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A Semi-Automatic Data Management Framework for Studying Thermal Comfort, Cognitive Performance, Physiological Performance, and Environmental Parameters in Semi-Outdoor Spaces

Author

Listed:
  • Shisheng Chen

    (Department of the Built Environment, College of Design and Engineering, National University of Singapore, Singapore 117566, Singapore)

  • Kuniaki Mihara

    (Kajima Technical Research Institute Singapore, Singapore 117566, Singapore)

  • Nyuk Hien Wong

    (Department of the Built Environment, College of Design and Engineering, National University of Singapore, Singapore 117566, Singapore)

  • Jason Kai Wei Lee

    (Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore)

  • Chun Liang Tan

    (Department of Architecture, College of Design and Engineering, National University of Singapore, Singapore 117566, Singapore)

Abstract

Semi-outdoor space can be used as an alternative to short-term office activities to save office energy consumption and promote a healthy and nature-based working environment. This study evaluated the suitability of semi-outdoor space in four aspects including environmental measurements, physiological measurements, subjective measurements and cognitive performance tests. However, the manual processing and analysis of such multidimensional data can be time-consuming and error-prone. Hence, the objective of this study was to develop a semi-automatic method to manage and analyze the data from different instruments and platforms and two open-source applications (a stroop color and word test and a digit span test) for cognitive performance tests. These codes were critical to the success of the project, providing an effective framework for data extraction, data pre-processing, data analysis and performance tests. Eighty-nine people participated in the experiment of evaluation of thermal comfort, cognitive performance, physiological performance and environmental parameters in semi-outdoor spaces in a tropical setting. Each participant received cognitive tests to assess their selective attention, short-term memory, concentration and creativity quotient. Concurrently, qualitative measurements were conducted to assess thermal sensation, thermal comfort and thermal acceptability. The heart rate, skin temperature, and skin conductance of participants were measured throughout the experiments. Microclimatic variables such as illuminance, noise levels, dry-bulb air temperature, global temperature, relative humidity, air speed, and air direction were monitored simultaneously. To understand the effects of semi-outdoor spaces on participant performance, this study recorded participant performance in different environments through controlled experiments. Data related to participants in different settings include those shared (e.g., environmental measurement), and data unique to each participant (e.g., physiological performance). The results revealed that the subjects’ cognitive and physiological performance did not change significantly after switching to the semi-outdoor space due to the availability of natural and mechanical ventilation, suggesting that short-term office activities in the semi-outdoor space are feasible in the tropics.

Suggested Citation

  • Shisheng Chen & Kuniaki Mihara & Nyuk Hien Wong & Jason Kai Wei Lee & Chun Liang Tan, 2022. "A Semi-Automatic Data Management Framework for Studying Thermal Comfort, Cognitive Performance, Physiological Performance, and Environmental Parameters in Semi-Outdoor Spaces," Sustainability, MDPI, vol. 15(1), pages 1-23, December.
  • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:183-:d:1011864
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    References listed on IDEAS

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    1. Masoud Esfandiari & Suzaini Mohamed Zaid & Muhammad Azzam Ismail & Mohammad Reza Hafezi & Iman Asadi & Saleh Mohammadi & Salah Vaisi & Ardalan Aflaki, 2021. "Occupants’ Satisfaction toward Indoor Environment Quality of Platinum Green-Certified Office Buildings in Tropical Climate," Energies, MDPI, vol. 14(8), pages 1-25, April.
    2. Belabes, Belkacem & Paraschivoiu, Marius, 2021. "Numerical study of the effect of turbulence intensity on VAWT performance," Energy, Elsevier, vol. 233(C).
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