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 2014
Modeling dermatome selectivity of single-and multiple-current source spinal cord stimulation systems.
A recently published computational modeling study of spinal cord stimulation (SCS) predicted that a multiple current source (MCS) system could generate a greater number of central points of stimulation in the dorsal column (DC) than a single current source (1 CS) system. However, the clinical relevance of this finding has not been established. The objective of this work was to compare the dermatomal zone selectivity of MCS and 1 CS systems. ⋯ The activation regions within the DC were determined by coupling the FEM output to a biophysical nerve fiber model, and coverage was mapped to dermatomal zones. Results showed marginal differences in activated dermatomal zones between 1 CS and MCS systems. This indicates that a MCS system may not provide incremental therapeutic benefit as suggested in prior analysis.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Evaluation of Laplacian diaphragm electromyographic recording in a dynamic inspiratory maneuver.
The analysis of the electromyographic signal of the diaphragm muscle (EMGdi) can provide important information for evaluating the respiratory muscular function. The EMGdi can be recorded using surface Ag/AgCl disc electrodes in monopolar or bipolar configuration. However, these non-invasive EMGdi recordings are usually contaminated by the electrocardiographic (ECG) signal. ⋯ Thus, the objective of this work is to compare and to evaluate CRE and traditional bipolar EMGdi recordings in a healthy subject during a dynamic inspiratory maneuver with incremental inspiratory loads. In the conducted study, it was calculated the cumulative percentage of power spectrum of EMGdi recordings to determine the signal bandwidth, and the power ratio between the EMGdi signal segments with and without cardiac activity. The results of this study suggest that EMGdi acquired with CRE electrodes is less affected by the ECG interference, achieves a wider bandwidth and a higher power ratio between segments without cardiac activity and with cardiac activity.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
A portable multi-channel wireless NIRS device for muscle activity real-time monitoring.
Near-infrared spectroscopy (NIRS) is a relative new technology in monitoring muscle oxygenation and hemo-dynamics. This paper presents a portable multi-channel wireless NIRS device for real-time monitoring of muscle activity. The NIRS sensor is designed miniaturized and modularized, to make multi-site monitoring convenient. ⋯ Besides, the system is designed with high sampling rate so as to monitor rapid oxygenation changes during muscle activities. Dark noise and long-term drift tests have been carried out, and the result indicates the device has a good performance of accuracy and stability. In vivo experiments including arterial occlusion and isometric voluntary forearm muscle contraction were performed, demonstrating the system has the ability to monitor muscle oxygenation parameters effectively even in exercise.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Analysis of EEG to quantify depth of anesthesia using Hidden Markov Model.
Real-time quantification of the patient's consciousness level during anesthesia is an important issue to avoid intraoperative awareness and post-operative side effects. A depth-of-anesthesia (DoA) monitoring method called Bispectral Index (BIS) is generally used for this purpose. However, BIS is known to be inaccurate at the transitory state, and also shows a critical time delay in quantifying the patient's consciousness level. ⋯ Since the evaluation of DoA using HMM is training based method, it have better performance with more training process. Experiments show that HDoA has a high correlation with BIS at a steady state, and outperforms BIS in two ways: (1) shorter delay time in transition state, and (2) higher Fisher Score. The validity of HDoA has been tested by 8 real clinical data.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Classification of serous ovarian tumors based on microarray data using multicategory support vector machines.
Ovarian cancer, the most fatal of reproductive cancers, is the fifth leading cause of death in women in the United States. Serous borderline ovarian tumors (SBOTs) are considered to be earlier or less malignant forms of serous ovarian carcinomas (SOCs). SBOTs are asymptomatic and progression to advanced stages is common. ⋯ Application of the optimal model of support vector machines one-versus-rest with signal-to-noise as a feature selection method gave an accuracy of 97.3%, relative classifier information of 0.916, and a kappa index of 0.941. In addition, 5 features, including the expression of putative biomarkers SNTN and AOX1, were selected to differentiate between normal, SBOT, and SOC groups. An accurate diagnosis of ovarian tumor subclasses by application of multicategory machine learning would be cost-effective and simple to perform, and would ensure more effective subclass-targeted therapy.