Search Results (14)

Quantitative electroencephalography (QEEG) has emerged as a promising tool for detecting Alzheimer’s disease (AD). Among QEEG measures, Multiscale Fuzzy Entropy (MFE) shows great potential in identifying AD-related changes in EEG complexity. However, MFE is intrinsically linked to signal amplitude, which can vary substantially among EEG systems, and this hinders the adoption of this metric for AD detection. To overcome this issue, this study investigates different preprocessing strategies to make the calculation of MFE less dependent on the specific amplitude characteristics of the EEG signals at hand. This contributes to generalizing and making more robust the adoption of MFE for AD detection. To demonstrate the robustness of the proposed preprocessing methods, binary classification tasks with Support Vector Machines (SVMs), Random Forest (RF), and K-Nearest Neighbor (KNN) classifiers are used. Performance metrics, such as classification accuracy and Matthews Correlation Coefficient (MCC), are employed to assess the results. The methodology is validated on two public EEG datasets. Results show that amplitude transformation, particularly normalization, significantly enhances AD detection, achieving mean classification accuracy values exceeding 80% with an uncertainty of 10% across all classifiers. These results highlight the importance of preprocessing in improving the accuracy and the reliability of EEG-based AD diagnostic tools, offering potential advancements in patient management and treatment planning. Full article

Pulse oximetry is essential for monitoring arterial oxygen saturation ($Sp{O}_2$) and heart rate (HR) in various medical scenarios. However, the traditional pulse oximeters face challenges related to high costs, motion artifacts, and susceptibility to ambient light interference. This work presents a low-cost experimental pulse oximeter prototype designed to address these limitations through design advancements. The device incorporates a 3D-printed finger support to minimize motion artifacts and excessive capillary pressure, along with an elastic element to enhance stability. Unlike conventional transmission-based oximetry, the prototype employs a reflectance-based measurement approach, improving versatility and enabling reliable readings even in cases of poor peripheral perfusion. Additionally, the integration of light-shielding materials mitigates the effects of ambient illumination, ensuring accurate operation in challenging environments such as surgical settings. Metrological characterization demonstrates that the prototype achieves accuracy comparable to that of the commercial GIMA Oxy-50 pulse oximeter while maintaining a production cost at approximately one-tenth of the commercial alternatives. This study highlights the potential of the prototype to deliver affordable and reliable pulse oximetry for different applications. Full article

This study investigates the effectiveness of amplitude transformation in enhancing the performance and robustness of Multiscale Fuzzy Entropy for Alzheimer’s disease detection using electroencephalography signals. Multiscale Fuzzy Entropy is a complexity measure particularly sensitive to intra- and inter-subject variations in signal amplitude, as well as the selection of key parameters such as embedding dimension (m) and similarity criterion (r), which often result in inconsistent outcomes when applied to multivariate data, such as electroencephalography signals. To address these challenges and to generalize the possibility of adopting Multiscale Fuzzy Entropy as a diagnostic tool for Alzheimer’s disease, this research explores amplitude transformation preprocessing on electroencephalography signals in Multiscale Fuzzy Entropy calculation across varying parameters. The statistical analysis of the obtained results demonstrates that amplitude transformation preprocessing significantly enhances Multiscale Fuzzy Entropy’s ability to detect Alzheimer’s disease, achieving higher and more consistent significant comparison percentages, with an average of 73.2% across all parameter combinations, compared with only one raw data combination exceeding 65%. Clustering analysis corroborates these findings, showing that amplitude transformation improves the differentiation between Alzheimer’s disease patients and healthy subjects. These results highlight the potential of amplitude transformation to stabilize Multiscale Fuzzy Entropy performance, making it a more reliable tool for early Alzheimer’s disease detection. Full article

This study investigates the dielectric properties of conductive biocomposites (CBs), which are integral to the development of advanced materials for flexible electronics and medical devices. A novel method employing Microwave Reflectometry (MR) is introduced, utilizing a miniaturized Vector Network Analyzer (m-VNA) and a dedicated sensing element (SE), to extract the dielectric properties of CBs. The method is grounded in a minimization principle, aligning the measured $S_{11}$ reflection scattering parameter with its electromagnetic (EM) simulation, facilitating a refined process for determining the dielectric properties. The experimental setup was meticulously engineered, optimized, and validated using reference dielectric samples (RDSs) with known dielectric properties. The method was then applied to three innovative CBs, resulting in an accurate extrapolation of their dielectric properties. The findings highlight the method’s versatility, cost-efficiency, and applicability to ultra-thin and flexible biopolymer films, offering significant potential for advancements in flexible electronics and bio-sensing applications. Full article

Alzheimer’s disease (AD) is a neurodegenerative brain disorder that affects cognitive functioning and memory. Current diagnostic tools, including neuroimaging techniques and cognitive questionnaires, present limitations such as invasiveness, high costs, and subjectivity. In recent years, interest has grown in using electroencephalography (EEG) for AD detection due to its non-invasiveness, low cost, and high temporal resolution. In this regard, this work introduces a novel metric for AD detection by using multiscale fuzzy entropy (MFE) to assess brain complexity, offering clinicians an objective, cost-effective diagnostic tool to aid early intervention and patient care. To this purpose, brain entropy patterns in different frequency bands for 35 healthy subjects (HS) and 35 AD patients were investigated. Then, based on the resulting MFE values, a specific detection algorithm, able to assess brain complexity abnormalities that are typical of AD, was developed and further validated on 24 EEG test recordings. This MFE-based method achieved an accuracy of 83% in differentiating between HS and AD, with a diagnostic odds ratio of 25, and a Matthews correlation coefficient of 0.67, indicating its viability for AD diagnosis. Furthermore, the algorithm showed potential for identifying anomalies in brain complexity when tested on a subject with mild cognitive impairment (MCI), warranting further investigation in future research. Full article

Chronic endometritis (CE) is the persistent inflammation of the endometrial lining associated with infertility and various forms of reproductive failures. The diagnosis of CE is based on the histological evidence of stromal plasma cells; however, standardized methods to assess plasma cells are still lacking. In the present paper, we aimed to determine the most appropriate plasma cell threshold to diagnose CE based on pregnancy outcomes. Three electronic databases were searched from their inception to February 2022 for all studies comparing pregnancy outcomes between patients with CE and patients without CE. The relative risk (RR) of pregnancy, miscarriage, and/or live birth rates were calculated and pooled based on the plasma cell threshold adopted. A p-value < 0.05 was considered significant. Nine studies adopting different thresholds (1 to 50 plasma cells/10 HPF) were included. In the meta-analysis, we only found a significant association between miscarriage rate and a plasma cell count ≥ 5/10 HPF (RR = 2.4; p = 0.007). Among studies not suitable for meta-analysis, CE showed an association with worsened pregnancy only when high thresholds (10 and 50/10 HPF) were adopted. In conclusion, our study suggests that the presence of plasma cells at low levels (<5/10 HPF) may not predict worsened pregnancy outcomes. Based on these findings, a threshold of ≥5 plasma cells/10 HPF may be more appropriate to diagnose CE. Full article

COVID-19 is an ongoing global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although it primarily attacks the respiratory tract, inflammation can also affect the central nervous system (CNS), leading to chemo-sensory deficits such as anosmia and serious cognitive problems. Recent studies have shown a connection between COVID-19 and neurodegenerative diseases, particularly Alzheimer’s disease (AD). In fact, AD appears to exhibit neurological mechanisms of protein interactions similar to those that occur during COVID-19. Starting from these considerations, this perspective paper outlines a new approach based on the analysis of the complexity of brain signals to identify and quantify common features between COVID-19 and neurodegenerative disorders. Considering the relation between olfactory deficits, AD, and COVID-19, we present an experimental design involving olfactory tasks using multiscale fuzzy entropy (MFE) for electroencephalographic (EEG) signal analysis. Additionally, we present the open challenges and future perspectives. More specifically, the challenges are related to the lack of clinical standards regarding EEG signal entropy and public data that can be exploited in the experimental phase. Furthermore, the integration of EEG analysis with machine learning still requires further investigation. Full article

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) represents one of the most threatening viral infections in the last decade. Amongst susceptible individuals, infected pregnant women might be predisposed to severe complications. Despite the extensive interest in SARS-CoV-2 research, the clinical course of maternal infection, the vertical transmission and the neonatal outcomes have not been completely understood yet. The aim of our study was to investigate the association between SARS-CoV-2 infection, obstetric outcomes and vertical transmission. Methods: A prospective observational study was performed, enrolling unvaccinated pregnant patients positive for SARS-CoV-2 (cases) and matched with uninfected pregnant women (controls). Maternal and neonatal nasopharyngeal swabs, maternal and cord blood, amniotic fluid and placenta tissue samples were collected; blood samples were tested for anti-S and anti-N antibodies, and histologic examination of placental tissues was performed. Results: The cases showed a significant association with the development of some obstetric complications, such as intrauterine growth restriction and pregnancy-associated hypothyroidism and diabetes, as compared to controls; their newborns were more likely to have a low birth weight and an arterial umbilical pH less than 7. The viral genome was detected in maternal and cord blood and placental samples in six cases. Conclusions: Pregnant women positive for SARS-CoV-2 infection are more likely to develop severe obstetric outcomes; their newborns could have a low birth weight and arterial pH. Vertical transmission seems a rare event, and further investigation is strongly needed. Full article

The problem of water scarcity affects many areas of the world due to water mismanagement and overconsumption and, more recently, to climate change. Monitoring the integrity of distribution systems is, therefore, increasingly important to avoid the waste of clean water. This paper presents a new signal processing technique for enhancing the performance of the methodology of leak detection in water distribution pipes based on time domain reflectometry (TDR). The new technique is based on a particular kind of TDR inversion (spatial TDR) based on a “gray-box” lumped parameter model of the system. The model does not include, e.g., radiative phenomena, non-TEM (transverse electromagnetic) modes etc. but is capable of reproducing accurately the complicated reflectograms obtained by a TDR leak detection system assuming a proper profile of capacitance per unit length along the sensing element. Even more importantly, the model is identified using only the reflectograms taken by the system with very little prior information about the system components. The developed technique is able to estimate with good accuracy, from reflectograms with unclear or ambiguous interpretation, the position and the extension of a region where water is located. The measurement is obtained without prior electromagnetic characterization of the TDR system components and without the need of modeling or quantifying a number of electromagnetic effects typical of on-site measurements. Full article

Background: Congenital heart diseases (CHDs) are often associated with significant neurocognitive impairment and neurological delay. This study aims to elucidate the correlation between type of CHD and Doppler velocimetry and to investigate the possible presence of fetal brain abnormalities identified by magnetic resonance imaging (MRI). Methods: From July 2010 to July 2020, we carried out a cross-sectional study of 63 singleton pregnancies with a diagnosis of different types of complex CHD: LSOL (left-sided obstructive lesions; RSOL (right-sided obstructive lesions) and MTC (mixed type of CHD). All patients underwent fetal echocardiography, ultrasound evaluation, a magnetic resonance of the fetal brain, and genetic counseling. Results: The analysis of 63 fetuses shows statistically significant results in Doppler velocimetry among the different CHD groups. The RSOL group leads to higher umbilical artery (UA-PI) pressure indexes values, whereas the LSOL group correlates with significantly lower values of the middle cerebral artery (MCA-PI) compared to the other subgroups (p = 0.036), whereas the RSOL group shows a tendency to higher pulsatility indexes in the umbilical artery (UA-PI). A significant correlation has been found between a reduced head circumference (HC) and the presence of brain injury at MRI (p = 0.003). Conclusions: Congenital left- and right-sided cardiac obstructive lesions are responsible for fetal hemodynamic changes and brain growth impairment. The correct evaluation of the central nervous system (CNS) in fetuses affected by CHD could be essential as prenatal screening and the prediction of postnatal abnormalities. Full article

The aim of this work is to propose two different and integrated sensors for the structural health monitoring of concrete beams. In particular, a diffused sensing element and a split ring resonator network are presented. The first sensor is able to detect the variations in the dielectric properties of the concrete along the whole beam length, for a diffuse monitoring both during the important concrete curing phase and also for the entire life cycle of the concrete beams. The resonators instead work punctually, in their surroundings, allowing an accurate evaluation of the permittivity both during the drying phase and after. This allows the continuous monitoring of any presence of water both inside the concrete beam and at points that can be critical, in the case of beams in dams, bridges or in any case subject to a strong presence of water which could lead to deterioration, or worse, cause serious accidents. Moreover, the punctual sensors are able to detect the presence of cracks in the structure and to localize them. Full article

The human sense of smell is important for many vital functions, but with the current state of the art, there is a lack of objective and non-invasive methods for smell disorder diagnostics. In recent years, increasing attention is being paid to olfactory event-related potentials (OERPs) of the brain, as a viable tool for the objective assessment of olfactory dysfunctions. The aim of this review is to describe the main features of OERPs signals, the most widely used recording and processing techniques, and the scientific progress and relevance in the use of OERPs in many important application fields. In particular, the innovative role of OERPs is exploited in olfactory disorders that can influence emotions and personality or can be potential indicators of the onset or progression of neurological disorders. For all these reasons, this review presents and analyzes the latest scientific results and future challenges in the use of OERPs signals as an attractive solution for the objective monitoring technique of olfactory disorders. Full article

Background: Neurogenic bowel dysfunction (NBD) indicates bowel dysfunction due to a lack of nervous control after a central nervous system lesion. Bowel symptoms, such as difficulties with evacuation, constipation, abdominal pain and swelling, are experienced commonly among individuals with spinal cord injury (SCI). Consequentially, individuals with SCI experience a general dissatisfaction with the lower perceived quality of life (QoL). Several studies have demonstrated the positive effects of manual therapies on NBD, including Osteopathic Manipulative Treatment (OMT). This study aimed to explore OMT effects on NBD in individuals with SCI compared with Manual Placebo Treatment (MPT). Methods: The study was a double-blind randomized controlled trial composed of three phases, each one lasting 30 days (i: NBD/drugs monitoring; ii: four OMT/MPT sessions; iii: NBD/drug monitoring and follow-up evaluation). Results: the NBD scale, the QoL on worries and concerns sub-questionnaire, and the perception of abdominal swelling and constipation significantly improved after treatments compared to baseline only for individuals who underwent OMT. Conclusion: These preliminary results showed positive effects of OMT on bowel function and QoL in individuals with SCI, but further studies are needed to confirm our results. Full article

This work presents a microwave reflectometry-based system for monitoring large concrete structures (during the curing process and also while the structure is in use), through the combined use of punctual and diffused sensing elements. In particular, the adoption of punctual probes on a reference concrete specimen allows the development of an innovative and accurate calibration procedure, useful to obtain the value of the water content on a larger structure made of the same material. Additionally, a wire-like diffused sensing element can be permanently embedded in buildings and used to monitor the structure along the entire length of the sensing element. The adopted diffused sensing element can be used not only to detect dielectric variation during the curing process, but also throughout the service life of the structure. The combined use of punctual and diffused sensing elements represents an important innovation from a procedural point of view, able to provide detailed and quantitative information on the health status of the structure both during and after construction. Full article