A new approach to the spatio-temporal pattern identification in neuronal multi-electrode registrations

A lot of methods were created in last decade for the spatio-temporal analysis of multi-electrode array (MEA) neuronal data sets. All these methods were implemented starting from a channel to channel analysis, with a great computational effort and onerous spatial pattern recognition task. 
Our idea is to approach the MEA data collection from a different point of view, i.e. considering all channels simultaneously. We transform the 2D plus time MEA signal in a mono-dimensional plus time signal and elaborate it as a normal 1D signal, using the Space-Amplitude Transform method. 
This geometrical transformation is completely invertible and allows to employ very fast processing algorithms. 
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Antepartum Fetal Monitoring through a Wearable System and a Mobile Application

Prenatal monitoring of Fetal Heart Rate (FHR) is crucial for the prevention of fetal pathologies and unfavorable deliveries. However, the most commonly used Cardiotocographic exam can be performed only in hospital-like structures and requires the supervision of expert personnel. For this reason, a wearable system able to continuously monitor FHR would be a noticeable step towards a personalized and remote pregnancy care. Thanks to textile electrodes, miniaturized electronics, and smart devices like smartphones and tablets, we developed a wearable integrated system for everyday fetal monitoring during the last weeks of pregnancy. Pregnant women at home can use it without the need for any external support by clinicians. The transmission of FHR to a specialized medical center allows its remote analysis, exploiting advanced algorithms running on high-performance hardware able to obtain the best classification of the fetal condition. The system has been tested on a limited set of pregnant women whose fetal electrocardiogram recordings were acquired and classified, yielding an overall score for both accuracy and sensitivity over 90%. This novel approach can open a new perspective on the continuous monitoring of fetus development by enhancing the performance of regular examinations, making treatments really personalized, and reducing hospitalization or ambulatory visits. Keywords: tele-monitoring; wearable devices; fetal heart rate; telemedicin

Monitoring Fetal Heart Rate during Pregnancy: Contributions from Advanced Signal Processing and Wearable Technology

Monitoring procedures are the basis to evaluate the clinical state of patients and to assess changes in their conditions, thus providing necessary interventions in time. Both these two objectives can be achieved by integrating technological development with methodological tools, thus allowing accurate classification and extraction of useful diagnostic information. The paper is focused on monitoring procedures applied to fetal heart rate variability (FHRV) signals, collected during pregnancy, in order to assess fetal well-being. The use of linear time and frequency techniques as well as the computation of non linear indices can contribute to enhancing the diagnostic power and reliability of fetal monitoring. The paper shows how advanced signal processing approaches can contribute to developing new diagnostic and classification indices. Their usefulness is evaluated by comparing two selected populations: normal fetuses and intra uterine growth restricted (IUGR) fetuses. Results show that the computation of different indices on FHRV signals, either linear and nonlinear, gives helpful indications to describe pathophysiological mechanisms involved in the cardiovascular and neural system controlling the fetal heart. As a further contribution, the paper briefly describes how the introduction of wearable systems for fetal ECG recording could provide new technological solutions improving the quality and usability of prenatal monitoring. © 2014 Maria G. Signorini et al

Children, algorithm and the decimal numeral system

A large number of studies in Mathematics Education approach some possible problems in the study of algorithms in the early school years of arithmetic teaching. However, this discussion is not exhausted. In this feature, this article presents the results of a research which proposed to investigate if the arithmetic’s teaching, with emphasis in the fundamental operation’s algorithm, cooperate to build the mathematics knowledge, specifically of the Decimal Numeral System. In order to achieve this purpose, we interviewed, using the Piaget Critique Clinical Method, twenty students from a public school. The result’s analysis indicates that they mechanically reproduce the regular algorithm’s techniques without notice the relations between the techniques and the principle and the Decimal Numeral System’s properties

A NEW APPROACH TO THE SPATIO-TEMPORAL PATTERN IDENTIFICATION IN NEURONAL MULTI-ELECTRODE REGISTRATIONS

A lot of methods were created in last decade for the spatio-temporal analysis of multi-electrode array (MEA) neuronal data sets. All these methods were implemented starting from a channel to channel analysis, with a great computational effort and onerous spatial pattern recognition task. Our idea is to approach the MEA data collection from a different point of view, i.e. considering all channels simultaneously. We transform the 2D plus time MEA signal in a mono-dimensional plus time signal and elaborate it as a normal 1D signal, using the Space-Amplitude Transform method. This geometrical transformation is completely invertible and allows to employ very fast processing algorithms

A deep learning mixed-data type approach for the classification of FHR signals

The Cardiotocography (CTG) is a widely diffused monitoring practice, used in Ob-Gyn Clinic to assess the fetal well-being through the analysis of the Fetal Heart Rate (FHR) and the Uterine contraction signals. Due to the complex dynamics regulating the Fetal Heart Rate, a reliable visual interpretation of the signal is almost impossible and results in significant subjective inter and intra-observer variability. Also, the introduction of few parameters obtained from computer analysis did not solve the problem of a robust antenatal diagnosis. Hence, during the last decade, computer aided diagnosis systems, based on artificial intelligence (AI) machine learning techniques have been developed to assist medical decisions. The present work proposes a hybrid approach based on a neural architecture that receives heterogeneous data in input (a set of quantitative parameters and images) for classifying healthy and pathological fetuses. The quantitative regressors, which are known to represent different aspects of the correct development of the fetus, and thus are related to the fetal healthy status, are combined with features implicitly extracted from various representations of the FHR signal (images), in order to improve the classification performance. This is achieved by setting a neural model with two connected branches, consisting respectively of a Multi-Layer Perceptron (MLP) and a Convolutional Neural Network (CNN). The neural architecture was trained on a huge and balanced set of clinical data (14.000 CTG tracings, 7000 healthy and 7000 pathological) recorded during ambulatory non stress tests at the University Hospital Federico II, Napoli, Italy. After hyperparameters tuning and training, the neural network proposed has reached an overall accuracy of 80.1%, which is a promising result, as it has been obtained on a huge dataset

Entropy Information of Cardiorespiratory Dynamics in Neonates during Sleep

Abstract: Sleep is a central activity in human adults and characterizes most of the newborn infant life. During sleep, autonomic control acts to modulate heart rate variability (HRV) and respiration. Mechanisms underlying cardiorespiratory interactions in different sleep states have been studied but are not yet fully understood. Signal processing approaches have focused on cardiorespiratory analysis to elucidate this co-regulation. This manuscript proposes to analyze heart rate (HR), respiratory variability and their interrelationship in newborn infants to characterize cardiorespiratory interactions in different sleep states (active vs. quiet). We are searching for indices that could detect regulation alteration or malfunction, potentially leading to infant distress. We have analyzed inter-beat (RR) interval series and respiration in a population of 151 newborns, and followed up with 33 at 1 month of age. RR interval series were obtained by recognizing peaks of the QRS complex in the electrocardiogram (ECG), corresponding to the ventricles depolarization. Univariate time domain, frequency domain and entropy measures were applied. In addition, Transfer Entropy was considered as a bivariate approach able to quantify the bidirectional information flow from one signal (respiration) to another (RR series). Results confirm the validity of the proposed approach. Overall, HRV is higher in active sleep, while high frequency (HF) power characterizes more quiet sleep. Entropy analysis provides higher indices for SampEn and Quadratic Sample entropy (QSE) in quiet sleep. Transfer Entropy values were higher in quiet sleep and point to a major influence of respiration on the RR series. At 1 month of age, time domain parameters show an increase in HR and a decrease in variability. No entropy differences were found across ages. The parameters employed in this study help to quantify the potential for infants to adapt their cardiorespiratory responses as they mature. Thus, they could be useful as early markers of risk for infant cardiorespiratory vulnerabilities

Traditional knowledge on ethno-veterinary and fodder plants in South Angola: an ethnobotanic field survey in Mopane woodlands in Bibala, Namibe province

Livestock is a critical resource to improve income and household livelihoods in many rural areas. To date, very few studies have investigated farmers’ local knowledge on plants used in managing animal health and welfare in Angolan Mopane woodland. This is a very dry ecosystem where animal husbandry (mostly cattle and goats breeding) is highly widespread and is often the main form of subsidence, greatly contributing to local communities food security, especially in periods of resources shortage. An ethnobotanical research project was carried out in Bibala (Namibe province – Angola) in 2010 – 2012, in order to collect information on different traditional uses of plants, involving an interviewed sample of 66 informants. Fifty-eight of them (87.9%) listed a total of 39 species used as ethno-veterinary and/or fodder plants. Ten ethno-veterinary species (28 citations) were reported by 20 informants as used to treat diseases commonly affecting animals in the studied area, namely respiratory tract problems (Laphangium luteoalbum, Gyrocarpus americanus, Craibia brevicaudata subsp. baptistarum, Lepisanthes senegalensis, Ptaeroxylon obliquum, Ximenia americana) and skin diseases and wounds (Aloe littoralis, Blepharis sp., Ficus thonningii), or acting as a general tonic (Faidherbia albida). Thirty-four plants (235 citations) were cited by 58 informants as fodder. In this category of use, the most cited species were Terminalia prunioides (30 citations), Faidherbia albida (28 citations) and Spirostachys africana (21 citations). Our study shows that communities living in South Angola Mopane woodlands still retain a valuable traditional knowledge about plants used to maintain animal health and welfare. This body of knowledge and related skills can play a crucial role in the resilience of livestock systems facing present environmental and socioeconomic changes

Influence of Gestational Diabetes on Fetal Heart Rate in Antepartum Cardiotocographic Recordings

In pregnancy, diabetes is known to increase the risk of adverse maternal and neonatal outcomes. It would be beneficial to find techniques that allow early investigation of the physio-pathological mechanisms involved to provide clinicians with tools for prevention and therapies. For that, cardiotocography (CTG) is a promising tool. However, the evidence is still scarce and the impact on clinical practice little. In this study, we aim at characterizing the changes induced by gestational diabetes (GDM) on the fetal heart rate series. To do so, we performed a retrospective cohort study on a CTG dataset containing more than 20000 recordings of which 852 belong to 301 GDM-diagnosed patients. We divided the recordings by gestational age (G.A.) into 4 groups (weeks: 31-35, 36, 37, 38 to delivery) and for each we identified a control population of equal size matched by comorbidities. We analyzed a comprehensive set of parameters from the time domain, frequency domain and non-linear analysis and assessed variations in median values on each feature. For all G.A. below the 38th week, we found a significant increase in the power in the movement frequency band (p<0.01) and an increase in the absolute value of Deceleration Reserve (p<0.01) in GDM vs control. Other significant values were also identified and are discussed in more detail in the paper

Violência contra o idoso: suportes legais para a intervenção

The intent of this paper is to discuss the abuse of elders. The analysis of this complex issue is based upon both Brazilian and international studies. Subsequently we discuss some of the difficulties usually faced by professionals working with elder abuse in Brazil. We also present Brazilian legal documents which support the action of professionals aiming to reduce such violence. We believe that mental health and human rights are connected. In order to promote the former, we need to ensure the latter.Keywords: family violence; elder abuse; human rights.Este artigo tem como objetivo abordar a questão da violência contra idosos. A complexidade da questão é analisada com base em levantamento bibliográfico de trabalhos nacionais e internacionais. A seguir, são discutidas algumas das dificuldades enfrentadas pelos profissionais que trabalham com a violência contra o idoso, no Brasil. Também apresentamos os documentos legais que sustentam a ação de profissionais que visam a redução das diversas formas de violência enfrentadas na terceira idade. Saúde mental e direitos humanos são temas conexos, e para promover a saúde é preciso assegurar os direitos da pessoa idosa.Palavras-chave: violência familiar; violência contra o idoso; direitos humanos