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
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
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
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.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Adaptive thresholding with inverted triangular area for real-time detection of the heart rate from photoplethysmogram traces on a smartphone.
Photoplethysmogram (PPG) signals acquired by smartphone cameras are weaker than those acquired by dedicated pulse oximeters. Furthermore, the signals have lower sampling rates, have notches in the waveform and are more severely affected by baseline drift, leading to specific morphological characteristics. This paper introduces a new feature, the inverted triangular area, to address these specific characteristics. ⋯ We collected data from 24 volunteers and compared our algorithm in peak detection with two competing algorithms designed for PPG signals, Incremental-Merge Segmentation (IMS) and Adaptive Thresholding (ADT). A sensitivity of 98.0% and a positive predictive value of 98.8% were obtained, which were 7.7% higher than the IMS algorithm in sensitivity, and 8.3% higher than the ADT algorithm in positive predictive value. The experimental results confirmed the applicability of the proposed method.
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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.