Linking Audience Physiology to Choreography

The clothing comfort sensation is a combination of complex components, including psychological and physiological responses. General linear analysis is not always sufficient for the evaluation of the clothing comfort sensation. The current study sought to predict the clothing comfort sensation of wearing an undershirt using an artificial neural network (ANN). We constructed ANN models with psychological sensation data and physiological response data as inputs, including electrocardiogram and thermo-physiological indicators, and the clothing comfort sensation as the output. For the input layer of the model, three conditions were used: the psychological response data only, the physiological response data only, and both the psychological and physiological data. The number of hidden layers in the models ranged from one to three, and the number of units in each hidden layer was changed when fixed values of 30, 60, and 90 were used, or according to the number of data points in the input conditions. The results revealed that, among the three conditions, the accuracy rate was higher when both psychological and physiological response data were used as input. The prediction results exhibited an accuracy rate of up to 85% for unknown test data. The results suggest that the method of evaluating the state of clothing comfort sensation when wearing an undershirt using psychophysiological response measurement was effective and that neural networks are useful for predicting the clothing comfort sensation.

Biosensing technologies, which monitor physiological responses such as Heart Rate Variability (HRL), Skin Conductance Level (SCL), and Electroencephalogram (EEG) activity, offer a novel approach to enhancing the dissemination of health information in ideological and political education (IPE). In this context, health information encompasses topics such as mental health, stress management, and healthy lifestyle practices, all crucial to students’ overall well-being. Traditional health education methods cannot often capture real-time physiological and emotional responses, which can improve engagement and learning outcomes. This research explores the effectiveness of biosensing technology in enhancing the dissemination of health information within IPE. It examines how physiological data can be utilized to assess student engagement, emotional responses, and learning outcomes related to health. A mixed-methods approach was adopted, combining quantitative data from wearable biosensors (heart rate monitors, Galvanic Skin Response (GSR) sensors, EEG headsets) with qualitative feedback from students. Physiological data were preprocessed using signal filtering techniques, such as the Savitzky-Golay Filter, and features such as heart rate variability, skin conductance, and EEG alpha waves were extracted using the Kalman Filter (KF). A Modified Runge-Kutta Optimizer Integrated with Deep Belief Networks (MRKO-DBN) classifier was employed to predict student engagement based on these features. The research revealed that physiological responses, particularly heart rate variability and skin conductance, were strongly correlated with student engagement. The MRKO-DBN model achieved accuracy in predicting engagement. Qualitative feedback further confirmed that Biosensing technology significantly improved students’ engagement. Integrating Biosensing technology into health education within ideological and political contexts offers significant potential for enhancing student engagement and learning outcomes. By providing real-time, personalized feedback, it fosters a more interactive and responsive learning environment.

Gynecologic oncology patients undergo complex operations with high rates of postoperative complication. Frailty is consistently associated with complication but is not routinely measured in clinical practice. This study aimed to examine the association of physiologic and activity data with frailty and postoperative complications in presurgical gynecologic oncology patients. We performed a prospective cohort study of gynecologic oncology surgery patients who wore wearable actigraphy rings before and after surgery from 03/2021-11/2023. Exposures were physiologic data (heart and respiratory rates, heart rate variability), preoperative activity intensity and level. Primary outcomes included frailty (Pajewski frailty score) and 30-day complications. Multivariable models were adjusted for age, cancer and surgery type. We enrolled 96 patients and 87 met inclusion criteria. 41.3% were not frail, 44% were pre-frail and 14.7% were frail. Average heart rate and respiratory rate differed between frail and non-frail patients (HR 78.6 vs 68.3bpm, aOR=1.10,95%CI1.01-1.20; RR 18.6 vs 16.7b/m,aOR=2.1,95%CI1.20–3.55). Heart rate variability (RMSSD) also differed (24 vs 30.9ms,aOR=0.81,95%CI0.68-0.97). Preoperative physical activity was also associated with postoperative complications. Overall, 29.9% experienced a complication and higher activity was associated with fewer complications: 500-1000 MET-mins (OR=0.26,95%CI=0.07-0.92) and >1000 MET-mins (OR=0.25,95%CI=0.07-0.94) vs <500 MET-mins; ≥8000 steps (OR=0.25,95%CI=0.08-0.73) vs <8000 steps. In conclusion, physiologic data and activity levels differ in frail compared to not frail patients independent of age. Wearable devices may be useful in the preoperative assessment of frailty. Furthermore, higher preoperative activity levels are associated with fewer postoperative complications. Physical activity may be a modifiable risk factor for adverse postoperative outcomes.

BACKGROUND Staffing and resource shortages, especially during the COVID-19 pandemic, have increased stress levels among health care workers. Many health care workers have reported feeling unable to maintain the quality of care expected within their profession, which, at times, may lead to moral distress and moral injury. Currently, interventions for moral distress and moral injury are limited. OBJECTIVE This study has the following aims: (1) to characterize and reduce stress and moral distress related to decision-making in morally complex situations using a virtual reality (VR) scenario and a didactic intervention; (2) to identify features contributing to mental health outcomes using wearable, physiological, and self-reported questionnaire data; and (3) to create a personal digital phenotype profile that characterizes stress and moral distress at the individual level. METHODS This will be a single cohort, pre- and posttest study of 100 nursing professionals in Ontario, Canada. Participants will undergo a VR simulation that requires them to make morally complex decisions related to patient care, which will be administered before and after an educational video on techniques to mitigate distress. During the VR session, participants will complete questionnaires measuring their distress and moral distress, and physiological data (electrocardiogram, electrodermal activity, plethysmography, and respiration) will be collected to assess their stress response. In a subsequent 12-week follow-up period, participants will complete regular assessments measuring clinical outcomes, including distress, moral distress, anxiety, depression, and loneliness. A wearable device will also be used to collect continuous data for 2 weeks before, throughout, and for 12 weeks after the VR session. A pre-post comparison will be conducted to analyze the effects of the VR intervention, and machine learning will be used to create a personal digital phenotype profile for each participant using the physiological, wearable, and self-reported data. Finally, thematic analysis of post-VR debriefing sessions and exit interviews will examine reoccurring codes and overarching themes expressed across participants’ experiences. RESULTS The study was funded in 2022 and received research ethics board approval in April 2023. The study is ongoing. CONCLUSIONS It is expected that the VR scenario will elicit stress and moral distress. Additionally, the didactic intervention is anticipated to improve understanding of and decrease feelings of stress and moral distress. Models of digital phenotypes developed and integrated with wearables could allow for the prediction of risk and the assessment of treatment responses in individuals experiencing moral distress in real-time and naturalistic contexts. This paradigm could also be used in other populations prone to moral distress and injury, such as military and public safety personnel. CLINICALTRIAL ClinicalTrials.gov NCT05923398; https://clinicaltrials.gov/study/NCT05923398 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/54180

Introduction: Virtual-reality (VR) technology has, over the last decade, quickly expanded from gaming into other sectors including training, education, and wellness. One of the most popular justifications for the use of VR over 2D is increased immersion and engagement. However, very little fundamental research has been produced evaluating the comparative impact of immersive VR on the user’s cognitive, physiological, and emotional state.Methods: A within-subject cross-over study design was used to directly compare VR and 2D screen delivery of different subject matter content. Both physiological and self-report data were collected for scenes containing calming nature environments, aggressive social confrontations, and neutral content.Results: Compared to 2D, the VR delivery resulted in a higher sense of presence, higher ratings of engagement, fun, and privacy. Confrontational scenes were rated as more tense whilst calming scenes were rated as more relaxing when presented in VR compared to 2D. Physiological data indicated that the scenes promoted overall states of arousal and relaxation in accordance with the scene subject matter (both VR and 2D). However, heart rate (HR) and galvanic skin response (GSR) were consistently higher throughout the VR delivery condition compared to 2D, including responses during scenes of neutral and calming subject matter.Discussion: This discrepancy between emotional and physiological responses for calming and neutral content in VR suggest an elevated arousal response driven by VR immersion that is independent of the emotional and physiological responses to the subject matter itself. These findings have important implications for those looking to develop and utilize VR technology as a training and educational tool as they provide insights into the impact of immersion on the user.

This study's purpose is to introduce a new measurement system that objectively assesses the social validity of behavioral feeding intervention from the child's perspective via the concurrent measurement of two dimensions of emotion. To date, the primary measures of social validity for behavioral feeding intervention are caregiver treatment acceptability and satisfaction surveys. This is the first study to objectively measure two dimensions of emotion, physiological arousal and emotional valence, while children received behavioral intervention for feeding difficulties. Data collectors used a new open‐source data collection software, cometrics, developed to synchronize and record physiological and observational data. Physiological data was collected using a wearable biosensor and observers recorded an index of child happiness, unhappiness, or neither using definitions by Phipps et al. (2022) for six children with a pediatric feeding disorder. Two out of six children needed programmed habituation to the device before data collection. All children assented to wearing the device during data collection. Recorded indices mapped to separable physiological states using electrodermal activity and its constituent components, skin conductance responses and skin conductance level, in addition to skin temperature. Findings demonstrated the feasibility of measuring two dimensions of child emotions during behavioral feeding intervention and revealed that children's physiological responses were distinctly different during intervals scored as happy, unhappy, or neither. This new data collection system has implications for future research on the child's emotional experience of behavioral feeding treatment and increases the possibilities for improving clinical practice.

A pragmatic breath-based intervention to benefit human performance and stress management is timely and valuable to individuals seeking holistic approaches for emotional regulation and optimizing compensatory reserve mechanisms. This protocol is designed to not only teach mind-body awareness but also to provide feedback utilizing physiological data and survey results. The primary findings of this study showed that heart coherence and alpha variables were significantly correlated after four weeks of the breath-based meditation stress protocol. Meditation and rhythmic breathing produced significant increases in alpha brain activity. These brain physiological responses conformed to the Pleth Variability Index (PVI) changes, suggesting the ability of the human body to enter into a meditative state and effectively manage stress. When assessed after four weeks of daily practicing the techniques employed in the stress management protocol, based on the Five Facet Mindfulness Questionnaire, subjects improved in applying mindfulness skills. The overall mindfulness score, Pleth variability index (PVI), and perfusion index (PI) increased after the 4-week intervention period. Results from electroencephalography (brain waves) were consistent with a meditative state during the post-study follow-up session. This provides evidence that wearable devices are feasible for data collection during a breath-based stress management intervention. This protocol can be easily and efficiently implemented into any study design in which physiological data are desired in a non-laboratory-based setting.

Occupant-centered indoor environmental quality management: Physiological response measuring methods

Mental stress is a prevalent issue in modern society, and detecting and classifying it accurately is crucial for effective interventions and treatment plans. This study aims to compare various machine learning (ML) algorithms for detecting mental stress using wearable physiological signal data and proposes a novel model that is automatic, high-performing, low-cost, and with lower time and computation complexity. The proposed model was trained and tested on a dataset of 200 participants, which involves applying four different stressors. Nine ML algorithms were investigated for both multivariate and univariate features. The physiological data was collected using a novel device developed using an Arduino microcontroller and low-cost sensors such as ECG, GSR, and ST sensors. The findings reveal that the suggested model detects mental stress with an accuracy of 96.17%, with the XGBoost method outperforming other algorithms in multivariate analysis. Univariate feature analysis found that XGBoost regularly demonstrated good accuracy, showing its dependability for detecting mental stress. The novel device created using low-cost sensors and automatic, high-performing algorithms is an effective and accessible tool for mental stress detection. Additionally, benchmark dataset validation (SWELL-KW, WESAD) confirmed the model’s robustness with accuracies of 92.38% and 94.21% respectively. A real-time pilot test on ten new participants utilizing the developed device validated the model’s practical value, with 97.5% classification accuracy and low latency. This study provides insights into the most effective ML algorithms for mental stress detection and creates a comprehensive and reliable resource for future research.

In recent years, stress-monitoring innovations using wearable technology have entered the market. One innovation is biocueing, a process where patients receive real-time feedback on passive monitoring of significant changes in their physiological data, such as (additional) heart rate, heart rate variability or skin conductance. This technology offers potential for patients with borderline personality disorder, as they often report severe stress, difficulties in emotion regulation and low levels of emotional- and body awareness. Yet, currently there is no clear direction on when and how to fit these technologies, and physiology in general, into treatments for borderline personality disorder. We provide a comprehensive review on how and to what extent evidence-based treatments (Transference Focused Psychotherapy, Mentalization Based Treatment, Schema Therapy, Dialectical Behavior Therapy), and their underpinning theories provide guidance and predictions for integrating these technologies. Only Dialectical Behavior Therapy provide a theoretical framework that includes physiology, as well as interventions that actively target physiological data, whereas the other evidence-based treatments largely disregard physiology. Other promising developments are Creative Arts and Psychomotor Therapies and the Polyvagal theory, as they target bodily sensations and physiology more directly. Four avenues for future research and integration of psychophysiological theory and wearable technology in treatment are discussed: abandoning physiological data and technology, keeping a human in the loop, machine-learning biocueing interventions, or biomonitoring devices as long-term (mental) health monitors.

Analysis of multimodal physiological signals within and between individuals to predict psychological challenge vs. threat

Mobile projection interfaces are no longer fiction. Integrated pico projectors in mobile and wearable devices could make mobile projection ubiquitous within the next few years and create commonplace practices where walls, desks, floors, and t-shirts act as projection surfaces for these kinds of new devices. Several projector phones— mobile phones with built-in projectors—are commercially available, have been demonstrated or are announced [5]. It is expected that such projector phones will be integrated in many of the next generation mobile handsets. Furthermore, we have seen the first research toward the integration of pico projectors and cameras into various wearable systems, such as stand-alone personal projectors [4], watches [2], pendants [3], or headsets [6], leading to new form factors, interaction techniques, and applications. These mobile projection units, often equipped with a camera or other additional sensors for tracking input, have a great potential to overcome the limited input and output capabilities of mobile and wearable devices. They can be expected to have a significant impact on the cultural usage habits of content consumption and media sharing. This makes mobile projectors an interesting and important platform for research in the area of Human–Computer Interaction. Current research in this field mainly focuses on the design, development, and evaluation of novel interaction techniques and applications, on the study of how this technology is used in realistic contexts and how it affects the usage of mobile and wearable devices. In addition, new sensing and tracking methods are being investigated in order to support novel ways of interaction and emerging applications. Therefore, we are still at the beginning of understanding and addressing the multifaceted challenges of this emerging research area of Human–Computer Interaction. Of course, mobile projectors have been used in various other research disciplines for a couple of years. As the first paper of this special issue vividly shows, their history even goes back to the seventeenth century, where ‘‘magic lanterns’’ provided early forms of mobile projection. More recently, previous research has focused on technical aspects, such as hardware construction, optics, projection geometry [1], energy consumption, and interaction with projected multi-scale user interfaces [4]. Through continuous miniaturization, these devices have now reached form factors that allow us to focus on HCI research in the context of realistic pervasive environments, such as mobile settings. This theme issue on personal projection is a follow-up of the successful Ubiprojection 2010 workshop being held in conjunction with the Pervasive 2010 conference in E. Rukzio (&) University of Duisburg-Essen, Essen, Germany e-mail: Enrico.Rukzio@uni-due.de

First responders are specialty teams who are trained to work in toxic environments to assess and diffuse the threat. They have to wear specially designed Personal Protective Ensembles (PPE) that is impermeable to liquids and gasses. Microclimate inside PPEs gets hot and humid, rapidly rendering it uncomfortable and often hazardous to work longer than 30 minutes at a time. Providing active cooling is one way to extend the time spent in PPEs. Two water-cooled prototype garments were developed at our department. This study focused on the evaluation of the prototype cooling garments using human subjects, performing simulated tasks in an environmental chamber. Both physiological and perceptual responses were considered to understand the garment's effectiveness in providing cooling relief as well as the user acceptance in terms of ease of use, comfort and perceived effectiveness. The subjects' perception of cooling relief generally agreed with the physiological data. The two prototype cooling vests positively affected skin temperatures, sweat rate, microclimate temperature, humidity, perceived temperature and perceived humidity. Both physiological and perception data indicated there were no significant and consistent differences between the two cooling vests. The subjects perceived the prototype cooling garments to provide effective cooling, to be attractive and practical overall.

We first describe the process of working on creative problems using three different but related approaches: Art, Design and Human Computer Interaction research. We present case studies of two interactive artworks; Magic Hopscotch and Cities Tango: Melbourne/Sydney, and explain how engagement with those works has informed our further practice in art, design and HCI. We consider how HCI research can influence art and design, and how art and design can influence HCI research, thereby making some kinds of decisions more explicit, supporting stronger hypothesis generation and crucially enriching evaluation methods for creativity support tools.

Background Informed consent processes in critical care trials can be overwhelming for patients and their families as decisions about participation need to be made under distressing circumstances. Existing consent processes have been developed for and by White Western populations, making them less relevant for racialized groups from low- and middle-income countries. One solution is involving patients, their relatives and members of the public from diverse backgrounds in co-designing informed consent processes. Methods This project aims to co-design the consent materials and processes for two ongoing critical care trials with an existing Patient and Public Involvement and Engagement group at Ziauddin University in Pakistan. Using experience-based co-design and participatory action research, the process will follow six stages for each trial: (i) Introduction to trial and consent, (ii) Review of existing materials, (iii) Process mapping & recommendations, (iv) Creation of new materials, (v) Vetting, and (vi) Finalization. The final two steps involve collaboration with clinicians, trial teams, sponsors, and members of ethics review boards. Expected Outcomes The co-design process will produce new consent materials, aligned with patient and substitute decision-maker needs, that can be implemented to improve the conduct of two active trials. Deliverables include an informed consent process map, recommendations for revising consent materials, and guidelines on patient-centred formats. Additionally, training patient and public members in co-design will build capacity and enable the group to contribute to the design of consent processes of future trials. Conclusion Collaboration between patients, researchers and the public has the potential to promote ethical conduct of critical care trials in Pakistan and elsewhere by supporting patient-centered informed decision-making. This co-design process represents the first step towards achieving this goal, with future work evaluating the impact of the new consent materials and processes on trial enrolment rates, participant diversity and consent experiences.