城市绿化重构的健康化评估：基于可穿戴设备的证据框架
Health Assessment of Urban Regreening: An Evidence Framework Derived from Wearable Devices
【目的】传统绿化评估依赖绿量、覆盖率和可达性等静态指标，难以解释城市绿化重构在真实使用情境中的健康效应差异，本研究梳理可穿戴设备相关研究，构建城市绿化重构健康化评估的证据链框架。【方法】采用结构化综述方法，以压力恢复理论和注意力恢复理论为解释框架，对74篇英文文献进行归纳，重点分析可穿戴数据、位置轨迹与环境暴露的时空对齐方法，梳理指标-设备-场景的对应关系及数据质量、技术偏差、人群公平性、样本代表性和隐私与伦理的实施边界。【结果】心率变异性（heart rate variability, HRV）和皮电活动（electrodermal activity, EDA）等近端生理-心理反应指标可用于捕捉短时恢复效应、真实移动情境中的压力反应及路径-街道尺度的压力热点；绿色基础设施健康效应并非由绿量单独决定，而是受交通、人流、热暴露、噪声、空气污染、停留方式和个体差异等因素共同影响。【结论】可穿戴证据有助于推动城市绿化重构健康化评估由静态增绿指标转向过程性健康证据，并为公园与城市森林、通勤路径、水岸与蓝绿界面的空间诊断、干预评估与项目迭代提供支持，但其应用需建立在数据质量控制、技术偏差解释、人群公平性审查、样本代表性报告以及隐私与伦理治理的基础上。
[Objective] Within a broader framework of urban health promotion and multiple urban exposures, this article systematically reviews research on the use of wearable devices in evaluating the health impacts of urban regreening. Urban regreening is increasingly expected to move beyond the simple provision of greenness, landscape beautification, or ecological restoration. It is also expected to support stress recovery, attention restoration, environmental comfort, everyday mobility, and the health-promoting use of public space. However, conventional evaluation approaches often rely on relatively static indicators, such as green space area, vegetation coverage, NDVI, accessibility, or distance to parks. These indicators are useful for citywide comparison and policy monitoring, but they are less capable of explaining whether green infrastructure actually improves users’ restoration experience, physiological stress, emotional state, and exposure conditions during everyday activities. They are also limited in answering the question of where regreening interventions are effective, for whom they are effective, and under what spatial and temporal circumstances they are effective. Against this background, this article conceptualizes wearable devices not as a replacement for planning judgment, but as an evidence interface that connects spatial exposure, behavioral processes, subjective experience, proximal physiological and psychological responses, and planning feedback. [Methods] This article adopts a structured review approach. It uses stress recovery theory and attention restoration theory as interpretive perspectives to synthesize existing research on nature-based health services, green infrastructure, and wearable-based evidence. The literature search focused on wearable and mobile sensing terms, including wearable device, wearable sensor, GPS, mobile sensing, smartphone, fitness tracker, ecological momentary assessment, experience sampling, heart rate variability, electrodermal activity, and EEG. These terms were combined with urban and environmental keywords, including green infrastructure, urban green space, park, street, built environment, walkability, and urban regreening. Studies were included when they used wearable devices, smartphones, or other mobile sensing approaches that could be linked with time and location information; reported sampling intervals or valid wearing and recording criteria; provided environmental exposure indicators with clear spatial or temporal meaning; and examined stress relief, restoration, emotional response, or proximal physiological and psychological reactions. Studies that focused only on steps, walking frequency, or physical activity without linking individual responses to environmental exposure were excluded. Finally, 74 studies were included in the review. Based on these studies, the article identifies major evidence domains, summarizes commonly used indicators and device configurations, proposes a planning issue−indicator−device comparison table, and develops a minimum viable indicator set for urban regreening health assessment. [Results] The review identifies three major evidence domains. First, short-term green walking and nature exposure studies show that green routes or natural environments are often associated with higher heart rate variability, reduced perceived stress, improved positive affect, and changes in stress-related biomarkers. These findings suggest that green exposure has measurable short-term restoration potential. However, the evidence should not be interpreted as a simple “more green means better health” relationship. The effects of green exposure are often influenced by route conditions, noise, air pollution, temperature, walking intensity, and individual baseline status. Second, studies using mobile EEG, electrodermal activity, wearable cameras, GPS, and ecological momentary assessment show that physiological and psychological responses in real-world urban settings are context dependent. Green space, crowding, traffic, indoor-outdoor transitions, spatial enclosure, seating, water, vegetation, and activity type may jointly shape emotional valence, arousal, cognitive load, and physiological stress. The same urban element may therefore produce different responses under different spatial, temporal, and social conditions. Third, street-segment and route-based studies demonstrate that wearable signals can be spatially aggregated and linked with GPS trajectories, street attributes, green view index, and micro-environmental characteristics. This makes it possible to identify stress hotspots, restoration nodes, priority segments for intervention, and route-level differences in exposure and response. In this regard, wearable-based evidence can support a shift from average greening indicators to more diagnostic, contextualized, and process-oriented planning evaluation. [Conclusion] This article argues that the main contribution of wearable-based evidence is not to prove once again that green space is beneficial to health. Rather, its contribution lies in reorganizing scattered physiological, behavioral, experiential, and environmental evidence into a planning-oriented evidence framework. The proposed framework follows a chain of “spatial exposure–behavioral processes–subjective experience–proximal health responses–spatial diagnosis–planning feedback.” It supports a shift in urban regreening evaluation from asking “how much green has been added” to asking “what kind of green, in what context, for which users, and with what proximal physiological and psychological responses.” For planning practice, the framework can inform three application scenarios: The refinement of restorative experience in parks and urban forests, the identification of exposure reduction and recovery nodes along commuting corridors, and the diagnosis of blue-green interfaces where visual attractiveness does not necessarily translate into actual use or restorative benefit. At the same time, the review emphasizes that wearable data cannot directly replace long-term health outcomes or professional judgment. Wearable indicators are sensitive to motion artifacts, temperature, humidity, skin contact, device model, algorithm version, sample bias, and privacy risks. Therefore, the application of wearable-based evidence in urban regreening requires rigorous quality control, transparent reporting, stratified error analysis, ethical governance, and local validation. Only under these conditions can wearable evidence become a reliable interface for health-oriented urban regreening assessment.
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