Measurement and prediction of work engagement under different indoor lighting conditions using physiological sensing

Deng, Min; Wang, Xi; Menassa, Carol C.

doi:10.1016/j.buildenv.2021.108098

Cited by 40 publications

(18 citation statements)

References 66 publications

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“…For the thermal sensation database used in the room recommendation, the data are collected from the experiments in our previous studies (Li et al 2017(Li et al , 2018Deng et al 2021c). People are asked to report their thermal sensation (from −3 to 3) under different indoor environments, and the random forest (RF) algorithm is used to establish a thermal sensation prediction model based on the indoor environment (e.g., temperature and relativity humidity).…”

Section: Personal Database For Existing Occupantsmentioning

confidence: 99%

“…In our previous studies, Shimmer3 GSR+ Unit is used to collect the GSR signal of the occupants, Optical Pulse Ear-Clip, and Skin Surface Temperature Probe are used to collect the HR and ST of the subjects, respectively. More information on the data collection process can be found in our previous study (Deng et al 2021c). In the real world, a more portable device such as a wristband can be used to collect these data and connect these physiological responses to the computer terminal through Bluetooth.…”

Section: Feedback Strategy Based On Physiological Responsesmentioning

confidence: 99%

“…Therefore, given the GSR, HR, and ST data, the models can output estimations of people's thermal sensations. Based on the previous study (Deng et al 2021c), lighting level is selected to be the environmental parameter associated with GSR, HR, and ST values to establish the prediction models for work engagement. As for the outputs, the discrete indices range from −2 to 2.…”

Section: Feedback Strategy Based On Physiological Responsesmentioning

confidence: 99%

“…For example, it is suggested that females prefer higher room temperatures than males (Karjalainen 2007) and the thermal sensation of people in different age groups (under 25 years old, 26-45 years old, and over 65 years old) are statistically different (Calis and Kuru 2017). In addition, it is shown that the occupants' physiological features such as brain signal (Matthews et al 2017;Wang et al 2019;Deng et al 2021c), skin conductance level, heart rate, and skin temperature may vary across individuals under the same indoor environment (i.e., temperature and lighting conditions) (Deng et al 2021c). Therefore, it is essential to consider the individual differences in the decision-making of the building systems.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Digital ID framework for human-centric monitoring and control of smart buildings

Deng

Wang

et al. 2022

Build. Simul.

Self Cite

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Smart offices can help employers attract and retain talented people and can positively impact well-being and productivity. Thanks to emerging technologies and increased computational power, smart buildings with a specific focus on personal experience are gaining attraction.Real-time monitoring and estimation of the human states are key to achieving individual satisfaction. Although some studies have incorporated real-time data into the buildings to predict occupants' indoor experience (e.g., thermal comfort and work engagement), a detailed framework to integrate personal prediction models with building systems has not been well studied.Therefore, this paper proposes a framework to predict and track the real-time states of each individual and assist with decision-making (e.g., room assignment and indoor environment control). The core idea of the framework is to distinguish individuals by a new concept of Digital ID (DID), which is then integrated with recognition, prediction, recommendation, visualization, and feedback systems. The establishment of the DID database is discussed and a systematic prediction methodology to determine occupants' indoor comfort is developed. Based on the prediction results, the Comfort Score Index (CSI) is proposed to give recommendations regarding the best-fit rooms for each individual. In addition, a visualization platform is developed for real-time monitoring of the indoor environment. To demonstrate the framework, a case study is presented. The thermal sensation is considered the reference for the room allocation, and two groups of people are used to demonstrate the framework in different scenarios. For one group of people, it is assumed that they are existing occupants with personal DID databases. People in another group are considered the new occupants without any personal database, and the public database is used to give initial guesses about their thermal sensations. The results show that the recommended rooms can provide better thermal environments for the occupants compared to the randomly assigned rooms. Furthermore, the recommendations regarding the indoor setpoints (temperature and lighting level) are illustrated using a work engagement prediction model. However, although specific indoor metrics are used in the case study to demonstrate the framework, it is scalable and can be integrated with any other algorithms and techniques, which can serve as a fundamental framework for future smart buildings.

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Section: Personal Database For Existing Occupantsmentioning

confidence: 99%

Section: Feedback Strategy Based On Physiological Responsesmentioning

confidence: 99%

Section: Feedback Strategy Based On Physiological Responsesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Digital ID framework for human-centric monitoring and control of smart buildings

Deng

Wang

et al. 2022

Build. Simul.

Self Cite

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“…With the frequency domain, accumulating evidence highlights the frontal asymmetry index (FAI) to uncover the potential underlying neural mechanism [ 33 , 34 , 50 , 51 ]. Research on the spectrum analysis of brain oscillation has yielded substantial results on the potential mechanisms underlying the brain process [ 34 , 50 ].…”

Section: Introductionmentioning

confidence: 99%

Scarcity Enhances Outcome Evaluation in the Present: Electroencephalography Evidence

Ding

Zhang

et al. 2022

Brain Sciences

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Scarcity goods have generally been perceived as high in value in real-world and empirical studies. However, few studies have investigated this value over time, such as performance in intertemporal decision making. This study’s chief objective was to determine how scarcity evaluation changes temporally. We used the electroencephalogram technique and an outcome evaluation task with the valuation of scarcity and ordinary rewards delivered at different times to explore the effect of scarcity on delay discounting. The feedback-related negativity (FRN) results show that ordinary goods were associated with a more negative amplitude than scarcity goods, and that rewards delivered in the future evoked more negative deflection compared to those delivered immediately. The prominent FRN effect was derived mainly from ordinary trials rather than scarcity trials in the immediate condition and in the future rather than only in the immediate condition. The Frontal Asymmetry Index (FAI) results show that the scarcity condition was associated with greater relative left frontal cortical activity than the ordinary condition when delivered immediately. The frontal asymmetry indicated greater approach motivation. Our electrophysiology data indicate that scarcity goods have a perceived high value, particularly when delivered immediately.

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Assessing Lighting Experience Using Physiological Measures: A Review

Luo

Zhang

2023

Lecture Notes in Computer Science

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Measurement and prediction of work engagement under different indoor lighting conditions using physiological sensing

Cited by 40 publications

References 66 publications

Digital ID framework for human-centric monitoring and control of smart buildings

Digital ID framework for human-centric monitoring and control of smart buildings

Scarcity Enhances Outcome Evaluation in the Present: Electroencephalography Evidence

Assessing Lighting Experience Using Physiological Measures: A Review

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