Electrical Engineering Design with the Subconscious Mind

Mann, Steve; Phillip, V.; Garcia, Danson Evan; Hernandez, Jesse; Khokhar, Humza

doi:10.1109/ichms49158.2020.9209380

Cited by 5 publications

(1 citation statement)

References 18 publications

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“…The typical implementation of hardware-based ayinography utilizes the Sequential Wave Imprinting Machine (SWIM) technique to overlay the visual field onto the desired spatial plane. The SWIM uses multi-mediated reality to visualize invisible physical phenomenology, and thus it can be used for scientific measurement and analysis [7,10,22,23,26,28]. Typically, the SWIM uses a linear array of light sources connected to and receiving signals from a computing device.…”

Section: Hardware Ayinographymentioning

confidence: 99%

Interpreting the Visual Acuity of the Human Eye with Wearable EEG Device and SSVEP

Garcia

Liu

Zheng

et al. 2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Using a wearable electroencephalogram (EEG) device, this paper introduces a novel method of quantifying and understanding the visual acuity of the human eye with the steady-state visually evoked potential (SSVEP) technique. This method gives users easy access to self-track and to monitor their eye health. The study focuses on how varying the SSVEP stimulus frequency and duration affect the overall representation of a person's visual perception. The study proposes two methods for this visual representation. The first method is a hardware system that utilizes long-exposure photography to augment reality and collocate the visual map onto the plane of interest. The second is a software implementation that captures the visual field at a set distance. A three-dimensional mapping is created by gathering software-defined visual maps at various set distances. Preliminary results show that these methods can gain some insight into the user's central vision, peripheral vision, and depth perception.

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Section: Hardware Ayinographymentioning

confidence: 99%