朱萌 陈锦富 郭嫚丽 王悦

Zhu Meng, Chen Jinfu, Guo Manli, Wang Yue

在当前城市更新背景下，人本尺度的空间感知测度已成为精细化空间设计的重要依据。现有主要测度方法易受到感觉阈限等问题的干扰，而基于生理信号的空间感知测度在高细粒度、实时性和反馈感知的灵敏性方面具有优势，正发展成为一种针对人本尺度空间感知测度的新方法，但目前尚缺乏对该方法的系统建构。在认知理论的基础上，首先通过重建空间感知过程，提出情绪是空间感知测度的重要中介；再根据情绪的生理响应过程，提出测度空间情绪的生理信号类型及相应的计算方法；最终完成基于“感知—信号—情绪”的空间感知测度框架构筑，并对情绪恢复性环境、空间安全感与空间活动体验等实证研究进行分类梳理。同时利用CiteSpace 对最近十年的相关文献进行回顾，发现该方法在城市更新领域和旅游空间感知研究中均具备重要研究潜力。未来需要在建立系统的测度理论、对精细化设计实践的指导及与其他多源数据相结合方面继续开展深入研究。

In the current context of urban regeneration, human-scale spatial perception measurement has become an important basis for refined urban design. The spatial perception measurement based on physiological signals has advantages in terms of high fine-grainedness, real-time performance and sensitivity of feedback perception, and is developing into a new method for human-scale spatial perception measurement. On the basis of cognitive theory, firstly by reconstructing the process of spatial perception, it is proposed that emotion is an important mediator of spatial perception measurement; then based on the physiological response process of emotion, the physiological signal types and corresponding calculation methods for measuring spatial emotion are proposed, and finally the construction of spatial perception measurement framework based on “perception-signal-emotion” is completed. The empirical researches on emotional restorative environment, spatial security and spatial activity experience are classified and sorted out. At the same time, CiteSpace is used to review the relevant literature in the past 10 years, and it is found that this method has important research potential in both the field of urban renewal and tourism spatial perception research. In the future, we need to continue to conduct in-depth research in establishing a systematic measurement theory, guiding refined design practices, and combining with other multi-source data.

朱萌，华中科技大学建筑与城市规划学院，湖北省城镇化工程技术研究中心，博士研究生；

安徽农业大学林学与园林学院，讲师。zhumeng@ahau.edu.cn

陈锦富（通信作者），华中科技大学建筑与城市规划学院，湖北省城镇化工程技术研究中心，教授，博士生导师。0070010039@hust.edu.cn

郭嫚丽，安徽农业大学林学与园林学院，硕士研究生。2391488114@qq.com

王悦，安徽农业大学林学与园林学院，硕士研究生。791543386@qq.com

• [1] 邹兵. 增量规划、存量规划与政策规划[J]. 城市规划, 2013, 37(2): 35-37, 55.

  [2] 王德, 殷振轩, 俞晓天. 用地混合使用的国际经验：模式、测度方法和效果[J]. 国际城市规划, 2019, 34(6): 79-85. DOI: 10.22217/upi.2018.312.

  [3] 龙瀛, 叶宇. 人本尺度城市形态：测度、效应评估及规划设计响应[J]. 南方建筑, 2016(5): 41-47.

  [4] 孟昭兰. 普通心理学[M]. 北京: 北京大学出版社, 1994: 83-85.

  [5] 封丹珺, 石林. 应对方式的生态瞬时评估法及其他测量方法简介[J]. 心理科学进展, 2004(3): 429-434.

  [6] GRIMM S D, CHURCH A T. A cross-cultural study of response biases in personality measures[J]. Journal of research in personality, 1999, 33(4): 415-441.

  [7] FERRANDO P J, LORENZO-SEVA U, CHICO E. A general factor-analytic procedure for assessing response bias inquestionnaire measures[J]. Structural equation modeling: a multidisciplinary journal, 2009, 16(2): 364-381.

  [8] PEER E, GAMLIEL E. Too reliable to be true? response bias as a potential source of inflation in paper-and-pencil questionnaire reliability[J]. Practical assessment, research, and evaluation, 2011, 16(1): 1-8.

  [9] 邵源, 叶丹, 叶宇. 基于街景数据和深度学习的街道界面渗透率大规模测度研究——以上海为例[J/OL]. 国际城市规划. (2022-02-15)[2022-03-03]. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CAPJ&dbname=CAPJLAST&filename=GWCG20220610000&uniplatform=NZKPT&v=BxdPOPdOwA_jfO17WSOQWdowwghaSSyNedlML5JVxYOIBWNBzIx47y7AES-TrwQR.

  [10] 支文军. 新技术与新数据条件下的空间感知与设计[J]. 时代建筑, 2017(5): 1.

  [11] ULRICH R S, SIMONS R F, LOSITO B D, et al. Stress recovery during exposure to natural and urban environments[J]. Journal of environmental psychology, 1991, 11(3): 201-230.

  [12] 胡正凡, 林玉莲. 环境心理学——环境—行为研究及其设计应用[M]. 第四版. 北京: 中国建筑工业出版社, 2018.

  [13] 克里斯多夫·霍舍尔, 徐蜀辰. 人本视角的范式转变与挑战——新时代下的空间感知、行为与设计[J]. 时代建筑, 2017(5): 60-63.

  [14] 王甦, 汪安圣. 认知心理学[M]. 重排本. 北京: 北京大学出版社, 2006.

  [15] NORMAN D A. Twelve issues for cognitive science[J]. Cognitive science,1980, 4(1): 1-32.

  [16] 谢久书, 张常青, 王瑞明, 等. 知觉符号理论及其研究范式[J]. 心理科学进展, 2011, 19(9): 1293-1305.

  [17] 梁宁建. 心理学导论[M]. 上海: 上海教育出版社, 2011: 352.

  [18] 孟昭兰. 情绪心理学[M]. 北京: 北京大学出版社, 2005: 28.

  [19] MASLOW A H. A theory of human motivation[J]. Psychological review, 1943, 50(4): 1-21.

  [20] TAMIETTO M, DE GELDER B. Neural bases of the non-conscious perception of emotional signals[J]. Nature reviews neuroscience, 2010, 11(10): 697-709.

  [21] 郑涌著, 黄希庭. 心理学导论[M]. 北京: 人民教育出版社, 2015.

  [22] ZHANG J, CHEN M, ZHAO S, et al. ReliefF-based EEG sensor selection methods for emotion recognition[J]. Sensors, 2016, 16(10): 1-15.

  [23] 郑旭东, 马云飞. 脑电图技术的教育研究图景与趋势——基于2000—2019 年国际文献的知识图谱分析[J]. 现代远程教育研究, 2020, 32(4): 36-47.

  [24] 王忠民, 赵玉鹏, 郑镕林, 等. 脑电信号情绪识别研究综述[J]. 计算机科学与探索, 2022, 16(4): 760-774.

  [25] 赵国朕, 宋金晶, 葛燕, 等. 基于生理大数据的情绪识别研究进展[J]. 计算机研究与发展, 2016, 53(1): 80-92.

  [26] 易欣, 葛列众, 刘宏艳. 正负性情绪的自主神经反应及应用[J]. 心理科学进展, 2015, 23(1): 72-84.

  [27] RUSSELL J A, LANIUS U F. Adaptation level and the affective appraisal of environments[J]. Journal of environmental psychology, 1984, 4(2): 119-135.

  [28] 梁宁建, 编. 心理学导论[M]. 上海: 上海教育出版社, 2011: 357.

  [29] 朱萌, 王灿祥, 陈锦富. 街道步行环境夜间安全感关键影响因素识别——基于可穿戴生理传感器的感知实验[J]. 中国园林, 2023, 39(6): 64-69.

  [30] 朱滢. 实验心理学[M]. 第三版. 北京: 北京大学出版社, 2000: 2.

  [31] KAPLAN S, TALBOT J F. Psychological benefits of a wilderness experience[M] // Behavior and the natural environment. Boston, MA: Springer, 1983: 163-203.

  [32] 赵欢, 吴建平. 城市绿色与灰色空间复愈作用的初步对比研究[J]. 北京林业大学学报( 社会科学版), 2011, 10(3): 46-52.

  [33] ROE J J, ASPINALL P A, MAVROS P, et al. Engaging the brain: the impact of natural versus urban scenes using novel EEG methods in an experimental setting[J]. Proceedings of the National Academy of Sciences of the United States of America, 2013, 1(2): 93-104.

  [34] ASPINALL P, MAVROS P, COYNE R, et al. The urban brain: analysing outdoor physical activity with mobile EEG[J]. British journal of sports medicine, 2013, 49(4): 1-6.

  [35] Van den BERG M M H E, MAAS J, MULLER R, et al. Autonomic nervous system responses to viewing green and built settings: differentiating between sympathetic and parasympathetic activity[J]. International journal of environmental research and public health, 2015, 12(12): 15860-15874.

  [36] 武锋, 陆钊华, 郑松发. 基于情绪生理指标的红树林舒适度初步研究[J]. 湿地科学, 2015, 13(1): 43-48.

  [37] ANDERSON A P, MAYER M D, FELLOWS A M, et al. Relaxation with immersive natural scenes presented using virtual reality[J]. Aerospace medicine and human performance, 2017, 88(6): 520-526.

  [38] 李同予, 薛滨夏, 杨秀贤, 等. 基于无线生理传感器与虚拟现实技术的复愈性环境注意力恢复作用研究[J]. 中国园林, 2020, 36(12): 62-67.

  [39] 房城, 王成, 郭二果, 等. 城郊森林公园游憩与游人生理健康关系——以北京百望山森林公园为例[J]. 东北林业大学学报, 2010, 38(3): 87-88, 107.

  [40] BEIL K, HANES D. The influence of urban natural and built environments on physiological and psychological measures of stress–a pilot study[J]. International journal of environmental research and public health, 2013,10(4): 1250-1267.

  [41] LI D, SULLIVAN W C. Impact of views to school landscapes on recovery from stress and mental fatigue[J]. Landscape and urban planning, 2016, 148: 149-158.

  [42] 徐磊青, 孟若希, 黄舒晴, 等. 疗愈导向的街道设计：基于VR 实验的探索[J]. 国际城市规划, 2019, 34(1): 38-45. DOI: 10.19830/j.upi.2018.496.

  [43] ALVARSSON J J, WIENS S, NILSSON M E. Stress recovery during exposure to nature sound and environmental noise[J]. International journal of environmental research and public health, 2010, 7(3): 1036-1046.

  [44] MEDVEDEV O, SHEPHERD D, M J. HAUTUS. The restorative potential of soundscapes: a physiological investigation[J]. Applied acoustics, 2015, 96: 20-26.

  [45] SHU S, MA H. Restorative effects of urban park soundscapes on children's psychophysiological stress[J]. Applied acoustics, 2020, 164: 1-10.

  [46] HIJAZI I H, KOENIG R, SCHNEIDER S, et al. Geostatistical analysis for the study of relationships between the emotional responses of urban walkers to urban spaces[J]. International journal of e-planning research, 2016, 5(1): 1-19.

  [47] DE SILVA C S, WARUSAVITHARANA E J, RATNAYAKE R. An examination of the temporal effects of environmental cues on pedestrians’feelings of safety[J]. Computers, environment and urban systems, 2017, 64: 266-274.

  [48] HACKMAN D A, ROBERT S A, GRüBEL J, et al. Neighborhood environments influence emotion and physiological reactivity[J]. Scientific reports, 2019, 9(1): 1-11.

  [49] RISTEA A, LEITNER M, RESCH B, et al. Applying spatial video geonarratives and physiological measurements to explore perceived safety in Baton Rouge, Louisiana[J]. International journal of environmental researchand public health, 2021, 18(3): 1284.

  [50] LEITE S, DIAS M S, ELOY S, et al. Physiological arousal quantifying perception of safe and unsafe virtual environments by older and younger adults[J]. Sensors, 2019, 19(11): 1-19.

  [51] KIM S K, KANG H B. An analysis of fear of crime using multimodal measurement[J]. Biomedical signal processing and control, 2018, 41: 186-197.

  [52] SCHEBELLA M F, WEBER D, SCHULTZ L, et al. The nature of reality: human stress recovery during exposure to biodiverse, multisensory virtual environments[J]. International journal of environmental research and public health, 2020, 17(1): 1-24.

  [53] KAPLAN R, KAPLAN S, BROWN T. Environmental preference: a comparison of four domains of predictors[J]. Environment and behavior, 1989, 21(5): 509-530.

  [54] 叶宇, 周锡辉, 王桢栋. 高层建筑低区公共空间社会效用的定量测度与导控以虚拟现实与生理传感技术为实现途径[J]. 时代建筑, 2019(6): 152-159.

  [55] CHRISINGER B W, KING A C. Stress experiences in neighborhood and social environments (SENSE): a pilot study to integrate the quantified self with citizen science to improve the built environment and health[J]. International journal of health geographics, 2018, 17(1): 1-13.

  [56] OJHA V K, GRIEGO D, KULIGA S, et al. Machine learning approaches to understand the influence of urban environments on human’s physiological response[J]. Information sciences, 2019, 474: 154-169.

  [57] RESCH B, PUETZ I, BLUEMKE M, et al. An interdisciplinary mixedmethods approach to analyzing urban spaces: the case of urban walkability and bikeability[J]. International journal of environmental research and public health, 2020, 17(19): 1-20.

  [58] XIANG L, CAI M, REN C, et al. Modeling pedestrian emotion in highdensity cities using visual exposure and machine learning: tracking real-time physiology and psychology in Hong Kong[J]. Building and environment, 2021, 205: 1-15.

  [59] 陈筝, 杨云, 邱明, 等. 面向城市空间的实景视觉体验评价技术[J]. 风景园林, 2017(4): 28-33.

  [60] 陈筝, 刘颂. 基于可穿戴传感器的实时环境情绪感受评价[J]. 中国园林, 2018, 34(3): 12-17.

  [61] 陈筝, 何晓帆, 杨汶, 等. 实景实时感受支持的城市街道景观视觉评价及设计[J]. 中国城市林业, 2017, 15(4): 35-40.

  [62] 朱萌, 张云彬, 王悦, 等. 基于情绪测量实验的黟县屏山村旅游情境感知研究[J]. 华中农业大学学报, 2021, 40(6): 91-102.

  [63] 陈志敏, 黄鎔, 黄莹, 等. 街道空间宜步行性的精细化测度与导控——基于虚拟现实与可穿戴生理传感器的循证分析[J]. 中国园林, 2022, 38(1): 70-75.

  [64] MILLAR G C, MITAS O, BOODE W, et al. Space-time analytics of human physiology for urban planning[J]. Computers, environment and urban systems, 2021, 85: 1-11.

  [65] BIRENBOIM A, HELBICH M, KWAN M P. Advances in portable sensing for urban environments: understanding cities from a mobility perspective[J]. Computers, environment and urban systems, 2021, 88: 160-169.

  [66] OSBORNE T, JONES P I. Biosensing and geography: a mixed methods approach[J]. Applied geography, 2017, 87: 160-169.

  
  

• 收起