Titlebook: Biomedical Engineering Systems and Technologies; 6th International Jo Mireya Fernández-Chimeno,Pedro L. Fernandes,Hugo G Conference proceed

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Texture Classification of Proteins Using Support Vector Machines and Bio-inspired Metaheuristicsused as inputs for a Support Vector Machine. The accuracy of the proposed method is around 94 %, a statistically better performance than the classification based on the entire feature set. This classification step can be very useful for discarding over-segmented areas after a protein segmentation or identification process.

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1865-0929 topical sections on biomedical electronics and devices; bioinformatics models, methods and algorithms; bio-inspired systems and signal processing; health informatics.978-3-662-44484-9978-3-662-44485-6Series ISSN 1865-0929 Series E-ISSN 1865-0937

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Picks-Disease

Il problema inconscio-coscienza,mpedance system capable of monitoring the ventilation using textile electrodes. Apart from describing the system, in this part some tests done in a controlled environment are also shown. In the second part of this paper, an enhancement of the system is described and checked using a patient simulator.

Mechanics

https://doi.org/10.1007/978-88-470-0613-3 The proposed method has a sensitivity of 92.41 % and a Predictive Positive Value (VPP) of 93.41 % in detecting drowsiness in laboratory conditions. The results show that the proposed index may be promising to assess the alertness state of real drivers.

艺术

debris

A 2nd Order CMOS Sigma-Delta Modulator Design Suitable for Low-Power Biosensor Applicationsrter (ADC). In addition to the circuit design techniques to achieve low power consumption, the use of low supply voltage is an effective alternative to reduce the overall power consumption of a CMOS circuit. Sigma-delta modulators are well suited for the low noise requirement in biosensors due to it

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