ESC core curriculum for the general cardiologist (2013)

[No abstract available

What does not happen: quantifying embodied engagement using NIMI and self-adaptors

Previous research into the quantification of embodied intellectual and emotional engagement using non-verbal movement parameters has not yielded consistent results across different studies. Our research introduces NIMI (Non-Instrumental Movement Inhibition) as an alternative parameter. We propose that the absence of certain types of possible movements can be a more holistic proxy for cognitive engagement with media (in seated persons) than searching for the presence of other movements. Rather than analyzing total movement as an indicator of engagement, our research team distinguishes between instrumental movements (i.e. physical movement serving a direct purpose in the given situation) and non-instrumental movements, and investigates them in the context of the narrative rhythm of the stimulus. We demonstrate that NIMI occurs by showing viewers’ movement levels entrained (i.e. synchronised) to the repeating narrative rhythm of a timed computer-presented quiz. Finally, we discuss the role of objective metrics of engagement in future context-aware analysis of human behaviour in audience research, interactive media and responsive system and interface design

Deep fusion of multi-channel neurophysiological signal for emotion recognition and monitoring

How to fuse multi-channel neurophysiological signals for emotion recognition is emerging as a hot research topic in community of Computational Psychophysiology. Nevertheless, prior feature engineering based approaches require extracting various domain knowledge related features at a high time cost. Moreover, traditional fusion method cannot fully utilise correlation information between different channels and frequency components. In this paper, we design a hybrid deep learning model, in which the 'Convolutional Neural Network (CNN)' is utilised for extracting task-related features, as well as mining inter-channel and inter-frequency correlation, besides, the 'Recurrent Neural Network (RNN)' is concatenated for integrating contextual information from the frame cube sequence. Experiments are carried out in a trial-level emotion recognition task, on the DEAP benchmarking dataset. Experimental results demonstrate that the proposed framework outperforms the classical methods, with regard to both of the emotional dimensions of Valence and Arousal

The Appreciative Heart: The Psychophysiology of Positive Emotions and Optimal Functioning

This monograph is an overview of Institute of HeartMath's research on the physiological correlates of positive emotions and the science underlying two core HeartMath techniques which supports Heart-Based Living. The heart's connection with love and other positive emotions has survived throughout millennia and across many diverse cultures. New empirical research is providing scientific validation for this age-old association. This 21-page monograph offers a comprehensive understanding of the Institute of HeartMath's cutting-edge research exploring the heart's central role in emotional experience. Described in detail is physiological coherence, a distinct mode of physiological functioning, which is generated during sustained positive emotions and linked with beneficial health and performance-related outcomes. The monograph also provides steps and applications of two HeartMath techniques, Freeze-Frame(R) and Heart Lock-In(R), which engage the heart to help transform stress and produce sustained states of coherence. Data from outcome studies are presented, which suggest that these techniques facilitate a beneficial repatterning process at the mental, emotional and physiological levels

Music Therapy Techniques for Memory Stabilization in Diverse Dementias

Music contains certain unmistakable healing properties pertaining specifically to the matured body and soul affected by various types of dementia. Music therapy aids in memory retention or the retarding of the loss of mental function as a result of Alzheimer\u27s disease, Dementia with Lewy bodies, and Senile Dementia. Music can help subjects access lost memories through interaction with a music therapist. Certain music therapy techniques have been shown to yield additional physical, communicative, and psychological benefits. The disease progress of Alzheimer\u27s disease, Dementia with Lewy bodies, and Senile Dementia may be further delayed by music therapy when paired with pharmaceutical interventions such as previously established memory enhancing medications

The songwriting coalface: where multiple intelligences collide

This paper investigates pedagogy around songwriting professional practice. Particular focus is given to the multiple intelligence theory of Howard Gardner as a lens through which to view songwriting practice, referenced to recent songwriting‐specific research (e.g. McIntyre, Bennett). Songwriting education provides some unique challenges; firstly, due to the qualitative nature of assessment and the complex and multi‐faceted nature of skills necessary (lyric writing, composing, recording, and performing), and secondly, in some less‐tangible capacities beneficial to the songwriter (creative skills, and nuanced choice‐making). From the perspective of songwriting education, Gardner’s MI theory provides a ‘useful fiction’ (his term) for knowledge transfer in the domain, especially (and for this researcher, surprisingly) in naturalistic intelligence