Emotion Transfer for 3D Hand and Full Body Motion using StarGAN

In this paper, we propose a new data-driven framework for 3D hand and full-body motion emotion transfer. Specifically, we formulate the motion synthesis task as an image-to-image translation problem. By presenting a motion sequence as an image representation, the emotion can be transferred by our framework using StarGAN. To evaluate our proposed method's effectiveness, we first conducted a user study to validate the perceived emotion from the captured and synthesized hand motions. We further evaluate the synthesized hand and full body motions qualitatively and quantitatively. Experimental results show that our synthesized motions are comparable to the captured motions and those created by an existing method in terms of naturalness and visual quality

Automated early prediction of cerebral palsy: interpretable pose-based assessment for the identification of abnormal infant movements

Cerebral Palsy (CP) is currently the most common chronic motor disability occurring in infants, affecting an estimated 1 in every 400 babies born in the UK each year. Techniques which can lead to an early diagnosis of CP have therefore been an active area of research, with some very promising results using tools such as the General Movements Assessment (GMA). By using video recordings of infant motor activity, assessors are able to classify an infant’s neurodevelopmental status based upon specific characteristics of the observed infant movement. However, these assessments are heavily dependent upon the availability of highly skilled assessors. As such, we explore the feasibility of the automated prediction of CP using machine learning techniques to analyse infant motion. We examine the viability of several new pose-based features for the analysis and classification of infant body movement from video footage. We extensively evaluate the effectiveness of the extracted features using several proposed classification frameworks, and also reimplement the leading methods from the literature for direct comparison using shared datasets to establish a new state-of-the-art. We introduce the RVI-38 video dataset, which we use to further inform the design, and establish the robustness of our proposed complementary pose-based motion features. Finally, given the importance of explainable AI for clinical applications, we propose a new classification framework which also incorporates a visualisation module to further aid with interpretability. Our proposed pose-based framework segments extracted features to detect movement abnormalities spatiotemporally, allowing us to identify and highlight body-parts exhibiting abnormal movement characteristics, subsequently providing intuitive feedback to clinicians. We suggest that our novel pose-based methods offer significant benefits over other approaches in both the analysis of infant motion and explainability of the associated data. Our engineered features, which are directly mapped to the assessment criteria in the clinical guidelines, demonstrate state-of-the-art performance across multiple datasets; and our feature extraction methods and associated visualisations significantly improve upon model interpretability

Applied Cognitive Sciences

Cognitive science is an interdisciplinary field in the study of the mind and intelligence. The term cognition refers to a variety of mental processes, including perception, problem solving, learning, decision making, language use, and emotional experience. The basis of the cognitive sciences is the contribution of philosophy and computing to the study of cognition. Computing is very important in the study of cognition because computer-aided research helps to develop mental processes, and computers are used to test scientific hypotheses about mental organization and functioning. This book provides a platform for reviewing these disciplines and presenting cognitive research as a separate discipline

Postmigration

The concept of »postmigration« has recently gained importance in the context of European societies' obsession with migration and integration along with emerging new forms of exclusion and nationalisms. This book introduces ongoing debates on the developing concept of »postmigration« and how it can be applied to arts and culture. While the concept has mainly gained traction in the cultural scene in Berlin, Germany, the contributions expand the field of study by attending to cultural expressions in literature, theatre, film, and art across various European societies, such as the United Kingdom, France, Finland, Denmark, and Germany. By doing so, the contributions highlight this concept's potential and show how it can offer new perspectives on transformations caused by migration

Postmigration: Art, Culture, and Politics in Contemporary Europe

The concept of "postmigration" has recently gained importance in the context of European societies' obsession with migration and integration along with emerging new forms of exclusion and nationalisms. This book introduces ongoing debates on the developing concept of "postmigration" and how it can be applied to arts and culture. While the concept has mainly gained traction in the cultural scene in Berlin, Germany, the contributions expand the field of study by attending to cultural expressions in literature, theatre, film, and art across various European societies, such as the United Kingdom, France, Finland, Denmark, and Germany. By doing so, the contributions highlight this concept's potential and show how it can offer new perspectives on transformations caused by migration

How does virtual simulation impact on nursing students’ knowledge and self-efficacy for recognising and responding to deteriorating patients? A mixed methods study.

Background: Preparing undergraduate nursing students effectively for safe clinical practice continues to present significant challenges due to the impact of the Covid-19 pandemic, global nursing shortages, greater competition for quality clinical placements, and no guarantee that nursing students will have exposure to a deteriorating patient during their clinical placements. This is a concern because early warning signs of clinical deterioration are often not detected by nurses in a timely manner, and recognition and response to deteriorating patients is recognised globally as a major safety challenge (Haddeland et al., 2018). Aim: To explore the impact of using interactive virtual simulation case studies with facilitated debriefing (Eppich and Cheng, 2015) on nursing students’ knowledge and self-efficacy for recognising and responding to early signs of clinical deterioration in patients. Design & Methods: Mixed methods study with quasi-experimental pre/post design and focus groups. A convenience sample (n=88) final year undergraduate nursing students with half the sample at each sites randomly allocated to a treatment or control group. The treatment group received a virtual simulation intervention, debriefing, and participated in a focus group. Results: The treatment group had statistically significant higher levels of clinical self-efficacy from pre to post survey scores (65.34 and 80.12) compared to the control group (62.59 and 70.73) and significantly increased levels of knowledge in recognizing and responding to the deteriorating patient scores from pre to post survey (11.30 to 13.1) in comparison to the control group (10.33 and 9.92). Conclusions: study findings demonstrated the positive impact of a the virtual simulation intervention on knowledge and confidence of undergraduate nursing students from geographically diverse areas

The role of gesture and non-verbal communication in popular music performance, and its application to curriculum and pedagogy

Jane Davidson states that ‘the use of the body is vital in generating the technical and expressive qualities of a musical interpretation’ (2002, p. 146). Although technique and expression within music performance are separate elements, ‘they interact with, and depend upon, one another’ (Sloboda, 2000, p. 398) and, therefore, require equal consideration. Although it is possible for a musician to perform with exceptional technical prowess but little expression (Sloboda, 2000), it is important that the significance of the expressive qualities of the performer, and the ramifications of these on the delivery of the given performance, are acknowledged because whilst ‘sound is the greatest result of performance’ (Munoz, 2007, p. 56), music is not exclusively an auditory event; principally because ‘sound is essentially movement’ (Munoz, 2007, p. 56). As a performing art, music relies on the use of the physical self and body in the communicative process, and may require more than technical skill and proficient instrumental handling to be truly communicatively effective not least because, as stated by Juslin and Laukka, ‘music is a means of emotional expression' (2003, p. 774). Through a designed interdisciplinary framework, this thesis examines the use of expressive gesture and non-verbal communication skills in popular music performance, and investigates how these communicative facets can be incorporated into popular music performance education within a higher education curriculum. To do this, this work explores the practices of student and professional musicians, focusing on the areas of gesture, persona and interaction, and uses ethnographic case studies, qualitative interview processes and extracts of video footage of 3 rehearsals and live performances to investigate the importance of the physical delivery of the given musical performance. The findings from these investigations are then applied to existing educational theories to construct a pedagogical approach which will provide student musicians with the knowledge and skill to understand the implications of the art of performance through assimilated study, allowing performers to develop their own unique style of artistic expression, and creating well-rounded, empathetic, and employable musicians who have a visceral understanding of their art form

Intelligent Sensors for Human Motion Analysis

The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems