A Real-Time Sequential Ship Roll Prediction Scheme Based on Adaptive Sliding Data Window

2018 ◽  
Vol 48 (12) ◽  
pp. 2115-2125 ◽  
Author(s):  
Jianchuan Yin ◽  
Ning Wang ◽  
Anastassios N. Perakis
2019 ◽  
Vol 24 (5) ◽  
pp. 509-519 ◽  
Author(s):  
Andrea Fanelli ◽  
Frederick W. Vonberg ◽  
Kerri L. LaRovere ◽  
Brian K. Walsh ◽  
Edward R. Smith ◽  
...  

OBJECTIVEIn the search for a reliable, cooperation-independent, noninvasive alternative to invasive intracranial pressure (ICP) monitoring in children, various approaches have been proposed, but at the present time none are capable of providing fully automated, real-time, calibration-free, continuous and accurate ICP estimates. The authors investigated the feasibility and validity of simultaneously monitored arterial blood pressure (ABP) and middle cerebral artery (MCA) cerebral blood flow velocity (CBFV) waveforms to derive noninvasive ICP (nICP) estimates.METHODSInvasive ICP and ABP recordings were collected from 12 pediatric and young adult patients (aged 2–25 years) undergoing such monitoring as part of routine clinical care. Additionally, simultaneous transcranial Doppler (TCD) ultrasonography–based MCA CBFV waveform measurements were performed at the bedside in dedicated data collection sessions. The ABP and MCA CBFV waveforms were analyzed in the context of a mathematical model, linking them to the cerebral vasculature’s biophysical properties and ICP. The authors developed and automated a waveform preprocessing, signal-quality evaluation, and waveform-synchronization “pipeline” in order to test and objectively validate the algorithm’s performance. To generate one nICP estimate, 60 beats of ABP and MCA CBFV waveform data were analyzed. Moving the 60-beat data window forward by one beat at a time (overlapping data windows) resulted in 39,480 ICP-to-nICP comparisons across a total of 44 data-collection sessions (studies). Moving the 60-beat data window forward by 60 beats at a time (nonoverlapping data windows) resulted in 722 paired ICP-to-nICP comparisons.RESULTSGreater than 80% of all nICP estimates fell within ± 7 mm Hg of the reference measurement. Overall performance in the nonoverlapping data window approach gave a mean error (bias) of 1.0 mm Hg, standard deviation of the error (precision) of 5.1 mm Hg, and root-mean-square error of 5.2 mm Hg. The associated mean and median absolute errors were 4.2 mm Hg and 3.3 mm Hg, respectively. These results were contingent on ensuring adequate ABP and CBFV signal quality and required accurate hydrostatic pressure correction of the measured ABP waveform in relation to the elevation of the external auditory meatus. Notably, the procedure had no failed attempts at data collection, and all patients had adequate TCD data from at least one hemisphere. Last, an analysis of using study-by-study averaged nICP estimates to detect a measured ICP > 15 mm Hg resulted in an area under the receiver operating characteristic curve of 0.83, with a sensitivity of 71% and specificity of 86% for a detection threshold of nICP = 15 mm Hg.CONCLUSIONSThis nICP estimation algorithm, based on ABP and bedside TCD CBFV waveform measurements, performs in a manner comparable to invasive ICP monitoring. These findings open the possibility for rational, point-of-care treatment decisions in pediatric patients with suspected raised ICP undergoing intensive care.


Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 51 ◽  
Author(s):  
Kaimeng Chen ◽  
Chin-Chen Chang

In this paper, a novel, real-time, error-free, reversible data hiding method for encrypted images has been proposed. Based on the (7, 4) Hamming code, we designed an efficient encoding scheme to embed secret data into the least significant bits (LSBs) of the encrypted image. For reversibility, we designed a most significant bit (MSB) prediction scheme that can recover a portion of the modified MSBs after the image is decrypted. These MSBs can be modified to accommodate the additional information that is used to recover the LSBs. After embedding the data, the original image can be recovered with no error and the secret data can be extracted from both the encrypted image and the decrypted image. The experimental results proved that compared with existing methods, the proposed method can achieve higher embedding rate, better quality of the marked image and less execution time of data embedding. Therefore, the proposed method is suitable for real-time applications in the cloud.


2018 ◽  
Vol 160 ◽  
pp. 10-19 ◽  
Author(s):  
Jian-Chuan Yin ◽  
Anastassios N. Perakis ◽  
Ning Wang

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