Real-Time Noninvasive Intracranial State Estimation Using Unscented Kalman Filter

Park, Chanki; Ryu, Seung Jun; Jeong, Bong Hyun; Lee, Sang Pyung; Hong, Chang-Ki; Kim, Yong Bae; Lee, Boreom

doi:10.1109/tnsre.2019.2932273

Cited by 6 publications

(7 citation statements)

References 47 publications

(62 reference statements)

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“…There are many potential routes for analyzing an ICP signal, as evidenced by published studies (Hornero et al 2005, Hornero et al 2007, Hu et al 2007, Holm and Eide 2008, Hu et al 2008a, Eide et al 2012, Santamarta et al 2012, Calisto et al 2012, García et al 2013, Xu et al 2013, Lee et al 2015, García et al 2018, Megjhani et al 2019, Park et al 2019, Hüser et al 2020. Among these approaches, one particular area worth further investigation is the characterization of the ICP pulse waveform.…”

Section: Introductionmentioning

confidence: 99%

Patient-adaptable intracranial pressure morphology analysis using a probabilistic model-based approach

Rashidinejad¹,

Hu²,

Russell³

2020

Physiol. Meas.

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Objective.-We present a framework for analyzing the intracranial pressure (ICP) morphology. Analyzing ICP signals is challenging due to the non-linear and non-Gaussian characteristics of the signal dynamics, inevitable corruption with noise and artifacts, and variations in the ICP pulse morphology among individuals with different neurological conditions. Existing frameworks make unrealistic assumptions regarding ICP dynamics and are not tuned for individual patients.Approach.-We propose a dynamic Bayesian network (DBN) for automated detection of three major ICP pulsatile components. The proposed model captures the non-linear and non-Gaussian dynamics of the ICP morphology and further adapts to a patient as the individual's ICP measurements are received. To make the approach more robust, we leverage evidence reversal and present an inference algorithm to obtain the posterior distribution over the locations of pulsatile components.Results.-We evaluate our approach on a dataset with over 700 hours of recordings from 66 neurological patients, where the pulsatile components have been annotated in prior studies. The algorithm obtains an accuracy of 96.56%, 92.39%, and 94.04% for detecting each pulsatile component on the test set, showing significant improvements over existing approaches.Significance.-Continuous ICP monitoring is essential in guiding the treatment of neurological conditions such as traumatic brain injuries. An automated approach for ICP morphology analysis takes a step toward enhancing patient care with minimal supervision. Compared to previous methods, our framework offers several advantages. It learns the parameters that model each patient's ICP in an unsupervised manner, resulting in an accurate morphology analysis. The Bayesian model-based framework provides uncertainty estimates and reveals interesting facts about ICP dynamics. The framework can be readily applied to replace existing morphological analysis methods and support the application of ICP pulse morphological features to aid the

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Section: Introductionmentioning

confidence: 99%

Patient-adaptable intracranial pressure morphology analysis using a probabilistic model-based approach

Rashidinejad¹,

Hu²,

Russell³

2020

Physiol. Meas.

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“…where a and b are coefficients that must be estimated from the sample data. A large number of publications have attempted to estimate the value of the regression coefficients and apply their findings to the problem of noninvasive ICP estimation [124][125][126][127][128][129][130][131][132][133][134][135][136][137][138]. A summary of such publications is provided in Table 4.…”

Section: Pi-based Methodsmentioning

confidence: 99%

“…Due to the somewhat complicated interplay between ICP, arterial pressure, and cerebral hemodynamics, a large number of methods have attempted to incorporate arterial pressure measurements, which may provide complementary information to assist in measuring ICP [125,154,155,[157][158][159][160][161][162][163][169][170][171][172][173][174][175]. These methods are not technically noninvasive as they require the placement of a radial artery catheter for monitoring ABP; however, this procedure is typically already performed as part of standard care in neurointesive care units, and the risks associated with monitoring ABP via radial artery catheter are considered significantly less risky than invasive ICP monitoring.…”

Section: Model-based Methodsmentioning

confidence: 99%

“…To solve these issues, a follow-up study was conducted which employed an unscented Kalman filter to perform adaptive internal state estimation and validated the method on 11 TBI patients, obtaining a bias of 0.21 mm Hg and SDE of 3.52 mm Hg, which compared favorably relative to the Kashif model and the PI-based method [125]. These theory-based models may appear more attractive in that they are physiologically motivated rather than just the result of fitting some algorithmic model; however, the consequence of this approach is that they must contend with deciphering the complex dynamics of the cerebral vasculature.…”

Section: Model-based Methodsmentioning

confidence: 99%

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Review: pathophysiology of intracranial hypertension and noninvasive intracranial pressure monitoring

Canac

Jalaleddini

Thorpe

et al. 2020

Fluids Barriers CNS

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Measurement of intracranial pressure (ICP) is crucial in the management of many neurological conditions. However, due to the invasiveness, high cost, and required expertise of available ICP monitoring techniques, many patients who could benefit from ICP monitoring do not receive it. As a result, there has been a substantial effort to explore and develop novel noninvasive ICP monitoring techniques to improve the overall clinical care of patients who may be suffering from ICP disorders. This review attempts to summarize the general pathophysiology of ICP, discuss the importance and current state of ICP monitoring, and describe the many methods that have been proposed for noninvasive ICP monitoring. These noninvasive methods can be broken down into four major categories: fluid dynamic, otic, ophthalmic, and electrophysiologic. Each category is discussed in detail along with its associated techniques and their advantages, disadvantages, and reported accuracy. A particular emphasis in this review will be dedicated to methods based on the use of transcranial Doppler ultrasound. At present, it appears that the available noninvasive methods are either not sufficiently accurate, reliable, or robust enough for widespread clinical adoption or require additional independent validation. However, several methods appear promising and through additional study and clinical validation, could eventually make their way into clinical practice.

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“…A retrospective evaluation found a moderate correlation (r = 0.51) between the ICP and non-invasive ICP, calculated using the middle cerebral artery blood flow velocity and arterial blood pressure [ 82 ]. An algorithm based on an unscented Kalman filter (using arterial blood pressure, and cerebral blood flow and velocity measured by TCD) demonstrated an improved correlation (r = 0.75) [ 83 ].…”

Section: Approaches Of Non-invasive Measurementsmentioning

confidence: 99%

Non-Invasive Intracranial Pressure Monitoring

Müller

Henkes

Gounis³

et al. 2023

JCM

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(1) Background: Intracranial pressure (ICP) monitoring plays a key role in the treatment of patients in intensive care units, as well as during long-term surgeries and interventions. The gold standard is invasive measurement and monitoring via ventricular drainage or a parenchymal probe. In recent decades, numerous methods for non-invasive measurement have been evaluated but none have become established in routine clinical practice. The aim of this study was to reflect on the current state of research and shed light on relevant techniques for future clinical application. (2) Methods: We performed a PubMed search for “non-invasive AND ICP AND (measurement OR monitoring)” and identified 306 results. On the basis of these search results, we conducted an in-depth source analysis to identify additional methods. Studies were analyzed for design, patient type (e.g., infants, adults, and shunt patients), statistical evaluation (correlation, accuracy, and reliability), number of included measurements, and statistical assessment of accuracy and reliability. (3) Results: MRI-ICP and two-depth Doppler showed the most potential (and were the most complex methods). Tympanic membrane temperature, diffuse correlation spectroscopy, natural resonance frequency, and retinal vein approaches were also promising. (4) Conclusions: To date, no convincing evidence supports the use of a particular method for non-invasive intracranial pressure measurement. However, many new approaches are under development.

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Real-Time Noninvasive Intracranial State Estimation Using Unscented Kalman Filter

Cited by 6 publications

References 47 publications

Patient-adaptable intracranial pressure morphology analysis using a probabilistic model-based approach

Patient-adaptable intracranial pressure morphology analysis using a probabilistic model-based approach

Review: pathophysiology of intracranial hypertension and noninvasive intracranial pressure monitoring

Non-Invasive Intracranial Pressure Monitoring

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