A Bio-Inspired Endogenous Attention-Based Architecture for a Social Robot.

A robust perception system is crucial for natural human-robot interaction. An essential capability of these systems is to provide a rich representation of the robot's environment, typically using multiple sensory sources. Moreover, this information allows the robot to react to both external stimuli and user responses. The novel contribution of this paper is the development of a perception architecture, which was based on the bio-inspired concept of endogenous attention being integrated into a real social robot. In this paper, the architecture is defined at a theoretical level to provide insights into the underlying bio-inspired mechanisms and at a practical level to integrate and test the architecture within the complete architecture of a robot. We also defined mechanisms to establish the most salient stimulus for the detection or task in question. Furthermore, the attention-based architecture uses information from the robot's decision-making system to produce user responses and robot decisions. Finally, this paper also presents the preliminary test results from the integration of this architecture into a real social robot.

A Bio-inspired Motivational Decision Making System for Social Robots Based on the Perception of the User.

Nowadays, many robotic applications require robots making their own decisions and adapting to different conditions and users. This work presents a biologically inspired decision making system, based on drives, motivations, wellbeing, and self-learning, that governs the behavior of the robot considering both internal and external circumstances. In this paper we state the biological foundations that drove the design of the system, as well as how it has been implemented in a real robot. Following a homeostatic approach, the ultimate goal of the robot is to keep its wellbeing as high as possible. In order to achieve this goal, our decision making system uses learning mechanisms to assess the best action to execute at any moment. Considering that the proposed system has been implemented in a real social robot, human-robot interaction is of paramount importance and the learned behaviors of the robot are oriented to foster the interactions with the user. The operation of the system is shown in a scenario where the robot Mini plays games with a user. In this context, we have included a robust user detection mechanism tailored for short distance interactions. After the learning phase, the robot has learned how to lead the user to interact with it in a natural way.

Using unmanned aerial vehicle (UAV) surveys and image analysis in the study of large surface-associated marine species: a case study on reef sharks Carcharhinus melanopterus shoaling behaviour.

A novel image analysis-based technique applied to unmanned aerial vehicle (UAV) survey data is described to detect and locate individual free-ranging sharks within aggregations. The method allows rapid collection of data and quantification of fine-scale swimming and collective patterns of sharks. We demonstrate the usefulness of this technique in a small-scale case study exploring the shoaling tendencies of blacktip reef sharks Carcharhinus melanopterus in a large lagoon within Moorea, French Polynesia. Using our approach, we found that C. melanopterus displayed increased alignment with shoal companions when distributed over a sandflat where they are regularly fed for ecotourism purposes as compared with when they shoaled in a deeper adjacent channel. Our case study highlights the potential of a relatively low-cost method that combines UAV survey data and image analysis to detect differences in shoaling patterns of free-ranging sharks in shallow habitats. This approach offers an alternative to current techniques commonly used in controlled settings that require time-consuming post-processing effort.

Detecting and Classifying Human Touches in a Social Robot Through Acoustic Sensing and Machine Learning.

An important aspect in Human-Robot Interaction is responding to different kinds of touch stimuli. To date, several technologies have been explored to determine how a touch is perceived by a social robot, usually placing a large number of sensors throughout the robot's shell. In this work, we introduce a novel approach, where the audio acquired from contact microphones located in the robot's shell is processed using machine learning techniques to distinguish between different types of touches. The system is able to determine when the robot is touched (touch detection), and to ascertain the kind of touch performed among a set of possibilities: stroke, tap, slap, and tickle (touch classification). This proposal is cost-effective since just a few microphones are able to cover the whole robot's shell since a single microphone is enough to cover each solid part of the robot. Besides, it is easy to install and configure as it just requires a contact surface to attach the microphone to the robot's shell and plug it into the robot's computer. Results show the high accuracy scores in touch gesture recognition. The testing phase revealed that Logistic Model Trees achieved the best performance, with an F-score of 0.81. The dataset was built with information from 25 participants performing a total of 1981 touch gestures.

Smart environment architecture for emotion detection and regulation.

This paper introduces an architecture as a proof-of-concept for emotion detection and regulation in smart health environments. The aim of the proposal is to detect the patient's emotional state by analysing his/her physiological signals, facial expression and behaviour. Then, the system provides the best-tailored actions in the environment to regulate these emotions towards a positive mood when possible. The current state-of-the-art in emotion regulation through music and colour/light is implemented with the final goal of enhancing the quality of life and care of the subject. The paper describes the three main parts of the architecture, namely "Emotion Detection", "Emotion Regulation" and "Emotion Feedback Control". "Emotion Detection" works with the data captured from the patient, whereas "Emotion Regulation" offers him/her different musical pieces and colour/light settings. "Emotion Feedback Control" performs as a feedback control loop to assess the effect of emotion regulation over emotion detection. We are currently testing the overall architecture and the intervention in real environments to achieve our final goal.

Development of a recommendation system and data analysis in personalized medicine: an approach towards healthy vascular ageing.

Purpose: Understanding early vascular ageing has become crucial for preventing adverse cardiovascular events. To this respect, recent AI-based risk clustering models offer early detection strategies focused on healthy populations, yet their complexity limits clinical use. This work introduces a novel recommendation system embedded in a web app to assess and mitigate early vascular ageing risk, leading patients towards improved cardiovascular health. Methods: This system employs a methodology that calculates distances within multidimensional spaces and integrates cost functions to obtain personalized optimisation of recommendations. It also incorporates a classification system for determining the intensity levels of the clinical interventions. Results: The recommendation system showed high efficiency in identifying and visualizing individuals at high risk of early vascular ageing among healthy patients. Additionally, the system corroborated its consistency and reliability in generating personalized recommendations among different levels of granularity, emphasizing its focus on moderate or low-intensity recommendations, which could improve patient adherence to the intervention. Conclusion: This tool might significantly aid healthcare professionals in their daily analysis, improving the prevention and management of cardiovascular diseases.

Acute Kidney Injury in the Context of COVID-19: An Analysis in Hospitalized Mexican Patients.

During the COVID-19 pandemic, a considerable proportion of patients developed a severe condition that included respiratory failure, shock, or multiple organ dysfunction. Acute Kidney Injury (AKI) has been recognized as a possible cause of severe COVID-19 development. Given this, this study investigates the occurrence and consequences of AKI in Mexican patients to contribute to better knowledge and management of this problem. Methods: Using a retrospective observational cohort methodology, we investigated 313 cases from a cohort of 1019 patients diagnosed with COVID-19 at the IMSS Zacatecas General Hospital of Zone No. 1 in 2020. The prevalence of AKI was determined using the AKIN criteria based on serum creatinine levels and a detailed review of demographic characteristics, medical history, comorbidities, and clinical development. Results: The data showed a 25.30% prevalence of AKI among patients infected with severe COVID-19. Remarkably, these patients with AKI exhibited an advanced age (>65 years), arterial hypertension, a higher number of white blood cells during admission and the hospital stay, and elevated levels of C-reactive protein, serum creatinine, and blood urea nitrogen (BUN). Clinically, patients with AKI had signs of prostration, pneumonia, and the requirement for ventilatory assistance when compared to those without AKI. Finally, those diagnosed with AKI and COVID-19 had a 74% death rate. Relative risk analyses indicated that age (>65 years), arterial hypertension, high creatinine levels, endotracheal intubation, and pneumonia are associated with the development of AKI. On the other hand, among the protective factors against AKI, high hemoglobin levels and the consumption of statins during COVID-19 were found. Conclusions: The findings of this study underscore the significance of promptly identifying and effectively managing AKI to potentially alleviate the negative consequences of this complication within the Mexican population during COVID-19.

An adaptive decision-making system supported on user preference predictions for human-robot interactive communication.

Adapting to dynamic environments is essential for artificial agents, especially those aiming to communicate with people interactively. In this context, a social robot that adapts its behaviour to different users and proactively suggests their favourite activities may produce a more successful interaction. In this work, we describe how the autonomous decision-making system embedded in our social robot Mini can produce a personalised interactive communication experience by considering the preferences of the user the robot interacts with. We compared the performance of Top Label as Class and Ranking by Pairwise Comparison, two promising algorithms in the area, to find the one that best predicts the user preferences. Although both algorithms provide robust results in preference prediction, we decided to integrate Ranking by Pairwise Comparison since it provides better estimations. The method proposed in this contribution allows the autonomous decision-making system of the robot to work on different modes, balancing activity exploration with the selection of the favourite entertaining activities. The operation of the preference learning system is shown in three real case studies where the decision-making system works differently depending on the user the robot is facing. Then, we conducted a human-robot interaction experiment to investigate whether the robot users perceive the personalised selection of activities more appropriate than selecting the activities at random. The results show how the study participants found the personalised activity selection more appropriate, improving their likeability towards the robot and how intelligent they perceive the system. query Please check the edit made in the article title.

The effectiveness of a web-based decision aid for patients with hip osteoarthritis: study protocol for a randomized controlled trial.

BACKGROUND: Osteoarthritis (OA) is a health condition sensitive to patient's preferences and values regarding the benefits and risks of the different treatment options. In this sense, patient decision aids (PtDA) can play an important role in helping patients to incorporate their values, needs, and preferences into the decision-making process, thus improving person-centered care. Previous research has focused almost exclusively on knee OA, and therefore, the aim of this study is to develop and evaluate the effectiveness of a PtDA for patients with hip OA. METHODS: The general design consists of two phases: (1) design a web-based PtDA for patients with hip OA, following the recommended procedures: systematic review of safety/effectiveness of treatments, and an iterative process of development with the help of an Advisory Committee composed of health professionals and patients, and (2) to evaluate the impact of the PtDA on hip OA patients' decision-making process related with their treatment. For that aim, a multicenter randomized controlled trial will be carried out with 124 patients with hip OA in Tenerife (Spain) comparing intervention or usual care. DISCUSSION: PtDAs have been recommended as a useful and effective resource for improving PCC in many health conditions. The intervention is intended to empower patients by fostering their active participation during the decision-making process about their treatment and by ensuring they make informed decisions congruent with their values and preferences. This study will contribute to the scientific knowledge about effectiveness of PtDAs in hip OA, in order to improve the quality of health care offered to these patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT04241978 . Registered on 24 January 2020.

Effectiveness and cost-effectiveness of a virtual community of practice to improve the empowerment of patients with ischaemic heart disease: study protocol of a randomised controlled trial.

INTRODUCTION: Virtual Communities of Practice (VCoP) or knowledge-sharing virtual communities offer ubiquitous access to information and exchange possibilities for people in similar situations, which might be especially valuable for the self-management of patients with chronic diseases. In view of the scarce evidence on the clinical and economic impact of these interventions on chronic conditions, we aim to evaluate the effectiveness and cost-effectiveness of a VCoP in the improvement of the activation and other patient empowerment measures in patients with ischaemic heart disease (IHD). METHODS AND ANALYSIS: A pragmatic randomised controlled trial will be performed in Catalonia, Madrid and Canary Islands, Spain. Two hundred and fifty patients with a recent diagnosis of IHD attending the participating centres will be selected and randomised to the intervention or control group. The intervention group will be offered participation for 12 months in a VCoP based on a gamified web 2.0 platform where there is interaction with other patients and a multidisciplinary professional team. Intervention and control groups will receive usual care. The primary outcome will be measured with the Patient Activation Measure questionnaire at baseline, 6, 12 and 18 months. Secondary outcomes will include: clinical variables; knowledge (Questionnaire of Cardiovascular Risk Factors), attitudes (Self-efficacy Managing Chronic Disease Scale), adherence to the Mediterranean diet (Mediterranean Diet Questionnaire), level of physical activity (International Physical Activity Questionnaire), depression (Patient Health Questionnaire), anxiety (Hospital Anxiety Scale-A), medication adherence (Adherence to Refill Medication Scale), quality of life (EQ-5D-5L) and health resources use. Data will be collected from self-reported questionnaires and electronic medical records. ETHICS AND DISSEMINATION: The trial was approved by Clinical Research Ethics Committee of Gregorio Marañón University Hospital in Madrid, Nuestra Señora de Candelaria University Hospital in Santa Cruz de Tenerife and IDIAP Jordi Gol in Barcelona. The results will be disseminated through workshops, policy briefs, peer-reviewed publications, local/international conferences. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Registry (NCT03959631). Pre-results.

Real-time accumulative computation motion detectors.

The neurally inspired accumulative computation (AC) method and its application to motion detection have been introduced in the past years. This paper revisits the fact that many researchers have explored the relationship between neural networks and finite state machines. Indeed, finite state machines constitute the best characterized computational model, whereas artificial neural networks have become a very successful tool for modeling and problem solving. The article shows how to reach real-time performance after using a model described as a finite state machine. This paper introduces two steps towards that direction: (a) A simplification of the general AC method is performed by formally transforming it into a finite state machine. (b) A hardware implementation in FPGA of such a designed AC module, as well as an 8-AC motion detector, providing promising performance results. We also offer two case studies of the use of AC motion detectors in surveillance applications, namely infrared-based people segmentation and color-based people tracking, respectively.

[Large uterine leiomyoma in a young patient]. / Leiomiomatosis uterina de grandes elementos en una paciente joven.

BACKGROUND: Great elements uterine leiomyomas are the most common tumours in the reproductive life affecting up to 30 % of the women in the United States. Its aetiology remains uncertain; cytogenic studies suggest that 40 to 50% present chromosomic abnormalities. Clinical manifestations are: hypermenorrhea and abdominal pain. In the great element cases, patients suffered intestinal constipation and rectal tenesm. The treatment includes analogous of human chorionic gonadotrophin liberation hormone (GnRH), progesterone, surgical treatment, myomectomy and hysterectomy, uterine artery embolization, high frequency ultrasound, laser, cryotherapy and thermoablation. CLINICAL CASE: An 18 year-old female, menarquia at 12, periods 28/4, nubil. 6 months previous: intestinal constipation, tumour-like mass in hypogastrium, of about 8 cm in diameter, which increased gradually up to 18 cm, smooth, movile and irregular. The pelvic ultrasound showed a tumour of 140 mm dependent of uterus. Myomectomy was performed. The histopathologic report was a 19.9 cm uterine leiomyoma, weighing 949 g and with hyaline degeneration. The patient was asymptomatic and without relapse a year later. CONCLUSIONS: Myomectomy is the choice treatment for the large uterine myomatosis when the patient's fertility is to be preserved.

Social Robotics in Therapy of Apraxia of Speech.

Apraxia of speech is a motor speech disorder in which messages from the brain to the mouth are disrupted, resulting in an inability for moving lips or tongue to the right place to pronounce sounds correctly. Current therapies for this condition involve a therapist that in one-on-one sessions conducts the exercises. Our aim is to work in the line of robotic therapies in which a robot is able to perform partially or autonomously a therapy session, endowing a social robot with the ability of assisting therapists in apraxia of speech rehabilitation exercises. Therefore, we integrate computer vision and machine learning techniques to detect the mouth pose of the user and, on top of that, our social robot performs autonomously the different steps of the therapy using multimodal interaction.

Association analysis between a VNTR intron 8 polymorphism of the dopamine transporter gene (SLC6A3) and obsessive- compulsive disorder in a Brazilian sample.

Family, twin and segregation analysis have provided evidences that genetic factors are implicated in the susceptibility for obsessive-compulsive disorder (OCD). Several lines of research suggest that the dopaminergic system may be involved in the pathophysiology of OCD. Thus, the aim of the present study was to investigate a possible association between a polymorphism located in intron 8 of the dopamine transporter gene (SLC6A3) and OCD in a Brazilian sample composed by 208 patients and 865 healthy controls. No statistical differences were observed in allelic and genotype distributions between cases and controls. No association was also observed when the sample was divided according to specific phenotypic features such as gender, presence of tic disorders, co-morbidity, and age at onset of obsessive-compulsive symptoms (OCS). Our results suggest that the intron 8 VNTR of the SLC6A3 investigated in this study is not related to the susceptibility for OCD in our Brazilian sample.

Association analysis between a VNTR intron 8 polymorphism of the dopamine transporter gene (SLC6A3) and obsessive- compulsive disorder in a Brazilian sample

Family, twin and segregation analysis have provided evidences that genetic factors are implicated in the susceptibility for obsessive-compulsive disorder (OCD). Several lines of research suggest that the dopaminergic system may be involved in the pathophysiology of OCD. Thus, the aim of the present study was to investigate a possible association between a polymorphism located in intron 8 of the dopamine transporter gene (SLC6A3) and OCD in a Brazilian sample composed by 208 patients and 865 healthy controls. No statistically differences were observed in allelic and genotype distributions between cases and controls. No association was also observed when the sample was divided according to specific phenotypic features such as gender, presence of tic disorders co-morbidity and age at onset of obsessive-compulsive symptoms (OCS). Our results suggest that the intron 8 VNTR of the SLC6A3 investigated in this study is not related to the susceptibility for OCD in our Brazilian sample.

Estudos de família, gêmeos e de segregação têm demonstrado que fatores genéticos estão envolvidos na susceptibilidade para o desenvolvimento do transtorno obsessivo-compulsivo (TOC). Várias linhas de pesquisa sugerem que o sistema dopaminérgico possa estar envolvido na fisiopatologia do TOC. Assim, o objetivo do presente estudo foi investigar uma possível associação entre o polimorfismo localizado no intron 8 do gene do transportador da dopamina (SLC6A3) e o TOC em uma amostra brasileira composta por 208 pacientes e 865 controles sadios. Nenhuma diferença estatisticamente significante foi observada nas distribuições alélicas e genotípicas entre os grupos de pacientes e controles. Nenhuma associação também foi observada quando as amostras foram divididas de acordo com características fenotípicas específicas, tais como gênero, presença de co-morbidade com tiques e idade de início dos sintomas obsessivo-compulsivo (SOC). Nossos resultados sugerem que o VNTR do intron 8 investigado neste estudo não está relacionado com o TOC na nossa amostra brasileira.

Neurobiologia em transtorno obsessivo-compulsivo de início na infância: estudo de revisäo / Neurobiology in obsessive-compulsive disorder beginning in the childhood: review study

Introdução: Alguns pacientes com transtorno obsessivo-compulsivo (TOC) de início na infância apresentam características clínicas que talvez justifiquem a inclusão destes em subgrupos distintos. Vários autores têm se dedicado a investigar a utilidade e a validade clínica dessa categorização de TOC infantil. Por outro lado, há evidências de que TOC poderia ser um transtorno devido a anormalidades no desenvolvimento de estruturas e circuitos no sistema nervoso central. O presente estudo tem como objetivo fazer uma revisão sobre o estado atual de conhecimento de aspectos neurobiológicos ligados ao TOC de início precoce. Metodologia: Revisão de artigos na literatura por meio de pesquisa em medline sobre características clínicas e estudos de neuroimagem de TOC de início na infância, sobre casos de coréia de Sydenham com manifestações psiquiátricas associadas em crianças e sobre associação de tiques (transtorno de Gilles de la Tourette e outros) e TOC infantil. Resultados: Transtorno do espectrum obsessivo-compulsivo incluindo tiques, sintomas obsessivo-compulsivos e outros distúrbios relacionados, de início pré-peberal, parece constituir um subgrupo clínico distinto, com história familiar positiva para tiques e TOC e resposta favorável, em alguns casos, ao tratamento com associação com neurolépticos. Manifestações de coréia de Sydenham associada a sintomas de TOC, reforçam a idéia de alterações nos gânglios da base envolvidas com fisiopatologia de TOC infantil. Estudos de neuroimagem estrutural em crianças e adolescentes com TOC apontam para alterações no desenvolvimento de estruturas subcorticais e de córtex pré-frontal na etiopatogenia desse transtorno. Conslusões: Esses resultados preliminares chamam a atenção para a importância de estudos nessa população sobre esse tema.

Neuroimagem em transtorno obsessivo-compulsivo / Neuroimagine in obsessive-compulsive disorder

O presente trabalho traz uma revisäo sobre neuroimagem em transtorno obsessivo-complusivo, analisando os achados em trabalhos publicados nos últimos cinco anos. Tais técnicas de exame permitiram a ocasiäo de estudar "in vivo" o que pode ocorrer no cérebro de pessoas que apresentam transtornos psiquiátricos. Em pacientes com transtorno obsessivo-compulsivo, exames de neuroimagem estruturais mostraram alteraçöes, como: aumento de volume ventricular em uma parcela destes pacientes e aumento do nucleo caudado unilateral (em geral a esquerda)...