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Wearable BrainComputer Interfaces Based on Steady-State Visually Evoked Potentials and Augmented Reality: A Review

期刊

IEEE SENSORS JOURNAL
卷 23, 期 15, 页码 16501-16514

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2023.3287983

关键词

Augmented reality (AR); brain-computer interface (BCI); electroencephalography (EEG); Health 4.0; Industry 4.0; instrumentation; measurement; monitoring; steady-state visually evoked potential (SSVEP); real-time systems; wearable systems

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BCIs are an integration of hardware and software communication systems that allow direct communication between the human brain and external devices. Among the various BCI paradigms, SSVEPs have gained attention due to their high signal-to-noise ratio and information transfer rate in noninvasive BCI applications.
Brain-computer interfaces (BCIs) are an integration of hardware and software communication systems that allow a direct communication path between the human brain and external devices. Among the existing BCI paradigms, steady-state visually evoked potentials (SSVEPs) have gained momentum in the development of noninvasive BCI applications as they are characterized by adequate signal-to-noise ratio (SNR) and information transfer rate (ITR). In recent years, the adoption of augmented reality (AR) head-mounted displays (HMDs) to render the flickering stimuli necessary for SSVEPs elicitation has become an attractive alternative to traditional computer screens (CSs). In fact, the increase in system wearability anticipates the possibility of adopting BCIs in contexts other than research laboratory. This has contributed to a steadily-increasing interest in BCIs, as also confirmed by the recent literature dedicated to the topic. In this evolving scenario, this review intends to provide a comprehensive picture of the current state-of-the-art in relation to the latest advancement of wearable BCIs based on SSVEPs classification and AR technology. The goal is to provide the reader with a systematic comparison of different technological solutions realized over the last years, thus making future research in this direction more efficient.

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