Integration of electroencephalography based services into consumer electronics

Kim, Youngrae; Moon, Jinyoung; Lee, Hyung-Jik; Bae, Changseok; Sohn, Sungwon

doi:10.1109/isce.2012.6241692

Cited by 6 publications

(3 citation statements)

References 7 publications

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“…Tests were conducted on four healthy awake participants to quantify the accuracy of the NeuroSky sensors and SVM classifier. The participants were divided according to information, mild concentration, and background noise [63]. As a result, classifying the information from noise or mild concentration, the developed system demonstrated high accuracy, with an average of about 86.…”

Section: Overview Of Commercial Wearable Devices For Detecting Sleep ...mentioning

confidence: 99%

Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview

et al. 2022

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Sleep is crucial for human health from metabolic, mental, emotional, and social points of view; obtaining good sleep in terms of quality and duration is fundamental for maintaining a good life quality. Over the years, several systems have been proposed in the scientific literature and on the market to derive metrics used to quantify sleep quality as well as detect sleep disturbances and disorders. In this field, wearable systems have an important role in the discreet, accurate, and long-term detection of biophysical markers useful to determine sleep quality. This paper presents the current state-of-the-art wearable systems and software tools for sleep staging and detecting sleep disorders and dysfunctions. At first, the paper discusses sleep’s functions and the importance of monitoring sleep to detect eventual sleep disturbance and disorders. Afterward, an overview of prototype and commercial headband-like wearable devices to monitor sleep is presented, both reported in the scientific literature and on the market, allowing unobtrusive and accurate detection of sleep quality markers. Furthermore, a survey of scientific works related the effect of the COVID-19 pandemic on sleep functions, attributable to both infection and lifestyle changes. In addition, a survey of algorithms for sleep staging and detecting sleep disorders is introduced based on an analysis of single or multiple biosignals (EEG—electroencephalography, ECG—electrocardiography, EMG—electromyography, EOG—electrooculography, etc.). Lastly, comparative analyses and insights are provided to determine the future trends related to sleep monitoring systems.

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Section: Overview Of Commercial Wearable Devices For Detecting Sleep ...mentioning

confidence: 99%

Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview

et al. 2022

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“…Again, we used the Neurosky Mindset headset in this piece, but for this experience we shifted from mapping data directedly to an audio or visual attribute and designed a new interactive approach Following the Performance Led Research in the Wild [2] approach this design was iteratively refined by previous studies [18] to use the feedback attribute of the filmic cut and visual sensitive Attention data from the Neurosky headset [14]. It was also guided by the theory of event segmentation [26].…”

Section: The Momentmentioning

confidence: 99%

Designing Musical Soundtracks for Brain Controlled Interface (BCI) Systems

Ramchurn

Chamberlian

Benford

2018

Proceedings of the Audio Mostly 2018 on Sound in Immersion and Emotion

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This paper presents research based on the creation and development of two Brain Controlled Interface (BCI) based film experiences. The focus of this research is primarily on the audio in the films; the way that the overall experiences were designed, the ways in which the soundtracks were specifically developed for the experiences and the ways in which the audience perceived the use of the soundtrack in the film. Unlike traditional soundtracks the adaptive nature of the audio means that there are multiple parts that can be interacted with and combined at specific moments. The design of such adaptive audio systems is something that is yet to be fully understood and this paper goes someway to presenting our initial findings. We think that this research will be of interest and excite the Audio-HCI community.

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“…At present, a single channel head-mounted EEG has been launched on the market, which is widely available at a reasonable price, comfortable to wear, and user-friendly to operate. In particular, as its weight is low, it allows users to be free from perceiving the experiment during the experiment [18].…”

Section: Introductionmentioning

confidence: 99%

To Design and Implement a Recommender System based on Brainwave: Applying Empirical Model Decomposition (EMD) and Neural Networks

Lai¹,

Jhang²,

Chen³

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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Recommender systems collect and analyze users' preferences to help users overcome information overload and make their decisions. In this research, we develop an online book recommender system based on users' brainwave information. We collect users' brainwave data by utilizing electroencephalography (EEG) device and apply empirical mode decomposition (EMD) to decompose the brainwave signals into intrinsic mode functions (IMFs). We propose a back-propagation neural networks (BPNN) model to portrait the user's brainwave preference correlations based on IMFs of brainwave signals, thereby designing and developing the book recommender system. The experimental results show that the recommender system combined with the brainwave analysis can improve accuracy significantly. This research has highlighted a future direction for research and development on humancomputer interaction (HCI) design and recommender system.

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Integration of electroencephalography based services into consumer electronics

Cited by 6 publications

References 7 publications

Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview

Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview

Designing Musical Soundtracks for Brain Controlled Interface (BCI) Systems

To Design and Implement a Recommender System based on Brainwave: Applying Empirical Model Decomposition (EMD) and Neural Networks

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