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
Clinical TrialA functional test for the detection of infusion lines extravasation.
Extravasation during intravenous (IV) infusion is a common secondary effect with potentially serious clinical consequences. The correct positioning of the needle in the vein may be difficult to confirm when no blood return is observed. ⋯ The analysis of the exhaled CO2 signal by a pattern recognition algorithm enables the robust detection of the CO2 excess release, thereby confirming the absence of extravasation. Initial results are presented for the application of the method on a group of 89 oncology patients.
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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
Facilitating medical information search using Google Glass connected to a content-based medical image retrieval system.
Wearable computing devices are starting to change the way users interact with computers and the Internet. Among them, Google Glass includes a small screen located in front of the right eye, a camera filming in front of the user and a small computing unit. Google Glass has the advantage to provide online services while allowing the user to perform tasks with his/her hands. ⋯ In this paper, we developed a Google Glass application able to take a photo and send it to a medical image retrieval system along with keywords in order to retrieve similar cases. As a preliminary assessment of the usability of the application, we tested the application under three conditions (images of the skin; printed CT scans and MRI images; and CT and MRI images acquired directly from an LCD screen) to explore whether using Google Glass affects the accuracy of the results returned by the medical image retrieval system. The preliminary results show that despite minor problems due to the relative stability of the Google Glass, images can be sent to and processed by the medical image retrieval system and similar images are returned to the user, potentially helping in the decision making process.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Respiratory rate estimation from the oscillometric waveform obtained from a non-invasive cuff-based blood pressure device.
The presence of respiratory activity in the electrocardiogram (ECG), the pulse oximeter's photoplethysmo-graphic and continuous arterial blood pressure signals is a well-documented phenomenon. In this paper, we demonstrate that such information is also present in the oscillometric signal acquired from automatic non-invasive blood pressure monitors, and may be used to estimate the vital sign respiratory rate (RR). ⋯ Results demonstrated a good RR estimation accuracy of our method when compared to the reference values extracted from the reference respiration waveforms (mean absolute error of 2.69 breaths/min), which is comparable to existing methods in the literature that extract RR from other physiological signals. The proposed method has been implemented in Java on the Android device for use in an mHealth platform.