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Start Over Author "Vu, Thai" Publisher institute of electrical and electronics engineers (ieee)
36 results on '"Vu, Thai"'

8. RelaHash: Deep Hashing With Relative Position

Author

Pham Vu Thai Minh, Nguyen Dong Duc Viet, Ngo Tung Son, Bui Ngoc Anh, and Jafreezal Jaafar

Subjects
General Computer Science, General Engineering, General Materials Science, Electrical and Electronic Engineering
Published
2023
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27. Double-loop control structure using proportional resonant and sequence-decoupled resonant controllers in static coordinates for dynamic voltage restorer

Author

Vu Thai Hung, Hongchun Shu, Le Ngoc Giang, and Nguyen Duc The

Subjects
Loop (topology), Sequence, Control and Systems Engineering, Control theory, Computer science, Voltage sag, Harmonics, Frame (networking), Energy Engineering and Power Technology, Electrical and Electronic Engineering, Swell, Voltage
Abstract

Among incidents on grids, the sag/swell voltage is considered as the most frequent incident. To solve this problem, custom power devices are used. In particular, the dynamic voltage restorer (DVR) is a modern and efficient customer device. DVRs are used to mitigate voltage sag/swells and harmonics on the load bus, thus protecting the sensitive loads. The DVR is a serial compensator that applies a voltage to the point of common coupling to maintain the voltage of sensitive load at the nominal value. To improve the performance of DVRs, in this study, the control strategy of the two-stage loop circuit is implemented. The external voltage control loop uses a sequence-decoupled resonant (SDR) controller, and the inner current-control loop uses the proportional resonant (PR) controller implemented in the stationary frame αβ.

Published
2019
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29. A Frequency-domain Approach to Noninvasive Intracranial Pressure Estimation

Author

Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology. Research Laboratory of Electronics, Jaishankar, Rohan, Fanelli, Andrea, Filippidis, Aristotelis, Vu, Thai, Holsapple, James, Heldt, Thomas, Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology. Research Laboratory of Electronics, Jaishankar, Rohan, Fanelli, Andrea, Filippidis, Aristotelis, Vu, Thai, Holsapple, James, and Heldt, Thomas

Abstract

Intracranial pressure (ICP) is a cranial vital sign, crucial in the monitoring and treatment of several neurological injuries. The clinically accepted measurement modalities of ICP are highly invasive, carrying risks of infection and limiting the benefits of ICP measurement to a small subset of critically ill patients. This work aims to take a step towards developing an accurate noninvasive means of estimating ICP, by utilizing a model-based frequency-domain approach. The mean ICP and pulse pressures of ICP are estimated from arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) waveforms, and the estimates are validated on an adult population, comprising of around two hours of data from five patients. The algorithm was shown to have an accuracy (mean error) of -1.5 mmHg and a precision (standard deviation of the error) of 4.3 mmHg in estimating the mean ICP. These results are comparable to the previously reported errors among the currently accepted invasive measurement methods, and well within the clinically relevant range.

Published
2021

30. A Spectral Approach to Model-Based Noninvasive Intracranial Pressure Estimation

Author

Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Jaishankar, Rohan, Fanelli, Andrea, Filippidis, Aristotelis, Vu, Thai, Holsapple, James, Heldt, Thomas, Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Jaishankar, Rohan, Fanelli, Andrea, Filippidis, Aristotelis, Vu, Thai, Holsapple, James, and Heldt, Thomas

Abstract

Background: Intracranial pressure (ICP) normally ranges from 5 to 15 mmHg. Elevation in ICP is an important clinical indicator of neurological injury, and ICP is therefore monitored routinely in several neurological conditions to guide diagnosis and treatment decisions. Current measurement modalities for ICP monitoring are highly invasive, largely limiting the measurement to critically ill patients. An accurate noninvasive method to estimate ICP would dramatically expand the pool of patients that could benefit from this cranial vital sign. Methods: This article presents a spectral approach to model-based ICP estimation from arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) measurements. The model captures the relationship between the ABP, CBFV, and ICP waveforms and utilizes a second-order model of the cerebral vasculature to estimate ICP. Results: The estimation approach was validated on two separate clinical datasets, one recorded from thirteen pediatric patients with a total duration of around seven hours, and the other recorded from five adult patients, one hour and 48 minutes in total duration. The algorithm was shown to have an accuracy (mean error) of 0.4 mmHg and −1.5 mmHg, and a precision (standard deviation of the error) of 5.1 mmHg and 4.3 mmHg, in estimating mean ICP (range of 1.3 mmHg to 24.8 mmHg) on the pediatric and adult data, respectively. These results are comparable to previous results and within the clinically relevant range. Additionally, the accuracy and precision in estimating the pulse pressure of ICP on a beat-by-beat basis were found to be 1.3 mmHg and 2.9 mmHg respectively. Conclusion: These contributions take a step towards realizing the goal of implementing a real-time noninvasive ICP estimation modality in a clinical setting, to enable accurate clinical-decision making while overcoming the drawbacks of the invasive ICP modalities., National Institute of Neurological Disorders and Stroke (Grant R21-NS084264)

Published
2021

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