Objective Under the background of the optimization of urban construction stock, the improvement of street space quality has become an important leverage for urban quality and efficiency enhancement. Although the importance of human-centered street space quality enhancement has been widely recognized at theoretical and cognitive levels, there is still a lack of practical guidance and operational frameworks in actual design practice. Existing research mainly focuses on measuring street space elements and analyzing their influence weights, but still lacks the refined determination of the optimal threshold intervals for street space indicators. This gap makes it difficult to translate theoretical findings into specific spatial design standards and interventions. Additionally, current guidelines provide limited guidance on street space elements, with broad or missing element intervals and insufficient support from evidence-based practice. Therefore, this research, rooted in human perception, employs VR and wearable biosensors for embodied perception experiments to refine the threshold intervals of street space elements, thus enabling more precise and operational improvements in street space quality.

Methods In this research, based on classical research and current guidelines, 4 functional types, 2 classification levels, 4 key elements, and their corresponding guidance thresholds for street spaces are identified. Then, 8 typical streets are used as spatial prototypes, and 251 virtual reality scenes are constructed based on the threshold of each key element, 185 participants are recruited to conduct an embodied, evidence-based perception experiment integrating subjective preferences and wearable biosensors. Based on measurement data, the analysis begins with assessing psychological comfort of key street space elements using a grouped scatter plot from ChiPlot. This helps to verify the validity of the experimental data and optimize the empirical guidance intervals in the current guidelines, providing a reference for eliminating physiological data outliers and determining effective physiological threshold intervals. Then, the window-based change point detection algorithm is used to process the physiological data, and the threshold intervals of the key elements of different types of street spaces are further determined. Finally, the physiological threshold intervals are compared with the guidance intervals to evaluate the influence of physiological data on the refinement of threshold interval.

Results In psychological dimension, different street types have similar comfort intervals in terms of interface permeability and utility area width, and sidewalk width threshold exhibits “moderate effect”. Physiological analysis shows that sidewalk width threshold is not significantly affected by cycle parking, and the difference is between 0.6 − 1.2 m for most street types. The sidewalk width interval in traffic streets is significantly affected by road grade, with the main road ranging from 4.2 m to 5.1 m and the secondary road ranging from 2.4 m to 3.2 m. Participants have a higher demand for sidewalk width and interface permeability on main road in commercial streets. People generally feel more comfortable when the utility area width is between 3.7 m and 4.1 m, and interface permeability is between 74% and 86%. Finally, through the embodied evidence-based perception experiment, the research reveals that the quantitative results of physiological data are highly consistent with the participants’ subjective perception. Furthermore, physiological data can refine and supplement the guidance thresholds for elements in the current guidelines, with the threshold range contraction reaching 20% − 80%.

Conclusion This research proposes a systematic framework for analyzing the threshold interval of street space elements. Compared to previous analyses, this method refines the quality utility intervals of street space elements, breaking through the inherent paradigm of traditional research which is limited to the perception comfort measurement of street space quality. Additionally, this research combines virtual reality and wearable biosensor technologies to establish a comprehensive and easily applicable measurement framework. With this method, the rapid refinement of measurements for existing representative street types and the threshold intervals of spatial elements is achieved. This research also formulates specific design strategies and index recommendations from a quantitative perspective, thereby providing scientific basis and practical support for the accurate improvement of the built environment quality and design guidance and control.