Thermal Comfort Applied in Hospital Environments: A Literature Review

Decoding influences of indoor temperature and light on neural activity: entropy analysis of electroencephalographic signals

Understanding the neural responses to indoor characteristics like temperature and light is crucial for comprehending how the physical environment influences the human brain. Our study introduces an innovative approach using entropy analysis, specifically, approximate entropy (ApEn), applied to electroencephalographic (EEG) signals to investigate neural responses to temperature and light variations in indoor environments. By strategically placing electrodes over specific brain regions linked to temperature and light processing, we show how ApEn can be influenced by indoor factors. We also integrate heart indices from a multi-sensor bracelet to create a machine learning classifier for temperature conditions. Results showed that in anterior frontal and temporoparietal areas, neutral temperature conditions yield higher ApEn values. The anterior frontal area showed a trend of gradually decreasing ApEn values from neutral to warm conditions, with cold being in an intermediate position. There was a significant interaction between light and site factors, only evident in the temporoparietal region. Here, the neutral light condition had higher ApEn values compared to blue and red light conditions. Positive correlations between anterior frontal ApEn and thermal comfort scores suggest a link between entropy and perceived thermal comfort. Our quadratic SVM classifier, incorporating entropy and heart features, demonstrates strong performance (until 90% in terms of AUC, accuracy, sensitivity, and specificity) in classifying temperature sensations. This study offers insights into neural responses to indoor factors and presents a novel approach for temperature classification using EEG entropy and heart features.

Assessment of indoor thermal comfort temperature and related behavioural adaptations: a systematic review

Thermal comfort is linked to our health, well-being, and productivity. The thermal environment is one of the main factors that influence thermal comfort and, consequently, the productivity of occupants inside buildings. Meanwhile, behavioural adaptation is well known to be the most critical contributor to the adaptive thermal comfort model. This systematic review aims to provide evidence regarding indoor thermal comfort temperature and related behavioural adaptation. Studies published between 2010 and 2022 examining indoor thermal comfort temperature and behavioural adaptations were considered. In this review, the indoor thermal comfort temperature ranges from 15.0 to 33.8 °C. The thermal comfort temperature range varied depending on several factors, such as climatic features, ventilation mode, type of buildings, and age of the study population. Elderly and younger children have distinctive thermal acceptability. Clothing adjustment, fan usage, AC usage, and open window were the most common adaptive behaviour performed. Evidence shows that behavioural adaptations were also influenced by climatic features, ventilation mode, type of buildings, and age of the study population. Building designs should incorporate all factors that affect the thermal comfort of the occupants. Awareness of practical behavioural adaptations is crucial to ensure occupants' optimal thermal comfort.

Monitoring of Thermal Comfort and Air Quality for Sustainable Energy Management inside Hospitals Based on Online Analytical Processing and the Internet of Things

There is a need to ensure comfortable conditions for hospital staff and patients from the point of view of thermal comfort and air quality so that they do not affect their performance. We consider the need for hospital employees and patients to enjoy conditions of greater well-being during their stay. This is understood as a comfortable thermal sensation and adequate air quality, depending on the task they are performing. The contribution of this article is the formulation of the fundamentals of a system and platform for monitoring thermal comfort and Indoor Air Quality (IAQ) in hospitals, based on an Internet of Things platform composed of a low-cost sensor node network that is capable of measuring critical variables such as humidity, temperature, and Carbon Dioxide (CO₂). As part of the platform, a multidimensional data model with an On-Line Analytical Processing (OLAP) approach is presented that offers query flexibility, data volume reduction, as well as a significant reduction in query response times. The experimental results confirm the suitability of the platform's data model, which facilitates operational and strategic decision making in complex hospitals.

A Review of Recent Literature on Systems and Methods for the Control of Thermal Comfort in Buildings

Thermal comfort in indoor environments is perceived as an important factor for the well-being and productivity of the occupants. To practically create a comfortable environment, a combination of models, systems, and procedures must be applied. This systematic review collects recent studies proposing complete thermal-comfort-based control strategies, extracted from a scientific database for the period 2017–2021. The study consists of this paper and of a spreadsheet recording all the 166 reviewed works. After a general introduction, the content of the papers is analyzed in terms of thermal comfort models, indoor environment control strategies, and correlation between these two aspects. Practical considerations on scope, required inputs, level of readiness, and, where available, estimated cost are also given. It was found that the predicted mean vote is the preferred thermal comfort modeling approach, followed by data-driven and adaptive methods. Thermal comfort is controlled mainly through indoor temperature, although a wide range of options are explored, including the comfort-based design of building elements. The most popular field of application of advanced control strategies is office/commercial buildings with air conditioning systems, which can be explained by budget and impact considerations. The analysis showed that few works envisaging practical implementations exist that address the needs of vulnerable people. A section is, therefore, dedicated to this issue.

A Study on Flow Field Characteristics and Air Purifier with Barrier Effects

An air curtain machine is used in the entrances and exits of public places where air conditioners are used. The high-speed centrifugal or axial fan blows out the air, creating an airflow barrier to prevent air convection inside and outside, reducing air conditioning losses, and maintaining the indoor air quality by preventing dust, insects, and harmful gases from entering the room. Observation of the airflow behavior was conducted using CFD simulation, to explore whether it has a blocking effect, and the air curtain principle was applied to the air purification equipment. It is mainly composed of several rows of arrayed hole air outlets to form a multi-composite air wall. The airflow on the two sides, or below, can be blocked by the composite air wall and integrated into the main airflow, so that the air walls will not affect each other, and form a barrier effect to prevent infection. This research includes the measurement of impedance characteristics for three layers of filters made of different materials. These filters are used as the input characteristic parameters in the simulation analysis. Four scenarios are discussed, including the consultation room, hospital ward, quarantine station, and conference room. From the simulation results, it is known that when there are many people, the equipment can be set to high speed to increase the volume of air, forming a wind wall to effectively block airflow from the people in the chairs, reducing the risk of infection. Note that the rotation speed should not be too high. The air outlet equipment is susceptible to turbulent flow, which will make the airflow deviate from the expected direction and increase the possibility of mutual infection between adjacent people. Partitions can be used to block airflow to reduce the risk of infection.

Evaluation of Comfort Models Considering the Peculiarities of Hospitalization: Bedding, Clothing and Reduced Activity of Patients

The study of thermo-hygrometric comfort in hospitals involves several factors: the presence of different subjects: patients, operators, visitors; different conditions of hospitalization: patients bedridden or out of bed; psychological aspects and therapeutic treatments. In this paper, the analysis focuses on patients in ordinary hospitalization rooms of a hospital located in southern Italy. Different room orientations, several characteristics, and specific factors concerning hospitalized patients’ conditions that significantly influence the comfort indices have been considered. In total, 41 scenarios have been defined and analyzed by means of two comfort models: static and adaptive. The study aims to investigate the application of these models to the complex environment of hospitals, finding strengths and weaknesses, which also results in a re-definition of the HVAC system operation. Results show that patient position (in bed or out), clothing type, and level of coverage in the bed can make the same microclimatic condition more suitable for one scenario over another. Furthermore, room exposure has an effect on the comfort of the indoor temperature. The seasonal analyses highlight that during summer, for all scenarios considering bedridden patients, more than 50% of the PMV calculated values are out of the comfort zone. In winter, the indoor conditions are good for bedridden patients with a cover level of 67% during the nighttime (almost 100% PMV values in comfort zone), while during the daytime, they are more suitable for a 48% coverage level if the patient is in bed or if they are walking (lower than 10% dissatisfied).

Experimental Investigation of Adaptive Thermal Comfort in French Healthcare Buildings

The thermal comfort requirements of disabled people in healthcare buildings are an important research topic that concerns a specific population with medical conditions impacted by the indoor environment. This paper experimentally investigated adaptive thermal comfort in buildings belonging to the Association of Parents of Disabled Children, located in the city of Troyes, France, during the winter season. Thermal comfort was evaluated using subjective measurements and objective physical parameters. The thermal sensations of respondents were determined by questionnaires adapted to their disability. Indoor environmental parameters such as relative humidity, mean radiant temperature, air temperature, and air velocity were measured using a thermal microclimate station during winter in February and March 2020. The main results indicated a strong correlation between operative temperature, predicted mean vote, and adaptive predicted mean vote, with the adaptive temperature estimated at around 21.65 °C. These findings highlighted the need to propose an adaptive thermal comfort strategy. Thus, a new adaptive model of the predicted mean vote was proposed and discussed, with a focus on the relationship between patient sensations and the thermal environment.

A Study of Workspace Design Characteristics Exemplified by Nurses' Satisfaction Within Three Intensive Care Units in a University Hospital

BACKGROUND

The critical conditions of intensive care patients require providing them with a higher acuity of care. Thus, it is essential to focus on critical care nurses and improve their work environment in a way that maximizes productivity, collaboration, satisfaction, and leads to improved patient care.

PURPOSE

This study aims to explore the role the workplace layout design play in determining nurses' satisfaction in three intensive care units (ICUs) at a university hospital.

METHOD

A prospective, cross-sectional, single-center, survey-based design was employed in this study. Data were obtained, via a standardized questionnaire, from 36 morning shift nurses. The nurses' self-reported satisfaction scores in three different ICUs with differing overall layouts, nursing station locations, and workplace design were statistically compared.

RESULTS

The study found that ICU 1 (private rooms, single corridor, central nursing station, close to supported services) had higher nursing satisfaction levels than ICUs 2 and 3 (open wards with separate service zones), F _(2,34) = 5.054, p = .012. However, overall satisfaction was higher with the ICU 2 primary workspace design, possibly due to the perceived acoustic privacy in this configuration, F _(2,34)= 4.492, p = .019. The ability of the ICU layout design to enhance teamwork and minimize traffic in patients care areas was found to be an important predictor of nurses' satisfaction. The primary workspace design capacity to minimize congestion and the presence of large numbers of providers in a confined workplace might account for variation in nurses' satisfaction.

CONCLUSION

Physical environment variables in the ICU design may contribute to staff workplace satisfaction scores and may help in guiding informed choices regarding the future ICU design.

How Can We Adapt Thermal Comfort for Disabled Patients? A Case Study of French Healthcare Buildings in Summer

This paper investigates adaptive thermal comfort during summer in medical residences that are located in the French city of Troyes and managed by the Association of Parents of Disabled Children (APEI). Thermal comfort in these buildings is evaluated using subjective measurements and objective physical parameters. The thermal sensations of respondents were determined by questionnaires, while thermal comfort was estimated using the predicted mean vote (PMV) model. Indoor environmental parameters (relative humidity, mean radiant temperature, air temperature, and air velocity) were measured using a thermal environment sensor during the summer period in July and August 2018. A good correlation was found between operative temperature, mean radiant temperature, and PMV. The neutral temperature was determined by linear regression analysis of the operative temperature and Fanger’s PMV model. The obtained neutral temperature is 23.7 °C. Based on the datasets and questionnaires, the adaptive coefficient α representing patients’ capacity to adapt to heat was found to be 1.261. A strong correlation was also observed between the sequential thermal index n(t) and the adaptive temperature. Finally, a new empirical model of adaptive temperature was developed using the data collected from a longitudinal survey in four residential buildings of APEI in summer, and the obtained adaptive temperature is 25.0 °C with upper and lower limits of 24.7 °C and 25.4 °C.