The rapid development of artificial intelligence (AI) has significantly transformed human-computer interactions, making it essential to establish robust design standards to ensure effective, ethical, and human-centered AI (HCAI) solutions. Standards serve as the foundation for the adoption of new technologies, and human-AI interaction (HAII) standards are critical to supporting the industrialization of AI technology by following an HCAI approach. These design standards aim to provide clear principles, requirements, and guidelines for designing, developing, deploying, and using AI systems, enhancing the user experience and performance of AI systems. Despite their importance, the creation and adoption of HCAI-based interaction design standards face challenges, including the absence of universal frameworks, the inherent complexity of HAII, and the ethical dilemmas that arise in such systems. This chapter provides a comparative analysis of HAII versus traditional human-computer interaction (HCI) and outlines guiding principles for HCAI-based design. It explores international, regional, national, and industry standards related to HAII design from an HCAI perspective and reviews design guidelines released by leading companies such as Microsoft, Google, and Apple. Additionally, the chapter highlights tools available for implementing HAII standards and presents case studies of human-centered interaction design for AI systems in diverse fields, including healthcare, autonomous vehicles, and customer service. It further examines key challenges in developing HAII standards and suggests future directions for the field. Emphasizing the importance of ongoing collaboration between AI designers, developers, and experts in human factors and HCI, this chapter stresses the need to advance HCAI-based interaction design standards to ensure human-centered AI solutions across various domains.

As more and more products and services are integrated into artificial intelligence, the interaction between humans and intelligent systems is becoming increasingly common. The interaction between humans and intelligent systems has put forward new requirements for human-computer interface design. Traditional human-computer interfaces are mainly based on the "stimulus-response" mode of "instruction sequence" interaction. The autonomous features of intelligent systems, such as situational awareness, intention recognition, autonomous learning, autonomous decision-making, and automatic execution, bring a new type of human-computer interaction mode. Humans can interact with systems in a more natural way. The intelligent human-computer interaction standards are an important support for the industrialization of artificial intelligence technology. This paper provides an overview of the international standards and China national standards for intelligent human-computer interaction. It outlines the intelligent human-computer interaction guidelines released by Microsoft, Google, and Apple. The development trend of intelligent human-computer interaction standards is discussed, in order to provide an analytical basis for the development of new standards and facilitate the construction of better intelligent systems.

Accurate identification of individual thermal states is an important basis for meeting the diverse demands of occupants and achieving user-centric thermal environment control. Developing Personal Comfort Model (PCM) by measuring skin temperature with infrared thermography enables effective thermal sensation prediction. However, existing research is typically conducted under uniform clothing conditions. This experimental design does not consider the differences in clothing between occupants and autonomous clothing adjustment behaviors in real-world scenarios, which limits the application potential of the prediction model based on experimental data. In this study, we conducted experiments in a climate chamber to collect clothing-uncovered skin temperatures (face, neck, arms, and wrists) and subjective evaluation under different clothing insulation (0.35, 0.51, 0.76, 1.01 clo). Statistical analysis and modeling analysis were performed by combining subjective evaluations, skin temperatures, and environmental parameters. The result shows that clothing changes can be reflected in the skin temperature at clothing-uncovered areas, and skin temperature is consistent with thermal sensation. On this basis, the machine learning algorithms were used to evaluate the performance of the thermal sensation prediction model under different combinations of input parameters. The model constructed with artificial neural network algorithm achieved a prediction accuracy of 76.8 % using only nose temperature and air temperature as inputs while clothing information is not included. This represents an approximately 5 % improvement over the PMV model, which requires clothing insulation as an input. This study demonstrates the generalizability of using physiological parameters to predict thermal sensation, providing the theoretical foundation for simplifying individual thermal demand recognition systems.

Skin temperature is a widely used physiological parameter in thermal comfort research. It serves as an indicator of personnel's thermal comfort and has the potential to guide the regulation of thermal conditions in future indoor environment designs. This study reviews relevant publications from 2013 to late 2023, focusing on population differences in skin temperature (local characteristics, age, gender, etc.), changing characteristics in different environments (dynamic and non-uniform environment, sleep environment, outdoor environment, etc.), and the application of skin temperature in thermal sensation prediction and performance evaluation of devices. This study clarifies the effectiveness of skin temperature in characterizing the thermal state of the human body through a review of existing research. It also proposes directions for future work considering research limitations in personal comfort models and performance evaluation of devices. The study suggests that skin temperature is likely to play a significant role in the future due to the development of technologies such as big data and the Internet of Things. In addition to conducting in-depth research in subdivided fields based on existing research, it is also important to pay attention to standardized data collection and processing.

A person spends about a third of their life sleeping, and high sleep quality is very important for health. Environmental factors are one of the most important factors affecting sleep quality, and indoor carbon dioxide (CO2) concentration while sleeping has a significant effect on sleep quality. In an indoor bedroom with no open windows and no fresh air system, different numbers of people sleeping will lead to changes in indoor CO2 concentration. In order to study the changes in sleep quality caused by differences in CO2 concentration, experimental research was performed. Objective sleep quality data are collected with polysomnography (PSG) and a subjective questionnaire. The sleep quality of the subjects is tested under three different CO2 concentration levels; the average carbon dioxide concentration of three conditions is 680, 920, and 1350 ppm, which simulate a room with 1, 2, and 3 people sleeping, respectively. Other environment parameters are controlled as follows: test environment temperature is 26 ± 0.5 °C, relative humidity is 50 ± 5%, there is no obvious heat source in the test room, and the radiation temperature and air temperature difference is less than 1 °C. A total of 30 subjective tests were carried out with 10 subjects; the test lasted more than one month. The data subsequently underwent statistical analysis to determine the influence of CO2 concentration on sleep quality. The results show that as the CO2 concentration level increased, the sleep quietness and satisfaction of the subjects gradually decreased, the sleep duration gradually decreased, and symptoms such as throat discomfort, dyspnea, dry and itchy skin, difficulty falling asleep, difficulty waking up, congested nose and bad air smell become more obvious. The PSG test results showed that CO2 concentration has a significant impact on the proportion of the N3 period. According to the group of CO2 concentration conditions, the mean of the N3 period proportion under the conditions of one person, two persons, and three persons is 20.4%, 17.3%, and 14.4%, respectively. Finally, there was also an increase in turning over or awakening during sleep, indicating that sleep quality was reduced under higher CO2 concentrations.

Personalized thermal sensation models play a crucial role in ensuring occupant's thermal comfort satisfaction and improving building energy efficiency. However, an adaptive and accurate personalized model that can be easily implemented in real life is still challenging. This paper investigates the influencing factors of thermal sensation vote (TSV) and proposes a personalized regression model that only uses a single local skin temperature as the key indicator. A survey is conducted with forty subjects aging from 20 to 59 years old. The relationship among ambient temperature, skin temperatures, and subjective TSV is analyzed. The forehead temperature is recommended as the key indicator for prediction because it exhibits a strong correlation with ambient temperature and TSV, and it is easy to capture. Furthermore, the impact of individual characteristics on TSV is investigated. The proposed model effectively captures and compensates for individual differences by incorporating subjects' set point skin temperature and body fat percentage (BF%). The proposed model can be readily applied in real-life scenarios due to its minimal requirement for occupant’s feedback and its higher accuracy compared to other models. Specifically, it exhibits a significantly lower Root Mean Square Error (RMSE) of 15.8 %, 9.4 %, and 65.2 % compared to the Support Vector Regression (SVR) model Zhang's model and Zhou's model. Moreover, the proposed model showcases the lowest mean absolute error among the compared models. This approach of developing a personalized regression model based on local body temperature holds promise for future international ergonomic standard development.

This study presents a two-dimensional distribution table of Chinese head and face dimensions related to the design of respiratory protective devices. The two-dimensional distribution table is set up according to the coverage rate of head width shape length of adult men (18–60 years old) and adult women (18–60 years old). The head width was graded by 5 mm, and the morphological surface length was graded by 5 mm. In use, it can be merged reasonably according to the actual needs, calculate the coverage rate and set the model.

According to the six neck sizes needed in the design of cervical vertebra health instrument, this study puts forward the corresponding classification index; through the cluster analysis of the classification index, the young women's neck is divided into three types, forming the specification series of young women's neck size. This series of specifications can provide more dimensional references for the structural design of female cervical vertebra health instruments.

The average daily stay time of city people in the vehicle is more than one hour. For some office workers in megalopolis, the stay time in the vehicle will be longer. Therefore, the thermal comfort of vehicle air conditioning system has an important impact on the life of residents. Using the warm manikin to test the comfort of the interior environment of the vehicle under different working conditions, test the steady-state conditions and compare with the comfortable equivalent space temperature of different parts of the human body, and give the air conditioning design optimization program. The results show that the cooling comfort in summer is relatively good, and the discomfort areas are mainly concentrated in feet, shins and other parts. In some cases, the thighs are overheated due to strong solar radiation, and the equivalent space temperature exceeds the comfort area.

When human body operates some heating equipment, the surface temperature will affect the working efficiency and safety of workers. This study included the critical temperature of skin in contact with a hot solid surface and the method of assessing the risk of burns, that is, the application of the data provided by ergonomics in the process of risk assessment. Through the test results, how to choose a reasonable temperature limit value is put forward, and how to establish the same temperature limit value for different products with the same risk is proposed. The time of intentional and unintentional contact is different. Considering the distribution of human response time, when a healthy adult inadvertently contacts the hot surface, 0.5 s is the safe contact time, while the intentional contact time is longer. It is very necessary to choose the contact time, which can best represent the actual situation of contacting hot products.

This study was based on the latest Chinese adult body size data collected by the China National Institute of Standardization from 2013 to 2018. Studies have shown that there are differences in body shape distribution between different regions and different age groups. Compared with the data of the first national body size survey in 1988, the body shape distribution of adults has also changed greatly. This study can provide data support for the revision of the current garment size national standard.

This study makes statistics and analysis on the body size for the working space of different gender and different age groups by using the regression formulas in GB/T 13547-1992 and the newly collected data of height and weight obtained in the national adult body size survey. The data obtained can be used for the design and ergonomic evaluation of various working spaces related to human body size, such as operation, maintenance, safety protection, etc.

Based on the data of the second national anthropometric survey conducted from 2014 to 2018, this study analyzed the correlations among 11 head and face measurement items, and the correlations between head and face measurement items and influencing factors. And the effective linear regression equations are established, which provided a technical reference for the optimization of human head and face measurement items. Head and face data were acquired according to the method defined in the Basic Project of Anthropometry for Technical Design (GB/T5703-1999). The research results can be directly applied to human head and face measurement, to update human head and face size data and reduce the difficulty of human body measurement field work.

This study used the Vicon motion capture system to record the spatial positions of the points and to obtain the range of five joint angles in comfortable driving positions for Chinese men and women. The data could provide basic reference data for the establishment of the human body template to do the ergonomic verification of Chinese automobile cab.

In this study, a small sample of head and face item sizes was measured for 278 boys and 256 girls aged from 12 to 17 years old in China. Through the analysis of relevant data, regression equations were established between the main head and face parameters and the head and face item sizes. The results of this study could be used as amendments and supplements to the original national standards, and can also be used for ergonomic design and evaluation of head and face protective products for minors.

The thermal manikin is a kind of equipment which can simulate the data of human body environment heat exchange and be used for the comfort test of clothing and so on. In this paper, the thermal resistance of the thermal manikin is measured according to the heat flow, surface temperature and environment temperature. The results show that the thermal resistance of the waist and abdomen is very close to that of the mountain suit. The thermal resistance of the local position is even better than that of the mountain suit, but the leg part of the thermal resistance value is only half of the mountain suit, which seriously affects the thermal resistance of the whole suit. Combined with the clothing surface temperature collected by infrared thermal imager, the test results are verified. It provides the basis for the design of clothing warmth preservation.

BACKGROUND:Mental workload is one of the contributing factors to human errors in road accidents or other potentially adverse incidents.OBJECTIVE:This research probes the effects of mental workload on the electroencephalographic (EEG) and electrocardiogram (ECG) of subjects in visual monitoring tasks, based on which a comprehensive evaluation model for mental workload is established effectively.METHODS:Three degrees of mental workload were obtained by monitoring tasks with different levels of difficulty. 20 healthy subjects were selected to take part in the research.RESULTS:The subjective scores showed a significant increase with the increase of task difficulty, meanwhile the reaction time (RT) increased and the accuracy decreased significantly, which proved the validity of three degrees of mental workload induced. For the EEG parameters, a significant decrease of θ energy was found in Frontal, Parietal and Occipital with the increase of level of mental workload, as well as a significant decrease of α energy in Frontal, Central and Occipital, meanwhile a significant increase of β energy occurred in Frontal and Occipital. There was a significant decrease of α/θ in Occipital, and significant increases of θ/β and (α+β)/θ in Frontal, Central and Occipital, meanwhile (α+θ)/β and WPE decreased significantly in Frontal and Occipital. Among the ECG parameters, it was shown that Mean RR, RMSSD, HF_norm and SampEn decreased significantly with the increase of task difficulty, while LF_norm and LF/HF showed significant increases. These EEG indictors in Occipital and ECG indictors were chosen and constituted a multidimensional original sample. Principal Component Analysis (PCA) was used to extract the principal elements and decreased the dimension of sample space in order to simplify the calculation, based on which an effective classification model with accuracy of 80% was achieved by support vector machine (SVM).CONCLUSION:This study demonstrates that the proposed algorithm can be applied to mental workload monitoring.

To examine the effects of button size with different shape on the usability of touch screen devices. Considering the forefinger operation, the subjective and objective evaluation were combined to assess the ergonomics of the touch-sensitive button size, so as to obtain the recommended range of button size. With the size of touch-sensitive buttons specified setting from 3 mm to 25 mm respectively, where the step size was 2 mm, thirsty subjects participated in the test. One-way ANOVA was used to analyze the operational performance (reaction time and error rate) at different key sizes, and then the S-N-K-hoc multiple pairwise comparison test was used for pairwise comparison. The results demonstrated that the recommended range for rounded corner touch button is from 11 mm to 19 mm, round touch button in the recommended range is from 13 to 19 mm. It is also confirmed that the rounded corner touch buttons are superior to round touch buttons in the same size. This research can provide a basis for the design of button size of enterprise electronic products, and has important guiding significance.

In this experiment, the digital Mars contrast sensitivity check tables are used to test the contrast sensitivity value between two genders and three age groups. There was no statistically significant difference in contrast sensitivity between genders (P > 0.05) and between different eyes (P > 0.05). The contrast sensitivity of individuals of different groups was significantly different. The contrast sensitivity values of the left eye, right eye and both eyes increase with the increase of visual acuity.