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Real-time regulation of room temperature based on individual thermal sensation using an online brain-computer interface.
He, Xiaohe; Wu, Meng; Li, Hailong; Liu, Shengchun; Liu, Bin; Qi, Hongzhi.
Afiliación
  • He X; Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
  • Wu M; Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
  • Li H; Tianjin Guokeyigong Science & Technology Development Co., Ltd., Tianjin, China.
  • Liu S; Future Energy, School of Business, Society and Engineering (EST), Mälardalen University, Västerås, Sweden.
  • Liu B; Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, China.
  • Qi H; Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, China.
Indoor Air ; 32(9): e13106, 2022 09.
Article en En | MEDLINE | ID: mdl-36168224
Regulation of indoor temperature based on neurophysiological and psychological signals is one of the most promising technologies for intelligent buildings. In this study, we developed a system for closed-loop control of indoor temperature based on brain-computer interface (BCI) technology for the first time. Electroencephalogram (EEG) signals were collected from subjects for two room temperature categories (cool comfortable and hot uncomfortable) and used to build a thermal-sensation discrimination model (TSDM) with an ensemble learning method. Then, an online BCI system was developed based on the TSDM. In the online room temperature control experiment, when the TSDM detected that the subjects felt hot and uncomfortable, BCI would automatically turn on the air conditioner, and when the TSDM detected that the subjects felt cool and comfortable, BCI would automatically turn off the air conditioner. The results of online experiments in a hot environment showed that a BCI could significantly improve the thermal comfort of subjects (the subjective thermal comfort score decreased from 2.45 (hot uncomfortable) to 0.55 (cool comfortable), p < 0.001). A parallel experiment further showed that if the subjects wore thicker clothes during the experiment, the BCI would turn on the air conditioner for a longer time to ensure the thermal comfort of the subjects. This has further confirmed the effectiveness of TSDM model in evaluating thermal sensation under the dynamic change of room temperature and showed the model's good robustness. This study proposed a new paradigm of human-building interaction, which is expected to play a promising role in the development of human-centered intelligent buildings.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminación del Aire Interior / Interfaces Cerebro-Computador Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Indoor Air Asunto de la revista: SAUDE AMBIENTAL Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminación del Aire Interior / Interfaces Cerebro-Computador Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Indoor Air Asunto de la revista: SAUDE AMBIENTAL Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido