scholarly journals Fully automated, real-time, calibration-free, continuous noninvasive estimation of intracranial pressure in children

2019 ◽  
Vol 24 (5) ◽  
pp. 509-519 ◽  
Author(s):  
Andrea Fanelli ◽  
Frederick W. Vonberg ◽  
Kerri L. LaRovere ◽  
Brian K. Walsh ◽  
Edward R. Smith ◽  
...  
Keyword(s):  
Intracranial Pressure ◽  
Data Collection ◽  
Real Time ◽  
Signal Quality ◽  
Icp Monitoring ◽  
Data Window ◽  
Arterial Blood ◽  
Time Calibration ◽  
Calibration Free ◽  
Data Windows

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.

scholarly journals Real-time non-invasive intracranial state estimation using unscented Kalman filter

2018 ◽  
Author(s):  
Chanki Park ◽  
Seungjun Ryu ◽  
Bonghyun Jung ◽  
Sangpyong Lee ◽  
Changkie Hong ◽  
...  
Keyword(s):  
Real Time ◽  
Unscented Kalman Filter ◽  
Transcranial Doppler Ultrasound ◽  
Ultrasound Measurement ◽  
Icp Monitoring ◽  
Non Invasive ◽  
Severance Hospital ◽  
Arterial Blood ◽  
Clinical Conditions ◽  
Increased Icp

AbstractIntracranial pressure (ICP) monitoring is desirable as a first-line measure to assist decision-making in cases of increased ICP. Clinically, non-invasive ICP monitoring is also required to avoid infection and hemorrhage in patients. The relationships among the arterial blood pressure (Pa), ICP, cerebral blood flow, and its velocity (QCBFv) measured by transcranial Doppler ultrasound measurement have been reported. However, real-time non-invasive ICP estimation using these modalities is less well documented. Here, we present a novel algorithm for real-time and non-invasive ICP monitoring with QCBFv and Pa, called direct-current (DC)-ICP. This technique is compared with invasive ICP for 11 traumatic-brain-injury patients admitted to Cheju Halla Hospital and Gangnam Severance Hospital from July 2017 to June 2018. The inter-subject correlation coefficient between true and estimate was 0.70. The AUCs of the ROCs for prediction of increased ICP for the DC-ICP methods are 0.816. Thus, QCBFv monitoring can facilitate reliable real-time ICP tracking with our novel DC-ICP algorithm, which can provide valuable information under clinical conditions.

scholarly journals WiFi-Based Real-Time Calibration-Free Passive Human Motion Detection

Sensors ◽  
2015 ◽  
Vol 15 (12) ◽  
pp. 32213-32229 ◽  
Author(s):  
Liangyi Gong ◽  
Wu Yang ◽  
Dapeng Man ◽  
Guozhong Dong ◽  
Miao Yu ◽  
...  
Keyword(s):  
Real Time ◽  
Motion Detection ◽  
Human Motion ◽  
Human Motion Detection ◽  
Time Calibration ◽  
Calibration Free

Real-time calibration-free C-scan images of the eye fundus using Master Slave swept source optical coherence tomography

2015 ◽  
Author(s):  
Adrian Bradu ◽  
Konstantin Kapinchev ◽  
Fred Barnes ◽  
David F. Garway-Heath ◽  
Ranjan Rajendram ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Real Time ◽  
Optical Coherence ◽  
Swept Source ◽  
Time Calibration ◽  
Calibration Free

Enhancing Clinical Supervision Using High-Definition Real-Time Digital Recording, Annotation, and Bluetooth Technology

2019 ◽  
Vol 4 (2) ◽  
pp. 356-362
Author(s):  
Jennifer W. Means ◽  
Casey McCaffrey
Keyword(s):  
Graduate Students ◽  
Data Collection ◽  
Real Time ◽  
Clinical Supervision ◽  
Video Recording ◽  
Advanced Technology ◽  
High Definition ◽  
Recording Technology ◽  
Self Confidence ◽  
Additional Data Collection

Purpose The use of real-time recording technology for clinical instruction allows student clinicians to more easily collect data, self-reflect, and move toward independence as supervisors continue to provide continuation of supportive methods. This article discusses how the use of high-definition real-time recording, Bluetooth technology, and embedded annotation may enhance the supervisory process. It also reports results of graduate students' perception of the benefits and satisfaction with the types of technology used. Method Survey data were collected from graduate students about their use and perceived benefits of advanced technology to support supervision during their 1st clinical experience. Results Survey results indicate that students found the use of their video recordings useful for self-evaluation, data collection, and therapy preparation. The students also perceived an increase in self-confidence through the use of the Bluetooth headsets as their supervisors could provide guidance and encouragement without interrupting the flow of their therapy sessions by entering the room to redirect them. Conclusions The use of video recording technology can provide opportunities for students to review: videos of prospective clients they will be treating, their treatment videos for self-assessment purposes, and for additional data collection. Bluetooth technology provides immediate communication between the clinical educator and the student. Students reported that the result of that communication can improve their self-confidence, perceived performance, and subsequent shift toward independence.

scholarly journals DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Suppawong Tuarob ◽  
Poom Wettayakorn ◽  
Ponpat Phetchai ◽  
Siripong Traivijitkhun ◽  
Sunghoon Lim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Data Collection ◽  
Stock Market ◽  
Real Time ◽  
Stock Prices ◽  
Contextual Information ◽  
Online News ◽  
Stock Prediction ◽  
Stock Market Prediction

AbstractThe explosion of online information with the recent advent of digital technology in information processing, information storing, information sharing, natural language processing, and text mining techniques has enabled stock investors to uncover market movement and volatility from heterogeneous content. For example, a typical stock market investor reads the news, explores market sentiment, and analyzes technical details in order to make a sound decision prior to purchasing or selling a particular company’s stock. However, capturing a dynamic stock market trend is challenging owing to high fluctuation and the non-stationary nature of the stock market. Although existing studies have attempted to enhance stock prediction, few have provided a complete decision-support system for investors to retrieve real-time data from multiple sources and extract insightful information for sound decision-making. To address the above challenge, we propose a unified solution for data collection, analysis, and visualization in real-time stock market prediction to retrieve and process relevant financial data from news articles, social media, and company technical information. We aim to provide not only useful information for stock investors but also meaningful visualization that enables investors to effectively interpret storyline events affecting stock prices. Specifically, we utilize an ensemble stacking of diversified machine-learning-based estimators and innovative contextual feature engineering to predict the next day’s stock prices. Experiment results show that our proposed stock forecasting method outperforms a traditional baseline with an average mean absolute percentage error of 0.93. Our findings confirm that leveraging an ensemble scheme of machine learning methods with contextual information improves stock prediction performance. Finally, our study could be further extended to a wide variety of innovative financial applications that seek to incorporate external insight from contextual information such as large-scale online news articles and social media data.

scholarly journals Quantifying the contribution of intracranial pressure and arterial blood pressure to spontaneous tympanic membrane displacement

2018 ◽  
Vol 39 (8) ◽  
pp. 085002
Author(s):  
Wahbi K El-Bouri ◽  
Dario Vignali ◽  
Konstantina Iliadi ◽  
Diederik Bulters ◽  
Robert J Marchbanks ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Intracranial Pressure ◽  
Tympanic Membrane ◽  
Arterial Blood Pressure ◽  
Arterial Blood ◽  
Membrane Displacement

The effects of mass-induced intracranial pressures on arterial hypertension and survival in awake cats

1972 ◽  
Vol 37 (5) ◽  
pp. 514-527 ◽  
Author(s):  
Stanley J. Goodman ◽  
Donald P. Becker ◽  
John Seelig
Keyword(s):  
Intracranial Pressure ◽  
Systemic Hypertension ◽  
Content Type ◽  
Arterial Blood ◽  
Mass Size ◽  
Intracranial Pressures ◽  
Relationship Of ◽  
The Relationship ◽  
Awake Cats ◽  
Supratentorial Mass

✓ Intracranial pressures above and below the tentorium, arterial blood pressure, heart rate, and respiratory rate were recorded continuously before, during, and after expansion of a supratentorial mass in awake unsedated cats. In general, as the mass enlarged, the intracranial pressure rose; however, considerable variation was observed among animals with respect to specific mass size and associated intracranial pressures. There was considerable variation in the relationship of supratentorial pressure to infratentorial pressure. No animal survived that had sustained a mass-induced pressure exceeding 1100 mm H2O, and survival was shorter with greater pressures. Systemic hypertension occurred always and only when the infratentorial pressure exceeded 600 mm H2O, regardless of the magnitude of the associated supratentorial intracranial pressure. The methodological limitations of previous studies of mass-induced intracranial hypertension appear to have been substantially reduced by the technique described.

Sign in / Sign up

Export Citation Format

Share Document