In recent years, the tourism industry in traditional villages has been developing rapidly due to the national call to vigorously advocate for and promote traditional culture, but there are plenty of problems and challenges facing the protection and development of traditional villages. The GPS action tracking method was adopted in this study to investigate the trajectory of tourists in typical traditional villages of Huizhou and to screen out different spatial sites with different characteristics based on the kernel density analysis. Thereby, people’s behavior in different spatial sites were analyzed in depth using the method of behavior observation, and ultimately, the relevance between the spatial environment of traditional villages, the characteristics of tourists’ actions, and their staying preferences were discussed, and hence an improvement strategy of spatial optimization was put forward accordingly. The research shows that, in Huizhou traditional villages, different scales and forms of space will affect tourists’ tour paths; the unreasonable distribution of commercial formats leads to the uneven distribution of village vitality; and traditional elements and landscape facilities are more likely to cause tourists to demonstrate a variety of behaviors. These findings provide (1) a basis for further understanding the spatial characteristics of traditional villages in Huizhou; (2) a basis for the spatial optimization of traditional villages; and (3) a new research perspective and feasible technical route for the protection, renewal, and sustainable development of traditional villages in other regions.

With the acceleration in globalization, cities have tended to become similar, and commercial districts have gradually lost their local characteristics. Hence, utilizing scientific means to assess human perceptions of traditional and modern districts in an objective manner, this study applies the electroencephalography (EEG) test and the Semantic Differential (SD) method to evaluate the external space perceptions of traditional and modern commercial districts. The results show that the alpha wave mean value of traditional samples is greater than that of modern samples among all electrodes, and most electrodes demonstrate a significant difference. Meanwhile, the alpha wave energy value of a single electrode of different subjects is mostly larger in the traditional samples, meaning that traditional districts can lead to an increase in the brain’s alpha waves. In addition, the SD results show that traditional samples make people feel more comfortable and relaxed; regarding the cultural atmosphere, they are more abundant in detail and distinct; regarding open and closed spaces, they are more closed and covert. The results also show that the electroencephalography (EEG) test can be applied to an evaluation of environmental perception to boost sustainable development of traditional commercial districts and offer more possibilities for future design.

In the field of digital design, a recent hot topic is the study of the interaction between spatial environment design and human factors. Electroencephalogram (EEG) and eye tracking can be used as quantitative analysis methods for architectural space evaluation; however, conclusions from existing studies on improving the quality of spatial environments based on human factors tend to remain qualitative. In order to realise the quantitative optimisation design of spatial elements from human physiological data, this research used the digital space optimisation method and perceptual evaluation research. In this way, it established an optimisation method for built space elements in real-time using human psychological indicators. Firstly, this method used the specific indicators of the Meditation value and Attention value in the human EEG signal, taking the ThinkGear AM (TGAM) module as the optimisation objective, the architectural space colour and the window size as the optimisation object, and the multi-objective genetic algorithm as the optimisation tool. Secondly, this research combined virtual reality scenarios and parametric linkage models to realise this optimisation method to establish a tool platform and workflow. Thirdly, this study took the optimisation of a typical living space as an example and recruited 50 volunteers to participate in an optimisation experiment. The results indicated that with the iterative optimisation of the multi-objective genetic algorithm, the specific EEG index decreases significantly and the standard deviation of the in-dex fluctuates and decreases during the iterative process, which further indicates that the optimisation method established in this study with the specific EEG index as the optimisation objective is effective and feasible. In addition, this study laid the foundation for more EEG indicators and more complex spatial element opti-misation research in the future.

Human experience in an architectural space is defined as the state of mind that is reflected on their physiological, emotional, and cognitive statuses. Ergonomic data, as an objective manifestation of quantifiable signals generated by the human body during specific spatial perception processes, serves as a vital foundation for spatial evaluation and guidance for optimization. Electroencephalogram (EEG) signals, as quantifiable sensory indicators directly arising from the interaction between individuals and external stimuli, hold substantial potential as a data-driven force and as a means of optimization assessment in the study of generative design. Although existing research has effectively established a unidirectional relationship between EEG and spatial-environment assessment, there is still a notable deficiency in addressing the creation of a two-way, mutually informative feedback mechanism. This study investigates the applicability of EEG signals as a data-driven basis for generative design across universal methods. It delves into various scales and scenarios of digital design, from the microscopic to the macroscopic, encompassing planar and volumetric visual elements, the design of architectural spatial environmental characteristics, and urban space design grounded in human perceptual sightlines. The research examines the viability and appropriateness of an interactive generative design method based on form generation, predicated on human-factor physiological data exemplified by EEG signals. This paper initially conducts a methodological and tool-based examination of current research in ergonomics-driven design and the use of EEG for design assessment, thereby discussing the objective feasibility of employing EEG in interactive generative design. Subsequently, the study establishes an integrated data flow system encompassing multiple hardware and software components to form a comprehensive workflow. Following this setup, empirical studies based on this method are conducted at different scales of application, yielding corresponding form-generative outcomes. Finally, this paper substantiates the rationality and feasibility of this framework in multi environment design domains.

In recent years, the research on digital design and perceptual evaluation has gradually become a hot topic in the field of digital design. Based on digital space optimization theory and perceptual evaluation tools, this study attempts to establish an optimization method to optimize built space elements in real-time using human psychological indicators. This method takes the specific indicators of the Meditation value and Attention value in the human EEG signal analyzed by the TGAM module as the optimization objective, the architectural space color and the window size as the optimization object, and the multi-objective genetic algorithm as the optimization tool. To realize this optimization method, this research combines virtual reality scene and parametric linkage model to establish tool platform and workflow. Taking the optimization of typical residential space as an example by recruiting 50 volunteers to participate in the experiment, this study concludes that this method is effective and feasible through experiment and quantitative analysis of experimental results and lays the foundation for more EEG indicators and more complex spatial element optimization research in the future.

This study selected green spaces from three residential areas in Hefei as the research subjects, combining behavioral observation methods and a natural experiment to collect behavioral data from 2010 and 2024. The data were then compared using Poisson regression models. Additionally, home visits were conducted to gather residents’ perceptions of the factors contributing to the decline in vitality. Based on the survey data, multilevel regression analysis was performed to explore the decline in RQGS usage vitality and its influencing factors in the context of rapid urbanization. This study found a significant decline in green space visits, particularly during the afternoon (16:00–18:00) and in areas adjacent to roadways. The main influencing factors include emerging leisure choices (such as taking the subway to large parks or preferring indoor activities) and residents’ satisfaction with RQGS characteristics (such as functional zoning, noise pollution, and neighborhood familiarity). Notably, there was no significant correlation between “disposable leisure time” and visit frequency. These findings suggest that, despite the inherent advantages of proximity, the vitality of RQGS faces increasing challenges due to emerging diverse leisure demands and growing environmental disturbances. In contrast to the traditional emphasis on accessibility, this study recommends that future RQGS planning prioritize functional zoning (e.g., dog-walking areas, sports zones), address the needs of vulnerable groups, and focus on mitigating vehicle noise and air pollution rather than merely expanding parking facilities. Interventions should be scheduled for the afternoon and emphasize strengthening community interaction and cohesion to enhance user experience. This research provides valuable scientific evidence and practical guidance for urban planners and policymakers to optimize residential green spaces in the context of rapid urbanization, offering new perspectives for the empirical evaluation of RQGS upgrades.