Infrared Thermography for Real-Time Assessment of the Effectiveness of Scoliosis Braces.

This work proposes an innovative method, based on the use of low-cost infrared thermography (IRT) instrumentation, to assess in real time the effectiveness of scoliosis braces. Establishing the effectiveness of scoliosis braces means deciding whether the pressure exerted by the brace on the patient's back is adequate for the intended therapeutic purpose. Traditionally, the evaluation of brace effectiveness relies on empirical, qualitative assessments carried out by orthopedists during routine follow-up examinations. Hence, it heavily depends on the expertise of the orthopedists involved. In the state of the art, the only objective methods used to confirm orthopedists' opinions are based on the evaluation of how scoliosis progresses over time, often exposing people to ionizing radiation. To address these limitations, the method proposed in this work aims to provide a real-time, objective assessment of the effectiveness of scoliosis braces in a non-harmful way. This is achieved by exploiting the thermoelastic effect and correlating temperature changes on the patient's back with the mechanical pressure exerted by the braces. A system based on this method is implemented and then validated through an experimental study on 21 patients conducted at an accredited orthopedic center. The experimental results demonstrate a classification accuracy slightly below 70% in discriminating between adequate and inadequate pressure, which is an encouraging result for further advancement in view of the clinical use of such systems in orthopedic centers.

A General Approach for the Modelling of Negative Feedback Physiological Control Systems.

Mathematical models can improve the understanding of physiological systems behaviour, which is a fundamental topic in the bioengineering field. Having a reliable model enables researchers to carry out in silico experiments, which require less time and resources compared to their in vivo and in vitro counterparts. This work's objective is to capture the characteristics that a nonlinear dynamical mathematical model should exhibit, in order to describe physiological control systems at different scales. The similarities among various negative feedback physiological systems have been investigated and a unique general framework to describe them has been proposed. Within such a framework, both the existence and stability of equilibrium points are investigated. The model here introduced is based on a closed-loop topology, on which the homeostatic process is based. Finally, to validate the model, three paradigmatic examples of physiological control systems are illustrated and discussed: the ultrasensitivity mechanism for achieving homeostasis in biomolecular circuits, the blood glucose regulation, and the neuromuscular reflex arc (also referred to as muscle stretch reflex). The results show that, by a suitable choice of the modelling functions, the dynamic evolution of the systems under study can be described through the proposed general nonlinear model. Furthermore, the analysis of the equilibrium points and dynamics of the above-mentioned systems are consistent with the literature.

Detection of Suspicious Cardiotocographic Recordings by Means of a Machine Learning Classifier.

Cardiotocography (CTG) is one of the fundamental prenatal diagnostic methods for both antepartum and intrapartum fetal surveillance. Although it has allowed a significant reduction in intrapartum and neonatal mortality and morbidity, its diagnostic accuracy is, however, still far from being fully satisfactory. In particular, the identification of uncertain and suspicious CTG traces remains a challenging task for gynecologists. The introduction of computerized analysis systems has enabled more objective evaluations, possibly leading to more accurate diagnoses. In this work, the problem of classifying suspicious CTG recordings was addressed through a machine learning approach. A machine-based labeling was proposed, and a binary classification was carried out using a support vector machine (SVM) classifier to distinguish between suspicious and normal CTG traces. The best classification metrics showed accuracy, sensitivity, and specificity values of 92%, 92%, and 90%, respectively. The main results were compared both with results obtained by considering a more unbalanced dataset and with relevant literature studies in the field. The use of the SVM proved to be promising in the field of CTG classification. However, appropriate feature selection and dataset balancing are crucial to achieve satisfactory performance of the classifier.

Feasibility of a Wearable Reflectometric System for Sensing Skin Hydration.

One of the major goals of Health 4.0 is to offer personalized care to patients, also through real-time, remote monitoring of their biomedical parameters. In this regard, wearable monitoring systems are crucial to deliver continuous appropriate care. For some biomedical parameters, there are a number of well established systems that offer adequate solutions for real-time, continuous patient monitoring. On the other hand, monitoring skin hydration still remains a challenging task. The continuous monitoring of this physiological parameter is extremely important in several contexts, for example for athletes, sick people, workers in hostile environments or for the elderly. State-of-the-art systems, however, exhibit some limitations, especially related with the possibility of continuous, real-time monitoring. Starting from these considerations, in this work, the feasibility of an innovative time-domain reflectometry (TDR)-based wearable, skin hydration sensing system for real-time, continuous monitoring of skin hydration level was investigated. The applicability of the proposed system was demonstrated, first, through experimental tests on reference substances, then, directly on human skin. The obtained results demonstrate the TDR technique and the proposed system holds unexplored potential for the aforementioned purposes.

Ocular vestibular-evoked myogenic potentials to bone-conducted vibration in superior vestibular neuritis show utricular function.

OBJECTIVE: To determine whether the first negative component (n10) of the ocular vestibular-evoked myogenic potential (oVEMP) to bone-conducted vibration (BCV) is due primarily to activation of the utricular macula. STUDY DESIGN: The n10 was recorded in response to brief BCV at the midline of the forehead at the hairline (Fz). If the n10 is due primarily to utricular activation, then diseases that affect only the superior division of the vestibular nerve in which all utricular afferents course (i.e., superior vestibular neuritis [SVN]) should reduce or eliminate n10 beneath the contralesional eye, whereas the n10 beneath the ipsilesional eye and the sacculo-collic cervical vestibular-evoked myogenic potential (cVEMP) on the ipsilesional side should be preserved. SETTING: A prospective study at a tertiary neurotological referral center. SUBJECTS AND METHODS: The n10 component of the oVEMP was measured in 133 patients with unilateral SVN but with inferior vestibular nerve function preserved, as shown by ipsilesional cVEMPs. RESULTS: The n10 to Fz BCV of 133 SVN patients was reduced beneath the contralesional eye relative to the ipsilesional eye so that there was an n10 asymmetry that was significantly greater than the n10 asymmetry in the 50 healthy subjects. In terms of predicting the affected side (shown by canal paresis), using an n10 asymmetry ratio (asymmetry ratio for the relative size of the n10 of the oVEMPs for the two eyes [AR]) of 46.5 percent, the n10 AR has a diagnostic accuracy of 94 percent. CONCLUSION: The n10 component of the oVEMP to BCV is probably mediated by the superior vestibular nerve and so mainly by the utricular receptors. The n10 AR is almost as good as canal paresis in identifying the affected side in patients.