Non-invasive Control of a Intelligent Room Using EEG Signals

Bolaños, Cristian D. Sanchez; Rodriguez, Domingo; Perdomo, César A.

doi:10.1016/j.ifacol.2021.10.005

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Bolaños et al. [ 62 ] created a room prototype that allowed people with motor disabilities to realize the control of the light and bed, and request assistance with a buzzer through an EEG-based BCI. EEG data recorded with Ultracortex “Mark IV” headset were filtered in the alpha band to train a one-dimensional (1D) CNN model.…”

Section: Scalp-eeg-based Bcimentioning

confidence: 99%

Recent Progress in Wearable Brain–Computer Interface (BCI) Devices Based on Electroencephalogram (EEG) for Medical Applications: A Review

Zhang,

Li,

Huang

et al. 2023

Health Data Sci

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Importance: Brain–computer interface (BCI) decodes and converts brain signals into machine instructions to interoperate with the external world. However, limited by the implantation risks of invasive BCIs and the operational complexity of conventional noninvasive BCIs, applications of BCIs are mainly used in laboratory or clinical environments, which are not conducive to the daily use of BCI devices. With the increasing demand for intelligent medical care, the development of wearable BCI systems is necessary. Highlights: Based on the scalp-electroencephalogram (EEG), forehead-EEG, and ear-EEG, the state-of-the-art wearable BCI devices for disease management and patient assistance are reviewed. This paper focuses on the EEG acquisition equipment of the novel wearable BCI devices and summarizes the development direction of wearable EEG-based BCI devices. Conclusions: BCI devices play an essential role in the medical field. This review briefly summarizes novel wearable EEG-based BCIs applied in the medical field and the latest progress in related technologies, emphasizing its potential to help doctors, patients, and caregivers better understand and utilize BCI devices.

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Section: Scalp-eeg-based Bcimentioning

confidence: 99%

Recent Progress in Wearable Brain–Computer Interface (BCI) Devices Based on Electroencephalogram (EEG) for Medical Applications: A Review

Zhang,

Li,

Huang

et al. 2023

Health Data Sci

View full text Add to dashboard Cite

show abstract

Brain-computer interface based generative design framework: an empirical multi-domain application exploration based on human-factors and form-generation interactive mechanisms

Guo,

Zhang,

et al. 2024

ARIN

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Human experience in an architectural space is defined as the state of mind that is reflected on their physiological, emotional, and cognitive statuses. Ergonomic data, as an objective manifestation of quantifiable signals generated by the human body during specific spatial perception processes, serves as a vital foundation for spatial evaluation and guidance for optimization. Electroencephalogram (EEG) signals, as quantifiable sensory indicators directly arising from the interaction between individuals and external stimuli, hold substantial potential as a data-driven force and as a means of optimization assessment in the study of generative design. Although existing research has effectively established a unidirectional relationship between EEG and spatial-environment assessment, there is still a notable deficiency in addressing the creation of a two-way, mutually informative feedback mechanism. This study investigates the applicability of EEG signals as a data-driven basis for generative design across universal methods. It delves into various scales and scenarios of digital design, from the microscopic to the macroscopic, encompassing planar and volumetric visual elements, the design of architectural spatial environmental characteristics, and urban space design grounded in human perceptual sightlines. The research examines the viability and appropriateness of an interactive generative design method based on form generation, predicated on human-factor physiological data exemplified by EEG signals. This paper initially conducts a methodological and tool-based examination of current research in ergonomics-driven design and the use of EEG for design assessment, thereby discussing the objective feasibility of employing EEG in interactive generative design. Subsequently, the study establishes an integrated data flow system encompassing multiple hardware and software components to form a comprehensive workflow. Following this setup, empirical studies based on this method are conducted at different scales of application, yielding corresponding form-generative outcomes. Finally, this paper substantiates the rationality and feasibility of this framework in multi environment design domains.

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Non-invasive Control of a Intelligent Room Using EEG Signals

Cited by 2 publications

References 12 publications

Recent Progress in Wearable Brain–Computer Interface (BCI) Devices Based on Electroencephalogram (EEG) for Medical Applications: A Review

Recent Progress in Wearable Brain–Computer Interface (BCI) Devices Based on Electroencephalogram (EEG) for Medical Applications: A Review

Brain-computer interface based generative design framework: an empirical multi-domain application exploration based on human-factors and form-generation interactive mechanisms

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