Static and Dynamic Hand Gestures: A Review of Techniques of Virtual Reality Manipulation.

This review explores the historical and current significance of gestures as a universal form of communication with a focus on hand gestures in virtual reality applications. It highlights the evolution of gesture detection systems from the 1990s, which used computer algorithms to find patterns in static images, to the present day where advances in sensor technology, artificial intelligence, and computing power have enabled real-time gesture recognition. The paper emphasizes the role of hand gestures in virtual reality (VR), a field that creates immersive digital experiences through the Ma blending of 3D modeling, sound effects, and sensing technology. This review presents state-of-the-art hardware and software techniques used in hand gesture detection, primarily for VR applications. It discusses the challenges in hand gesture detection, classifies gestures as static and dynamic, and grades their detection difficulty. This paper also reviews the haptic devices used in VR and their advantages and challenges. It provides an overview of the process used in hand gesture acquisition, from inputs and pre-processing to pose detection, for both static and dynamic gestures.

A Framework for Real-Time Gestural Recognition and Augmented Reality for Industrial Applications.

In recent decades, technological advancements have transformed the industry, highlighting the efficiency of automation and safety. The integration of augmented reality (AR) and gesture recognition has emerged as an innovative approach to create interactive environments for industrial equipment. Gesture recognition enhances AR applications by allowing intuitive interactions. This study presents a web-based architecture for the integration of AR and gesture recognition, designed to interact with industrial equipment. Emphasizing hardware-agnostic compatibility, the proposed structure offers an intuitive interaction with equipment control systems through natural gestures. Experimental validation, conducted using Google Glass, demonstrated the practical viability and potential of this approach in industrial operations. The development focused on optimizing the system's software and implementing techniques such as normalization, clamping, conversion, and filtering to achieve accurate and reliable gesture recognition under different usage conditions. The proposed approach promotes safer and more efficient industrial operations, contributing to research in AR and gesture recognition. Future work will include improving the gesture recognition accuracy, exploring alternative gestures, and expanding the platform integration to improve the user experience.

Progressive Rehabilitation Based on EMG Gesture Classification and an MPC-Driven Exoskeleton.

Stroke is a leading cause of disability and death worldwide, with a prevalence of 200 millions of cases worldwide. Motor disability is presented in 80% of patients. In this context, physical rehabilitation plays a fundamental role for gradually recovery of mobility. In this work, we designed a robotic hand exoskeleton to support rehabilitation of patients after a stroke episode. The system acquires electromyographic (EMG) signals in the forearm, and automatically estimates the movement intention for five gestures. Subsequently, we developed a predictive adaptive control of the exoskeleton to compensate for three different levels of muscle fatigue during the rehabilitation therapy exercises. The proposed system could be used to assist the rehabilitation therapy of the patients by providing a repetitive, intense, and adaptive assistance.

Recognition of Hand Gestures Based on EMG Signals with Deep and Double-Deep Q-Networks.

In recent years, hand gesture recognition (HGR) technologies that use electromyography (EMG) signals have been of considerable interest in developing human-machine interfaces. Most state-of-the-art HGR approaches are based mainly on supervised machine learning (ML). However, the use of reinforcement learning (RL) techniques to classify EMGs is still a new and open research topic. Methods based on RL have some advantages such as promising classification performance and online learning from the user's experience. In this work, we propose a user-specific HGR system based on an RL-based agent that learns to characterize EMG signals from five different hand gestures using Deep Q-network (DQN) and Double-Deep Q-Network (Double-DQN) algorithms. Both methods use a feed-forward artificial neural network (ANN) for the representation of the agent policy. We also performed additional tests by adding a long-short-term memory (LSTM) layer to the ANN to analyze and compare its performance. We performed experiments using training, validation, and test sets from our public dataset, EMG-EPN-612. The final accuracy results demonstrate that the best model was DQN without LSTM, obtaining classification and recognition accuracies of up to 90.37%±10.7% and 82.52%±10.9%, respectively. The results obtained in this work demonstrate that RL methods such as DQN and Double-DQN can obtain promising results for classification and recognition problems based on EMG signals.

Hand Gesture Recognition Using EMG-IMU Signals and Deep Q-Networks.

Hand gesture recognition systems (HGR) based on electromyography signals (EMGs) and inertial measurement unit signals (IMUs) have been studied for different applications in recent years. Most commonly, cutting-edge HGR methods are based on supervised machine learning methods. However, the potential benefits of reinforcement learning (RL) techniques have shown that these techniques could be a viable option for classifying EMGs. Methods based on RL have several advantages such as promising classification performance and online learning from experience. In this work, we developed an HGR system made up of the following stages: pre-processing, feature extraction, classification, and post-processing. For the classification stage, we built an RL-based agent capable of learning to classify and recognize eleven hand gestures-five static and six dynamic-using a deep Q-network (DQN) algorithm based on EMG and IMU information. The proposed system uses a feed-forward artificial neural network (ANN) for the representation of the agent policy. We carried out the same experiments with two different types of sensors to compare their performance, which are the Myo armband sensor and the G-force sensor. We performed experiments using training, validation, and test set distributions, and the results were evaluated for user-specific HGR models. The final accuracy results demonstrated that the best model was able to reach up to 97.50%±1.13% and 88.15%±2.84% for the classification and recognition, respectively, with regard to static gestures, and 98.95%±0.62% and 90.47%±4.57% for the classification and recognition, respectively, with regard to dynamic gestures with the Myo armband sensor. The results obtained in this work demonstrated that RL methods such as the DQN are capable of learning a policy from online experience to classify and recognize static and dynamic gestures using EMG and IMU signals.

Selection of the Best Set of Features for sEMG-Based Hand Gesture Recognition Applying a CNN Architecture.

The classification of surface myoelectric signals (sEMG) remains a great challenge when focused on its implementation in an electromechanical hand prosthesis, due to its nonlinear and stochastic nature, as well as the great difference between models applied offline and online. In this work, the selection of the set of the features that allowed us to obtain the best results for the classification of this type of signals is presented. In order to compare the results obtained, the Nina PRO DB2 and DB3 databases were used, which contain information on 50 different movements of 40 healthy subjects and 11 amputated subjects, respectively. The sEMG of each subject was acquired through 12 channels in a bipolar configuration. To carry out the classification, a convolutional neural network (CNN) was used and a comparison of four sets of features extracted in the time domain was made, three of which have shown good performance in previous works and one more that was used for the first time to train this type of network. Set one is composed of six features in the time domain (TD1), Set two has 10 features also in the time domain (TD2) including the autoregression model (AR), the third set has two features in the time domain derived from spectral moments (TD-PSD1), and finally, a set of five features also has information on the power spectrum of the signal obtained in the time domain (TD-PSD2). The selected features in each set were organized in four different ways for the formation of the training images. The results obtained show that the set of features TD-PSD2 obtained the best performance for all cases. With the set of features and the formation of images proposed, an increase in the accuracies of the models of 8.16% and 8.56% was obtained for the DB2 and DB3 databases, respectively, compared to the current state of the art that has used these databases.

Towards Facial Gesture Recognition in Photographs of Patients with Facial Palsy.

Humans express their emotions verbally and through actions, and hence emotions play a fundamental role in facial expressions and body gestures. Facial expression recognition is a popular topic in security, healthcare, entertainment, advertisement, education, and robotics. Detecting facial expressions via gesture recognition is a complex and challenging problem, especially in persons who suffer face impairments, such as patients with facial paralysis. Facial palsy or paralysis refers to the incapacity to move the facial muscles on one or both sides of the face. This work proposes a methodology based on neural networks and handcrafted features to recognize six gestures in patients with facial palsy. The proposed facial palsy gesture recognition system is designed and evaluated on a publicly available database with good results as a first attempt to perform this task in the medical field. We conclude that, to recognize facial gestures in patients with facial paralysis, the severity of the damage has to be considered because paralyzed organs exhibit different behavior than do healthy ones, and any recognition system must be capable of discerning these behaviors.

Do gesto à linguagem indireta: a noção de expressão em Merleau-Ponty / From gesture to indirect language: the notion of expression in Merleau-Ponty

O objetivo do artigo é compreender a noção de linguagem e expressão em Merleau-Ponty, de modo a evidenciar como se dá a gênese de sentido linguístico. Primeiro, optamos em expor o estado da questão na Fenomenologia da Percepção. Introduzimos o corpo como potência expressiva e significativa de mundo, e a linguagem como expressão atrelada ao caráter gestual da palavra. Em seguida, apresentamos a expressão da linguagem após a apropriação feita por Merleau-Ponty da linguística de Saussure. Por fim, enfocamos a articulação entre o sentido gestual da palavra e o caráter sistemático da língua: o sujeito falante, enquanto potência de atualização e criação de sentido, assume a língua à qual pertence, ao mesmo tempo em que a língua forma sua possibilidade de expressão.

This paper aims to understand the notion of language and expression in Merleau-Ponty, in order to show how the genesis of linguistic meaning occurs. First, we chose to showcase the state of this question in Phenomenology of Perception.We introduce the body as an expressive and significant power of world, and the language as an expression linked to the gestural character of the word. Then, we present the language expression after Merleau-Ponty's appropriation of Saussure's linguistics. Finally, we focus on the articulation between the gestural sense of the word and the systematic character of the language: the speaking subject, as a power of updating and creating meaning, assumes the language to which it belongs, at the same time that the language forms its possibility of expression.

Gestos humanos ¿herencia o crianza? / Human gestures inheritance or parenting?

El Documental, nos da a ver de un modo peculiar un experimento realizado con seres humanos en la década del ´60. El escenario que recorta arbitra la apertura para diferentes ejes de interés que atañen a la ética como dilemas, pero a su vez, problemas que la práctica misma construye. Haremos un recorte, en este texto, basado en los gestos que nos son dados a ver y leer y examinaremos, a partir de ellos, el lugar dado a la historia en la vida del infans, el concepto de niño y de la familia en el que se soportó el experimento original y el modo en que los relatos despliegan esas marcas ¿singularmente?

The Documentary, give us to see in a peculiar way an experiment carried out with human beings in the 60s. The scenario that cuts out arbitrates the opening for different axes of interest that concern ethics as dilemmas, but at the same time, problems that the practice itself constructs. We will make a route, in this text, based on the gestures that we are given to see and read, and we will examine, based on them, the place given to history in the life of infans, the concept of the child and the family in which the original experiment was supported and the way in which the stories display those marks, singularly?

Fundamentos físicos del gesto técnico del pitcher / Fundamentos físicos do gesto técnico do lançador / Physical foundations of the pitcher's technical gesture

RESUMEN La codicia por lanzar duro en el béisbol, más el desconocimiento mecánico-energético del aporte y lo que evita la correcta ejecución de las fases del gesto técnico del pitcher, resultaron ser las principales causas de las lesiones y el motivo de una investigación explicativa, a través de la aplicación de métodos físicos cinemáticos, dinámicos y energéticos, en el estudio de la manifestación de leyes físicas durante la observación no participativa de su desempeño, al lanzar la pelota, tanto en lanzadores nacionales como internacionales y de testimonios de personas con experiencias como pitcher. El objetivo de este artículo consistió en proponer una explicación física de cómo funciona la biomecánica del cuerpo del pitcher durante los gestos técnicos del lanzamiento para garantizar una bola rápida y minimizar lesiones. Con este trabajo, se pretendió, además, instruir al pitcher de cómo funciona la biomecánica de su cuerpo durante el lanzamiento de la pelota, aprovechando ventaja de la altura del montículo con argumentos desde la ciencia Física; esto contribuyó a lanzamientos más rápidos, elegantes y a minimizar lesiones. Como resultado, se elaboró una explicación física por fases para el pitcher, además, un sistema masa-resorte aislado para experimentar movimientos biomecánicos y energéticos, que evidenciaron en su desempeño manifestaciones de las leyes físicas de la mecánica clásica de Newton, de la conservación de la energía mecánica, del momento cinético y del momento angular.

RESUMO A ganância de jogar duro no basebol, mais a ignorância mecânico-energética da contribuição e o que impede a correta execução das fases do gesto técnico do lançador, revelaram-se as principais causas de lesões e a razão de uma pesquisa explicativa, através da aplicação de métodos físicos cinemáticos, dinâmicos e energéticos, no estudo da manifestação das leis físicas durante a observação não participativa do seu desempenho, ao lançar a bola, tanto em lançadores nacionais como internacionais e testemunhos de pessoas com experiências como lançadores. O objetivo deste artigo é propor uma explicação física de como funciona a biomecânica do corpo do lançador durante os gestos técnicos de lançamento para garantir uma bola rápida e minimizar as lesões. Com este trabalho, pretende-se também instruir o lançador sobre como funciona a biomecânica do seu corpo durante o lançamento da bola, tirando partido da altura do monte com argumentos da ciência física. Isto contribui para campos mais rápidos e mais elegantes e para minimizar as lesões. Como resultado, foi elaborada uma explicação física por fases para o jarro, além disso, um sistema isolado de suspensão em massa para experimentar movimentos biomecânicos e energéticos, que evidenciou no seu desempenho, manifestações das leis físicas da mecânica clássica de Newton, da conservação da energia mecânica, do momento cinético e do momento angular.

ABSTRACT The greed to throw hard in baseball, plus the mechanical-energetic ignorance of the contribution and what prevents the correct execution of the phases of the pitcher's technical gesture, turned out to be the main causes of injuries and the reason for an explanatory research, through the application of physical kinematic, dynamic and energetic methods, in the study of the manifestation of physical laws during the non-participatory observation of their performance, when throwing the ball, both in national and international pitchers and testimonies of people with experiences as pitchers. The objective of this article is to propose a physical explanation of how the biomechanics of the pitcher's body works during the technical gestures of pitching to guarantee a fast ball and minimize injuries. With this work, it is also intended to instruct the pitcher on how the biomechanics of his body works during the pitching of the ball, taking advantage of the height of the mound with arguments from the physical science. This contributes to faster, more elegant pitches and to minimize injuries. As a result, a physical explanation by phases was elaborated for the pitcher, in addition, an isolated mass-spring system to experiment biomechanical and energetic movements, which evidenced in their performance manifestations of the physical laws of Newton's classical mechanics, conservation of mechanical energy, kinetic momentum and angular momentum.

Structural biases that children bring to language learning: A cross-cultural look at gestural input to homesign.

Linguistic input has an immediate effect on child language, making it difficult to discern whatever biases children may bring to language-learning. To discover these biases, we turn to deaf children who cannot acquire spoken language and are not exposed to sign language. These children nevertheless produce gestures, called homesigns, which have structural properties found in natural language. We ask whether these properties can be traced to gestures produced by hearing speakers in Nicaragua, a gesture-rich culture, and in the USA, a culture where speakers rarely gesture without speech. We studied 7 homesigning children and hearing family members in Nicaragua, and 4 in the USA. As expected, family members produced more gestures without speech, and longer gesture strings, in Nicaragua than in the USA. However, in both cultures, homesigners displayed more structural complexity than family members, and there was no correlation between individual homesigners and family members with respect to structural complexity. The findings replicate previous work showing that the gestures hearing speakers produce do not offer a model for the structural aspects of homesign, thus suggesting that children bring biases to construct, or learn, these properties to language-learning. The study also goes beyond the current literature in three ways. First, it extends homesign findings to Nicaragua, where homesigners received a richer gestural model than USA homesigners. Moreover, the relatively large numbers of gestures in Nicaragua made it possible to take advantage of more sophisticated statistical techniques than were used in the original homesign studies. Second, the study extends the discovery of complex noun phrases to Nicaraguan homesign. The almost complete absence of complex noun phrases in the hearing family members of both cultures provides the most convincing evidence to date that homesigners, and not their hearing family members, are the ones who introduce structural properties into homesign. Finally, by extending the homesign phenomenon to Nicaragua, the study offers insight into the gestural precursors of an emerging sign language. The findings shed light on the types of structures that an individual can introduce into communication before that communication is shared within a community of users, and thus sheds light on the roots of linguistic structure.

The influence of sleep on language production modalities in preschool children with Down syndrome.

Evidence suggests that sleep may relate to oral language production in children with Down syndrome. However, these children are capable of using complex referential gestures as a compensation strategy for problems with oral production, and those with a greater productive oral vocabulary have less gestural vocabulary. The goal of this study was to explore whether sleep quality relates to oral and gestural production modalities in children with Down syndrome. We evaluated 36 preschool children with and without Down syndrome, paired by chronological age and gender, with similar sociodemographic backgrounds, using actigraphy to measure sleep behaviour and the Communicative Development Inventory for Down syndrome to measure vocabulary. Children with Down syndrome with better sleep efficiency showed more oral production but less gestural production. These results highlight the importance of sleep quality to language learning in children with Down syndrome.

A Gesture Elicitation Study of Nose-Based Gestures.

Presently, miniaturized sensors can be embedded in any small-size wearable to recognize movements on some parts of the human body. For example, an electrooculography-based sensor in smart glasses recognizes finger movements on the nose. To explore the interaction capabilities, this paper conducts a gesture elicitation study as a between-subjects experiment involving one group of 12 females and one group of 12 males, expressing their preferred nose-based gestures on 19 Internet-of-Things tasks. Based on classification criteria, the 912 elicited gestures are clustered into 53 unique gestures resulting in 23 categories, to form a taxonomy and a consensus set of 38 final gestures, providing researchers and practitioners with a larger base with six design guidelines. To test whether the measurement method impacts these results, the agreement scores and rates, computed for determining the most agreed gestures upon participants, are compared with the Condorcet and the de Borda count methods to observe that the results remain consistent, sometimes with a slightly different order. To test whether the results are sensitive to gender, inferential statistics suggest that no significant difference exists between males and females for agreement scores and rates.

Space in Hand and Mind: Gesture and Spatial Frames of Reference in Bilingual Mexico.

Speakers of many languages prefer allocentric frames of reference (FoRs) when talking about small-scale space, using words like "east" or "downhill." Ethnographic work has suggested that this preference is also reflected in how such speakers gesture. Here, we investigate this possibility with a field experiment in Juchitán, Mexico. In Juchitán, a preferentially allocentric language (Isthmus Zapotec) coexists with a preferentially egocentric one (Spanish). Using a novel task, we elicited spontaneous co-speech gestures about small-scale motion events (e.g., toppling blocks) in Zapotec-dominant speakers and in balanced Zapotec-Spanish bilinguals. Consistent with prior claims, speakers' spontaneous gestures reliably reflected either an egocentric or allocentric FoR. The use of the egocentric FoR was predicted-not by speakers' dominant language or the language they used in the task-but by mastery of words for "right" and "left," as well as by properties of the event they were describing. Additionally, use of the egocentric FoR in gesture predicted its use in a separate nonlinguistic memory task, suggesting a cohesive cognitive style. Our results show that the use of spatial FoRs in gesture is pervasive, systematic, and shaped by several factors. Spatial gestures, like other forms of spatial conceptualization, are thus best understood within broader ecologies of communication and cognition.

Procedimiento para el análisis biomecánico de la variabilidad del movimiento en el lanzamiento de disco / Procedimento para a análise biomecânica da variabilidade do movimento no lançamento do disco / Procedure for the analysis of the biomechanics of the variability of the movement in the discus throwing

Resumen El análisis sobre la técnica de los movimientos deportivos desde el estudio de la variabilidad del movimiento es un nuevo acercamiento a la evaluación, diagnóstico y control de las técnicas deportivas. Se conoció de la existencia de diversas investigaciones sobre la técnica del lanzamiento del disco, sin embargo, estas no han enfocado sus análisis desde la variabilidad, ni han ofrecido procedimientos para hacer el análisis desde esta perspectiva. El objetivo de esta investigación es establecer un procedimiento para el estudio de la variabilidad de la técnica en el Lanzamiento de Disco. El estudio se centró en un caso del sexo masculino que cuenta con 15 años y que entrena lanzamiento del disco en la Escuela de Iniciación Deportiva Escolar (Eide) de Villa Clara. Cuba. En la investigación se utilizaron métodos del nivel teórico y empírico tales como el estudio de casos, el estudio biomecánico y el análisis estadístico-matemático. Se logra comprobar que solo dos parámetros mostraron alta variabilidad en los nueve lanzamientos efectuados, mientras que el resto si logra una desviación estándar menor y por tanto poca variabilidad en los movimientos, además, existió una alta satisfacción de los usuarios con el procedimiento utilizado. El índice obtenido al aplicar la técnica IADOV indica que existe satisfacción de los usuarios introductores con los indicadores determinados.

Resumo A análise da técnica dos movimentos esportivos a partir do estudo da variabilidade do movimento é uma nova abordagem para a avaliação, diagnóstico e controle das técnicas esportivas. Sabia-se da existência de várias investigações sobre a técnica do lançamento de disco, porém, estas não focalizaram sua análise a partir da variabilidade, nem ofereceram procedimentos para fazer a análise nesta perspectiva. O objetivo desta pesquisa é estabelecer um procedimento para o estudo da variabilidade da técnica de Lançamento de Disco. O estudo teve como foco um jovem de 15 anos que treina lançamento de disco na Escola de Iniciação ao Esporte Escolar (Eide), em Villa Clara. Cuba. A pesquisa utilizou métodos de nível teórico e empírico como o estudo de caso, o estudo biomecânico e a análise estatística-matemática. É possível verificar que apenas dois parâmetros apresentaram alta variabilidade nos 9 arremessos realizados, enquanto os demais obtiveram menor desvio padrão e, portanto, pouca variabilidade nos movimentos, além disso, houve alta satisfação dos usuários com o procedimento utilizado. O índice obtido pela aplicação da técnica IADOV indica que há satisfação dos usuários introdutores com os indicadores determinados.

Abstract The analysis on the technique of the sport movements from the study of the variability of the movement is a new approach to the evaluation, diagnosis and control of the sport techniques. It was known of the existence of diverse investigations on the technique of the Launching of the Disk, however these they have not focused their analyses from the variability; neither they have offered procedures to make the analysis from this perspective. The objective of this paper is: to establish a procedure for the study of the variability of the technique in the Launching of Disk. The study was centered in a case of the masculine sex that has 15 years and that it trains Launching of the Disk in the School of Initiation Sport Scholar of Villa Clara. Cuba. As the research methods of the theoretical and empiric level were used as the study of cases, the study of the Biomechanics and the statistical-mathematical analysis. it is possible to verify that single two parameters showed high variability in the 9 made launchings, while the rest if it achieves a deviation standard smaller and therefore little variability in the movements, also, a high satisfaction of the users existed with the used procedure. The index obtained when applying the technical IADOV indicates that the introductory users' satisfaction exists with the certain indicators.

An Energy-Based Method for Orientation Correction of EMG Bracelet Sensors in Hand Gesture Recognition Systems.

Hand gesture recognition (HGR) systems using electromyography (EMG) bracelet-type sensors are currently largely used over other HGR technologies. However, bracelets are susceptible to electrode rotation, causing a decrease in HGR performance. In this work, HGR systems with an algorithm for orientation correction are proposed. The proposed orientation correction method is based on the computation of the maximum energy channel using a synchronization gesture. Then, the channels of the EMG are rearranged in a new sequence which starts with the maximum energy channel. This new sequence of channels is used for both training and testing. After the EMG channels are rearranged, this signal passes through the following stages: pre-processing, feature extraction, classification, and post-processing. We implemented user-specific and user-general HGR models based on a common architecture which is robust to rotations of the EMG bracelet. Four experiments were performed, taking into account two different metrics which are the classification and recognition accuracy for both models implemented in this work, where each model was evaluated with and without rotation of the bracelet. The classification accuracy measures how well a model predicted which gesture is contained somewhere in a given EMG, whereas recognition accuracy measures how well a model predicted when it occurred, how long it lasted, and which gesture is contained in a given EMG. The results of the experiments (without and with orientation correction) executed show an increase in performance from 44.5% to 81.2% for classification and from 43.3% to 81.3% for recognition in user-general models, while in user-specific models, the results show an increase in performance from 39.8% to 94.9% for classification and from 38.8% to 94.2% for recognition. The results obtained in this work evidence that the proposed method for orientation correction makes the performance of an HGR robust to rotations of the EMG bracelet.

An Acoustic Sensing Gesture Recognition System Design Based on a Hidden Markov Model.

Many human activities are tactile. Recognizing how a person touches an object or a surface surrounding them is an active area of research and it has generated keen interest within the interactive surface community. In this paper, we compare two machine learning techniques, namely Artificial Neural Network (ANN) and Hidden Markov Models (HMM), as they are some of the most common techniques with low computational cost used to classify an acoustic-based input. We employ a small and low-cost hardware design composed of a microphone, a stethoscope, a conditioning circuit, and a microcontroller. Together with an appropriate surface, we integrated these components into a passive gesture recognition input system for experimental evaluation. To perform the evaluation, we acquire the signals using a small microphone and send it through the microcontroller to MATLAB's toolboxes to implement and evaluate the ANN and HMM models. We also present the hardware and software implementation and discuss the advantages and limitations of these techniques in gesture recognition while using a simple alphabet of three geometrical figures: circle, square, and triangle. The results validate the robustness of the HMM technique that achieved a success rate of 90%, with a shorter training time than the ANN.

A construção da expressão de gênero na infância: do gesto à palavra / The construction of the expression of gender in childhood: from gesture to word / La construcción de la expresión de género en la infancia: del gesto a la palabra

Este artigo aborda a construção da expressão de gênero pelas crianças, à luz das contribuições do construcionismo social. A construção da expressão de gênero, vivida por meninos e meninas, é desenvolvida na dinâmica das relações sociais. De modo continuado e ininterrupto, a construção da expressão de gênero pelas crianças se dá pelas linguagens gestuais e verbais: do gesto à palavra. Tal compreensão foi construída com base em pesquisa bibliográfica e de campo realizada com crianças de 4 a 5 anos, no ambiente escolar. Nessa investigação, os dados foram construídos por um olhar etnográfico e sistematizados mediante núcleos de significação. Nesse processo, foi possível conhecer os modos de compreensão das educadoras sobre a identificação de gênero pelas crianças, bem como problematizar e compreender tais formas de entendimento.

This article deals with the construction of the expression of gender by children in the light of the contributions of social constructionism. The construction of gender expression, experienced by boys and girls, is developed through dynamics of social relations. In a continuous and uninterrupted way, the gestural and verbal languages give the construction of the expression of gender by children: from gesture to the word. This understanding was built based on bibliographical and field research carried out with children from 4 to 5 years old, in the school environment. In this research, the data was constructed based on an ethnographic look and systematized through nuclei of meaning. In this process, it was possible to interpret the educators' ways of understanding the identification of gender by children, as well as to problematize and comprehend such forms of understanding.

Este artículo discute la construcción de expresión de género por parte de los niños, teniendo en cuenta las contribuciones del construccionismo social. La construcción de la expresión de género, experimentada por los niños y las niñas, se desarrolla en la dinámica de las relaciones sociales. De modo continuado e ininterrumpido, la construcción de la expresión de género por parte de los niños se produce a través del lenguaje gestual y verbal: del gesto a la palabra. Tal comprensión se construye basada en bibliografías e investigación de campo, llevado a cabo con niños de 4 a 5 años, en el ambiente escolar. En esta investigación, los datos fueron construidos por una mirada etnográfica y organizados por núcleos de significado. En este proceso, fue posible conocer las formas de comprensión de los educadores en la identificación de género por los niños, así como discutir y entender esas formas de comprensión.

The communicative importance of agent-backgrounding: Evidence from homesign and Nicaraguan Sign Language.

Some concepts are more essential for human communication than others. In this paper, we investigate whether the concept of agent-backgrounding is sufficiently important for communication that linguistic structures for encoding this concept are present in young sign languages. Agent-backgrounding constructions serve to reduce the prominence of the agent - the English passive sentence a book was knocked over is an example. Although these constructions are widely attested cross-linguistically, there is little prior research on the emergence of such devices in new languages. Here we studied how agent-backgrounding constructions emerge in Nicaraguan Sign Language (NSL) and adult homesign systems. We found that NSL signers have innovated both lexical and morphological devices for expressing agent-backgrounding, indicating that conveying a flexible perspective on events has deep communicative value. At the same time, agent-backgrounding devices did not emerge at the same time as agentive devices. This result suggests that agent-backgrounding does not have the same core cognitive status as agency. The emergence of agent-backgrounding morphology appears to depend on receiving a linguistic system as input in which linguistic devices for expressing agency are already well-established.

Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic Literature Review.

Today, daily life is composed of many computing systems, therefore interacting with them in a natural way makes the communication process more comfortable. Human-Computer Interaction (HCI) has been developed to overcome the communication barriers between humans and computers. One form of HCI is Hand Gesture Recognition (HGR), which predicts the class and the instant of execution of a given movement of the hand. One possible input for these models is surface electromyography (EMG), which records the electrical activity of skeletal muscles. EMG signals contain information about the intention of movement generated by the human brain. This systematic literature review analyses the state-of-the-art of real-time hand gesture recognition models using EMG data and machine learning. We selected and assessed 65 primary studies following the Kitchenham methodology. Based on a common structure of machine learning-based systems, we analyzed the structure of the proposed models and standardized concepts in regard to the types of models, data acquisition, segmentation, preprocessing, feature extraction, classification, postprocessing, real-time processing, types of gestures, and evaluation metrics. Finally, we also identified trends and gaps that could open new directions of work for future research in the area of gesture recognition using EMG.