Abstract
Brain computer interfaces are currently considered to greatly enhance assistive technologies and improve the experiences of people with special needs in the workplace. The proposed adaptive control model for smart offices provides a complete prototype that senses an environment’s temperature and lighting and responds to users’ feelings in terms of their comfort and engagement levels. The model comprises the following components: (a) sensors to sense the environment, including temperature and brightness sensors, and a headset that collects electroencephalogram (EEG) signals, which represent workers’ comfort levels; (b) an application that analyzes workers’ feelings regarding their willingness to adjust to a space based on an analysis of collected data and that determines workers’ attention levels and, thus, engagement; and (c) actuators to adjust the temperature and/or lighting. This research implemented independent component analysis to remove eye movement artifacts from the EEG signals and used an engagement index to calculate engagement levels. This research is expected to add value to research on smart city infrastructures and on assistive technologies to increase productivity in smart offices.
Highlights
Worker engagement and concentration are essential to ensure productivity in the workplace.busy workers may find it hard to concentrate since their focus can be broken by many factors, and this may affect their engagement at work
Busy workers may find it hard to concentrate since their focus can be broken by many factors, and this may affect their engagement at work
The control system’s level of interaction with users in maintaining an appropriate environment is critical, as most busy workers find it difficult or time consuming to track their environment in order to continually adjust it
Summary
Worker engagement and concentration are essential to ensure productivity in the workplace.busy workers may find it hard to concentrate since their focus can be broken by many factors, and this may affect their engagement at work. The control system’s level of interaction with users in maintaining an appropriate environment is critical, as most busy workers find it difficult or time consuming to track their environment in order to continually adjust it. Such a control system sounds promising as an assistive technology to accommodate workers with movement disabilities, it would be impractical in offices with more than one worker. A background on brain wave types and the use of BCI technologies and methodologies in smart offices is discussed.
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