Analog-Like Control is Possible in SSVEP Based Brain-Computer Interfaces

Bianchi, Luigi; Ferrante, Raffaele; Ouitadamo, Lucia Rita

doi:10.1109/lsc.2018.8572094

Cited by 2 publications

(1 citation statement)

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“…Similarly, Saravanakumar and Reddy [14] demonstrated that use of electro-oculogram (EoG) along with SSVEP can improve the performance. Bianchi et al described a work [15] that studies the concept of providing analog like control using SSVEP through seven flickering stimuli.…”

Section: Introductionmentioning

confidence: 99%

A low cost SSVEP-EEG based human-computer-interaction system for completely locked-in patients

et al. 2021

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Human computer interaction (HCI) for completely locked-in patients is a very difficult task. Nowadays, information technology (IT) is becoming an essential part of human life. Patients with completely locked-in state are generally unable to facilitate themselves by these useful technological advancements. Hence, they cannot use modern IT gadgets and applications throughout the lifespan after disability. Advancements in brain computer interface (BCI) enable operating IT devices using brain signals specifically when a person is unable to interact with the devices in conventional manner due to cognitive motor disability. However, existing state-of-the-art application specific BCI devices are comparatively too expensive. This paper presents a research and development work that aims to design and develop a low-cost general purpose HCI system that can be used to operate computers and a general purpose control panel through brain signals. The system is based on steady state visual evoked potentials (SSVEP). In proposed system, these electrical signals are obtained in response of a number of different flickering lights of different frequencies through electroencephalogram (EEG) electrodes and an open source BCI hardware. Successful trails conducted on healthy participants suggest that severely paralyzed subjects can operate a computer or control panel as an alternative to conventional HCI device.

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Section: Introductionmentioning

confidence: 99%