Explore the vast range of titles available.

El artículo explora la posibilidad de integrar parte de la actividad deportiva dentro del marco de preocupaciones semióticas adscritas a la kinésica, una de sus grandes señas de identidad temática. En primer lugar, se realiza una aproximación teórica, para a continuación proponer una taxonomía de esta, basada en la casuística que genera la propia dinámica deportiva. Al final del trabajo, se confirma la hipótesis teórico-metodológica de la que se había partido, lo que supone abrir un camino para futuras investigaciones en semiótica deportiva.

Emotion is a subjective psychophysiological reaction coming from external stimuli which impacts every aspect of our daily lives. Due to the continuing development of non-invasive and portable sensor technologies, such as brain-computer interfaces (BCI), intellectuals from several fields have been interested in emotion recognition techniques. Human emotions can be recognised using a variety of behavioural cues, including gestures and body language, voice, and physiological markers. The first three, however, might be ineffective because people sometimes conceal their genuine emotions either intentionally or unknowingly. More precise and objective emotion recognition can be accomplished using physiological signals. Among other physiological signals, Electroencephalogram (EEG) is more responsive and sensitive to variation in affective states. Various EEG-based emotion recognition methods have recently been introduced. This study reviews EEG-based BCIs for emotion identification and gives an outline of the progress made in this field. A summary of the datasets and techniques utilised to evoke human emotions and various emotion models is also given. We discuss several EEG feature extractions, feature selection/reduction, machine learning, and deep learning algorithms in accordance with standard emotional identification process. We provide an overview of the human brain's EEG rhythms, which are closely related to emotional states. We also go over a number of EEG-based emotion identification research and compare numerous machine learning and deep learning techniques. In conclusion, this study highlights the applications, challenges and potential areas for future research in identification and classification of human emotional states.

The distinction between positive and negative emotions is fundamental in emotion models. Intriguingly, neurobiological work suggests shared mechanisms across positive and negative emotions. We tested whether similar overlap occurs in real-life facial expressions. During peak intensities of emotion, positive and negative situations were successfully discriminated from isolated bodies but not faces. Nevertheless, viewers perceived illusory positivity or negativity in the nondiagnostic faces when seen with bodies. To reveal the underlying mechanisms, we created compounds of intense negative faces combined with positive bodies, and vice versa. Perceived affect and mimicry of the faces shifted systematically as a function of their contextual body emotion. These findings challenge standard models of emotion expression and highlight the role of the body in expressing and perceiving emotions.

Sign language descriptions that use an analytic model borrowed from spoken language structural linguistics have proved to be not fully appropriate. Pictorial and action-like modes of expression are integral to how signed utterances are constructed and to how they work. However, observation shows that speakers likewise use kinesic and vocal expressions that are not accommodated by spoken language structural linguistic models, including pictorial and action-like modes of expression. These, also, are integral to how speaker utterances in face-to-face interaction are constructed and to how they work. Accordingly, the object of linguistic inquiry should be revised, so that it comprises not only an account of the formal abstract systems that utterances make use of, but also an account of how the semiotically diverse resources that all languaging individuals use are organized in relation to one another. Both language as an abstract system and languaging should be the concern of linguistics.

Joint action is essential in daily life, as humans often must coordinate with others to accomplish shared goals. Previous studies have mainly focused on sensorimotor aspects of joint action, with measurements reflecting event-to-event precision of interpersonal sensorimotor coordination (e.g., tapping). However, while emotional factors are often closely tied to joint actions, they are rarely studied, as event-to-event measurements are insufficient to capture higher-order aspects of joint action such as emotional expression. To quantify joint emotional expression, we used motion capture to simultaneously measure the body sway of each musician in a trio (piano, violin, cello) during performances. Excerpts were performed with or without emotional expression. Granger causality was used to analyze body sway movement time series amongst musicians, which reflects information flow. Results showed that the total Granger-coupling of body sway in the ensemble was higher when performing pieces with emotional expression than without. Granger-coupling further correlated with the emotional intensity as rated by both the ensemble members themselves and by musician judges, based on the audio recordings alone. Together, our findings suggest that Granger-coupling of co-actors’ body sways reflects joint emotional expression in a music ensemble, and thus provide a novel approach to studying joint emotional expression.

Gesture, outlined in terms of physical activity, philosophical theory and linguistics are strongly connected in the course of human interaction. Utterances are accompanied by facial expressions, shifts of gaze, movements, posture, etc. Therefore, we support the thesis that a gestural approach to analyzing communicative events is appropriate, since non-verbal components communicate attitudes and emotions and complete the verbal interchange in numerous ways. Disagreements are especially prone to such an analysis.

Recent theories of embodied cognition suggest new ways to look at how we process emotional information. The theories suggest that perceiving and thinking about emotion involve perceptual, somatovisceral, and motoric reexperiencing (collectively referred to as \"embodiment\") of the relevant emotion in one's self. The embodiment of emotion, when induced in human participants by manipulations of facial expression and posture in the laboratory, causally affects how emotional information is processed. Congruence between the recipient's bodily expression of emotion and the sender's emotional tone of language, for instance, facilitates comprehension of the communication, whereas incongruence can impair comprehension. Taken all together, recent findings provide a scientific account of the familiar contention that \"when you're smiling, the whole world smiles with you.\"

We assessed dairy cows' body postures while they were performing different stationary activities in a loose housing system and then used the variation within and between individuals to identify potential connections between specific postures and the valence and arousal dimensions of emotion. We observed 72 individuals within a single milking herd focusing on their ear, neck and tail positions while they were: feeding from individual roughage bins, being brushed by a mechanical rotating brush and queuing to enter a single automatic milking system. Cows showed different ear, neck and tail postures depending on the situation. When combined, their body posture during feeding was ears back up and neck down, with tail wags directed towards the body, during queuing their ears were mainly axial and forward, their neck below the horizontal and the tail hanging stationary, and during brushing their ears were backwards and asymmetric, the neck horizontal and the tail wagging vigorously. We then placed these findings about cow body posture during routine activities into an arousal/valence framework used in animal emotion research (dimensional model of core affect). In this way we generate a priori predictions of how the positions of the ears, neck and tail of cows may change in other situations, previously demonstrated to vary in valence and arousal. We propose that this new methodology, with its different steps of integration, could contribute to the identification and validation of behavioural (postural) indicators of how positively or negatively cows experience other activities, or situations, and how calm or aroused they are. Although developed here on dairy cattle, by focusing on relevant postures, this approach could be easily adapted to other species.