proposed geometries, demonstrating that the neural activation function was significantly enhanced in the tissue. The activation of 800 model axons positioned around the electrodes was also quantified, showing that modified fractal geometries yielded a 22% reduction in input power consumption while maintaining the same level of neural activation. The results demonstrate the feasibility of increasing stimulation efficiency using modified fractal geometries beyond the levels already reported in the literature.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Seizure prediction with bipolar spectral power features using Adaboost and SVM classifiers.
This paper presents the results of our study on finding a lower complexity and yet a robust seizure prediction method using intracranial electroencephalogram (iEEG) recordings. We compare two classifiers: a low-complexity Adaboost and the more complex support vector machine (SVM). Adaboost is a linear classier using decision stumps, and SVM uses a nonlinear Gaussian kernel. ⋯ The proposed methods were applied on 8 invasive recordings selected from the EPILEPSIAE database, the European database of EEG seizure recordings. Doublecross validation is used by separating data sets for training and optimization from testing. The key conclusion is that Adaboost performs slightly better than SVM using a reduced feature set on average with significantly less complexity resulting in a sensitivity of 77.1% (27 of 35 seizures in 873 h recordings) and a false alarm rate of 0.18 per hour.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Fully automatic rapid DNA Ploidy Analyzer for intraoperative rapid diagnosis support.
Frozen section studies are a useful method to rapidly define tumor malignancy and identify the extent of surgical resection. However, diagnosis with a frozen section is qualitative and sometimes difficult. Therefore a quantitative method for grading tumors is desired. ⋯ We also obtained a good correlation between the MI and histological grade (WHO grading). Our new system also enabled finishing the process from sample preparation to the end of analysis in ten minutes or less. These results demonstrate that our fully automatic rapid DNA ploidy analyzer is feasible for rapid determination of glioma presence in a surgical biopsy sample.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Demonstrating the accuracy of an in-hospital ambulatory patient monitoring solution in measuring respiratory rate.
This paper presents clinical testing conducted to evaluate the accuracy of Aingeal, a wireless in-hospital patient monitor, in measuring respiration rate via impedance pneumography. Healthy volunteers were invited to simultaneously wear a CE Marked Aingeal vital signs monitor and a capnograph, the current gold standard in respiration rate measurement. ⋯ Statistical analysis of the data collected shows a mean difference of -0.73, a standard deviation of 1.61, limits of agreement of -3.88 and +2.42 bpm and a P-value of 0.22. This testing demonstrates comparable performance of the Aingeal device in measuring respiration rate with a well-accepted and widely used alternative method.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Combined use of sEMG and accelerometer in hand motion classification considering forearm rotation.
Hand motion classification using surface electromyography (sEMG) has been widely studied for its applications in upper-limb prosthesis and human-machine interface etc. Pattern-recognition based control methods have many advantages, and the reported classification accuracy can meet the requirements of practical applications. ⋯ In this paper, we give a pilot study of the reverse effect of forearm rotations on hand motion classification, and the results show that the forearm rotations can substantially degrade the classifier's performance: the average intra-position error is only 2.4%, but the average interposition classification error is as high as 44.0%. To solve this problem, we use an extra accelerometer to estimate the forearm rotation angles, and the best combination of sEMG data and accelerometer outputs can reduce the average classification error to 3.3%.