Artificial Intelligence-Driven Prognosis of Respiratory Mechanics: Forecasting Tissue Hysteresivity Using Long Short-Term Memory and Continuous Sensor Data.

Tissue hysteresivity is an important marker for determining the onset and progression of respiratory diseases, calculated from forced oscillation lung function test data. This study aims to reduce the number and duration of required measurements by combining multivariate data from various sensing devices. We propose using the Forced Oscillation Technique (FOT) lung function test in both a low-frequency prototype and the commercial RESMON device, combined with continuous monitoring from the Equivital (EQV) LifeMonitor and processed by artificial intelligence (AI) algorithms.

Development, Validation, and Comparison of a Novel Nociception/Anti-Nociception Monitor against Two Commercial Monitors in General Anesthesia.

In this paper, we present the development and the validation of a novel index of nociception/anti-nociception (N/AN) based on skin impedance measurement in time and frequency domain with our prototype AnspecPro device. The primary objective of the study was to compare the Anspec-PRO device with two other commercial devices (Medasense, Medstorm). This comparison was designed to be conducted under the same conditions for the three devices.

Parametric Modeling and Deep Learning for Enhancing Pain Assessment in Postanesthesia.

Objective: The problem of reliable and widely accepted measures of pain is still open. It follows the objective of this work as pain estimation through post-surgical trauma modeling and classification, to increase the needed reliability compared to measurements only.

Methods: This article proposes (i) a recursive identification method to obtain the frequency response and parameterization using fractional-order impedance models (FOIM), and (ii) deep learning with convolutional neural networks (CNN) classification algorithms using time-frequency data and spectrograms.

Lumped Parametric Model for Skin Impedance Data in Patients with Postoperative Pain.

The societal and economic burden of unassessed and unmodeled postoperative pain is high and predicted to rise over the next decade, leading to over-dosing as a result of subjective (NRS-based) over-estimation by the patient. This study identifies how post-surgical trauma alters the parameters of impedance models, to detect and examine acute pain variability. Model identification is performed on clinical data captured from post-anesthetized patients, using Anspec-PRO prototype apriori validated for clinical pain assessment.

Revisiting Ziegler-Nichols. A fractional order approach.

PID controllers are largely used in industry. Auto-tuning methods for these controllers have emerged over the years, including the well-known Ziegler-Nichols method. Several extensions and improvements to this early autotuning method have been proposed throughout the years.

A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques.

The present manuscript aims at raising awareness of the endless possibilities of fractional calculus applied not only to system identification and control engineering, but also into sensing and filtering domains. The creation of the device has enabled the physical realization of a new array of sensors capable of gathering more information. The same fractional-order electronic component has led to the possibility of exploring analog filtering techniques from a practical perspective, enlarging the horizon to a wider frequency range, with increased robustness to component variation, stability and noise reduction.

Bioimpedance Sensor and Methodology for Acute Pain Monitoring.

The paper aims to revive the interest in bioimpedance analysis for pain studies in communicating and non-communicating (anesthetized) individuals for monitoring purpose. The plea for exploitation of full potential offered by the complex (bio)impedance measurement is emphasized through theoretical and experimental analysis. A non-invasive, low-cost reliable sensor to measure skin impedance is designed with off-the-shelf components.

Event-based fractional order control.

The present study provides a generalization of event-based control to the field of fractional calculus, combining the benefits brought by the two approaches into an industrial-suitable control strategy. During recent years, control applications based on fractional order differintegral operators have gained more popularity due to their proven superior performance when compared to classical, integer order, control strategies. However, the current industrial setting is not yet prepared to fully adapt to complex fractional order control implementations that require hefty computational resources; needing highly-efficient methods with minimum control effort.

Robust fractional-order auto-tuning for highly-coupled MIMO systems.

Many processes in industry are highly-coupled Multiple-Input Multiple-Output (MIMO) systems. In this paper, a methodology, based on the (KC) tuning method, is proposed to tune a fractional-order PI controller for these types of systems. The KC method relies on frequency domain specifications and emphasizes improving robustness.

An efficient algorithm for low-order direct discrete-time implementation of fractional order transfer functions.

Fractional order systems become increasingly popular due to their versatility in modelling and control applications across various disciplines. However, the bottleneck in deploying these tools in practice is related to their implementation on real-life systems. Numerical approximations are employed but their complexity no longer match the attractive simplicity of the original fractional order systems.

A novel auto-tuning method for fractional order PI/PD controllers.

Fractional order PID controllers benefit from an increasing amount of interest from the research community due to their proven advantages. The classical tuning approach for these controllers is based on specifying a certain gain crossover frequency, a phase margin and a robustness to gain variations. To tune the fractional order controllers, the modulus, phase and phase slope of the process at the imposed gain crossover frequency are required.

Podocyte-specific GLUT4-deficient mice have fewer and larger podocytes and are protected from diabetic nephropathy.

Podocytes are a major component of the glomerular filtration barrier, and their ability to sense insulin is essential to prevent proteinuria. Here we identify the insulin downstream effector GLUT4 as a key modulator of podocyte function in diabetic nephropathy (DN). Mice with a podocyte-specific deletion of GLUT4 (G4 KO) did not develop albuminuria despite having larger and fewer podocytes than wild-type (WT) mice.

Inferior mesentericocaval shunt--an efficient therapeutical alternative in Budd Chiari syndrome associated with portal and splenic vein thrombosis in a teenager.

The authors present the case of a 17 year old girl admitted to hospital for poor general state, mild scleral jaundice, deficient nutritional state, oliguria and massive ascites. She was diagnosed with Budd-Chiari syndrome: thrombosis of the left suprahepatic vein and nonocclusive thrombosis of the inferior vena cava at the level of the 12th thoracal and the lumbar vertebrae. The specific feature of the case was the association of portal and splenic vein thrombosis.