Evaluation of the Visual Stimuli on Personal Thermal Comfort Perception in Real and Virtual Environments Using Machine Learning Approaches

Flexible and Stretchable Light-Emitting Diodes and Photodetectors for Human-Centric Optoelectronics

Optoelectronic devices with unconventional form factors, such as flexible and stretchable light-emitting or photoresponsive devices, are core elements for the next-generation human-centric optoelectronics. For instance, these deformable devices can be utilized as closely fitted wearable sensors to acquire precise biosignals that are subsequently uploaded to the cloud for immediate examination and diagnosis, and also can be used for vision systems for human-interactive robotics. Their inception was propelled by breakthroughs in novel optoelectronic material technologies and device blueprinting methodologies, endowing flexibility and mechanical resilience to conventional rigid optoelectronic devices. This paper reviews the advancements in such soft optoelectronic device technologies, honing in on various materials, manufacturing techniques, and device design strategies. We will first highlight the general approaches for flexible and stretchable device fabrication, including the appropriate material selection for the substrate, electrodes, and insulation layers. We will then focus on the materials for flexible and stretchable light-emitting diodes, their device integration strategies, and representative application examples. Next, we will move on to the materials for flexible and stretchable photodetectors, highlighting the state-of-the-art materials and device fabrication methods, followed by their representative application examples. At the end, a brief summary will be given, and the potential challenges for further development of functional devices will be discussed as a conclusion.

Is it getting hot in here? The effects of VR headset microclimate temperature on perceived thermal discomfort, VR sickness, and skin temperature

Thermal discomfort is a driver of negative user experiences with modern VR headsets since they are similar to head-worn gaming computers. Here, we examined the effect of microclimate temperature (MCT; i.e., the air between headset and user) and the effect of standing and seated use on thermal discomfort for a goggle style headset. Users played VR games across three 48-min sessions with different thermal profiles ranging between 28°-43 °C. Perceived thermal and weight discomfort were rated by participants every 12-min. Thermal, but not weight comfort declined during the study period as MCT increased. Users sweat more and had greater forehead temperatures while standing with the lowest thermal profile, suggesting thermal management is more critical for active experiences. Overall, this study recommends MCT should be kept below 36 °C. Finally design for thermal comfort should be tailored to the individual, experience duration and activity level.

The effects of manipulating the visual environment on thermal perception: A structured narrative review

When exposed to ambient temperatures that cause thermal discomfort, a human's behavioral responses are more effective than autonomic ones at compensating for thermal imbalance. These behavioral thermal responses are typically directed by an individual's perception of the thermal environment. Perception of the environment is a holistic amalgamation of human senses, and in some circumstances, humans prioritize visual information. Existing research has considered this in the specific case of thermal perception, and this review investigates the state of the literature examining this effect. We identify the frameworks, research rationales, and potential mechanisms that underpin the evidence base in this area. Our review identified 31 experiments, comprising 1392 participants that met the inclusion criteria. Methodological heterogeneity was observed in the assessment of thermal perception, and a variety of methods were employed to manipulate the visual environment. However, the majority of the included experiments (80%) reported a difference in thermal perception after the visual environment was manipulated. There was limited research exploring any effects on physiological variables (e.g. skin and core temperature). This review has wide-ranging implications for the broad discipline of (thermo)physiology, psychology, psychophysiology, neuroscience, ergonomics, and behavior.

Impact of Outdoor Temperature Variations on Thermal State in Experiments Using Immersive Virtual Environment

Recent studies have established immersive virtual environments (IVEs) as promising tools for studying human thermal states and human–building interactions. One advantage of using immersive virtual environments is that experiments or data collection can be conducted at any time of the year. However, previous studies have confirmed the potential impact of outdoor temperature variations, such as seasonal variations on human thermal sensation. To the best of our knowledge, no study has looked into the potential impact of variations in outdoor temperatures on experiments using IVE. Thus, this study aimed to determine if different outdoor temperature conditions affected the thermal states in experiments using IVEs. Experiments were conducted using a head mounted display (HMD) in a climate chamber, and the data was analyzed under three temperature ranges. A total of seventy-two people participated in the experiments conducted in two contrasting outdoor temperature conditions, i.e., cold and warm outdoor conditions. The in situ experiments conducted in two cases, i.e., cooling in warm outdoor conditions and heating in cold outdoor conditions, were used as a baseline. The baseline in-situ experiments were then compared with the IVE experiments conducted in four cases, i.e., cooling in warm and cold outdoor conditions and heating in warm and cold outdoor conditions. The selection of cooling in cold outdoor conditions and heating in warm outdoor conditions for IVE experiments is particularly for studying the impact of outdoor temperature variations. Results showed that under the experimental and outdoor temperature conditions, outdoor temperature variations in most cases did not impact the results of IVE experiments, i.e., IVE experiments can replicate a temperature environment for participants compared to the ones in the in situ experiments. In addition, the participant’s thermal sensation vote was found to be a reliable indicator between IVE and in situ settings in all studied conditions. A few significantly different cases were related to thermal comfort, thermal acceptability, and overall skin temperature.

The R Language as a Tool for Biometeorological Research

R is an open-source programming language which gained a central place in the geosciences over the last two decades as the primary tool for research. Now, biometeorological research is driven by the diverse datasets related to the atmosphere and other biological agents (e.g., plants, animals and human beings) and the wide variety of software to handle and analyse them. The demand of the scientific community for the automation of analysis processes, data cleaning, results sharing, reproducibility and the capacity to handle big data brings a scripting language such as R in the foreground of the academic universe. This paper presents the advantages and the benefits of the R language for biometeorological and other atmospheric sciences’ research, providing an overview of its typical workflow. Moreover, we briefly present a group of useful and popular packages for biometeorological research and a road map for further scientific collaboration on the R basis. This paper could be a short introductory guide to the world of the R language for biometeorologists.

Correlation between Indoor Environmental Data and Biometric Parameters for the Impact Assessment of a Living Wall in a ZEB Lab

Users' satisfaction in indoor spaces plays a key role in building design. In recent years, scientific research has focused more and more on the effects produced by the presence of greenery solutions in indoor environments. In this study, the Internet of Things (IoT) concept is used to define an effective solution to monitor indoor environmental parameters, along with the biometric data of users involved in an experimental campaign conducted in a Zero Energy Building laboratory where a living wall has been installed. The growing interest in the key theory of the IoT allows for the development of promising frameworks used to create datasets usually managed with Machine Learning (ML) approaches. Following this tendency, the dataset derived by the proposed infield research has been managed with different ML algorithms in order to identify the most suitable model and influential variables, among the environmental and biometric ones, that can be used to identify the plant configuration. The obtained results highlight how the eXtreme Gradient Boosting (XGBoost)-based model can obtain the best average accuracy score to predict the plant configuration considering both a selection of environmental parameters and biometric data as input values. Moreover, the XGBoost model has been used to identify the users with the highest accuracy considering a combination of picked biometric and environmental features. Finally, a new Green View Factor index has been introduced to characterize how greenery has an impact on the indoor space and it can be used to compare different studies where green elements have been used.