Evaluating NeuroSky’s Single-Channel EEG Sensor for Drowsiness Detection

Patel, Kishan; Shah, Harit; Dcosta, Malcolm; Shastri, Dvijesh

doi:10.1007/978-3-319-58750-9_35

Cited by 9 publications

(6 citation statements)

References 18 publications

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“…Patel et al ( 2017 ) evaluated the Neurosky MindWave specifically as a drowsiness detector. Using a driving simulator, a total of 7 subjects had EEG recorded.…”

Section: Resultsmentioning

confidence: 99%

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A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

LaRocco

Paeng

2020

Front. Neuroinform.

114

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Drowsiness is a leading cause of traffic and industrial accidents, costing lives and productivity. Electroencephalography (EEG) signals can reflect awareness and attentiveness, and low-cost consumer EEG headsets are available on the market. The use of these devices as drowsiness detectors could increase the accessibility of safety and productivity-enhancing devices for small businesses and developing countries. We conducted a systemic review of currently available, low-cost, consumer EEG-based drowsiness detection systems. We sought to determine whether consumer EEG headsets could be reliably utilized as rudimentary drowsiness detection systems. We included documented cases describing successful drowsiness detection using consumer EEG-based devices, including the Neurosky MindWave, InteraXon Muse, Emotiv Epoc, Emotiv Insight, and OpenBCI. Of 46 relevant studies, ∼27 reported an accuracy score. The lowest of these was the Neurosky Mindwave, with a minimum of 31%. The second lowest accuracy reported was 79.4% with an OpenBCI study. In many cases, algorithmic optimization remains necessary. Different methods for accuracy calculation, system calibration, and different definitions of drowsiness made direct comparisons problematic. However, even basic features, such as the power spectra of EEG bands, were able to consistently detect drowsiness. Each specific device has its own capabilities, tradeoffs, and limitations. Widely used spectral features can achieve successful drowsiness detection, even with low-cost consumer devices; however, reliability issues must still be addressed in an occupational context.

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“…Patel et al ( 2017 ) evaluated the Neurosky MindWave specifically as a drowsiness detector. Using a driving simulator, a total of 7 subjects had EEG recorded.…”

Section: Resultsmentioning

confidence: 99%

“…The average performance values reported included an accuracy of 91%, a sensitivity of 83%, and a specificity of 99%. Patel et al (2017) evaluated the Neurosky MindWave specifically as a drowsiness detector. Using a driving simulator, a total of 7 subjects had EEG recorded.…”

Section: Neurosky Mindwavementioning

confidence: 99%

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

LaRocco

Paeng

2020

Front. Neuroinform.

114

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“…Attention evaluation device We used a portable EEG headband (Brainlink Pro) equipped with a NeuroSky ThinkGear sensor 40 to assess the sustained attention level of users. It has received authorization from the U.S. www.nature.com/scientificreports/ Federal Communications Commission and has been approved for use in the European Union 41 .…”

Section: Tedious Task Construction By Sorting Parcels On the Virtual ...mentioning

confidence: 99%

Exploring user experience and performance of a tedious task through human–agent relationship

Zhou

Bian

Zhang

et al. 2023

Sci Rep

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Positive human–agent relationships can effectively improve human experience and performance in human–machine systems or environments. The characteristics of agents that enhance this relationship have garnered attention in human–agent or human–robot interactions. In this study, based on the rule of the persona effect, we study the effect of an agent’s social cues on human–agent relationships and human performance. We constructed a tedious task in an immersive virtual environment, designing virtual partners with varying levels of human likeness and responsiveness. Human likeness encompassed appearance, sound, and behavior, while responsiveness referred to the way agents responded to humans. Based on the constructed environment, we present two studies to explore the effects of an agent’s human likeness and responsiveness to agents on participants’ performance and perception of human–agent relationships during the task. The results indicate that when participants work with an agent, its responsiveness attracts attention and induces positive feelings. Agents with responsiveness and appropriate social response strategies have a significant positive effect on human–agent relationships. These results shed some light on how to design virtual agents to improve user experience and performance in human–agent interactions.

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“…The MindWave device can be used to measure emotions such as attention, meditation, blinking and mental activity [28]. In addition, this device has been used to detect brain activity in many areas such as education [29], [30], human-machine interaction [31], [32] and robotics [33]. In this study, 512 samples are taken from the EEG sensor per second.…”

Section: Figure 2 Emg and Imu Wrist Bandagementioning

confidence: 99%

Otonom Araçların Görsel Eğitimi için EEG, EMG ve IMU ile Etiketleme Sistemi

Seçkin

2019

Bilişim Teknolojileri Dergisi

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Autonomous vehicles are tools that make decisions and take decisions by perceiving their environment. Today, autonomous vehicles are also used in traffic in some countries. Various types of cameras, laser radars (LIDAR), sonar distance sensors, etc. are used for environmental detection in autonomous vehicles. After the environment is perceived, the collected data is taught to the vehicle with the help of machine learning methods and the vehicle reaches the target by following the traffic rules. At the point of traffic rules, the biggest task belongs to image-based systems. However, ideal traffic conditions and environmental conditions are not always provided. It is important to identify situations that may present a danger to autonomous vehicles. When the literature is examined, no visual data set or a scientific study with dangerous labeling has been found. In this study, it is aimed to design a data collection and labeling system to overcome this gap in the literature. In the system designed for the purpose, a system which automatically creates a video label from the physiological data of the driver (EEG ve EMG) and the inertia change data during human driving is designed. For this reason, firstly, the sensor signals were collected by experiments. In the time and frequency field, attributes were extracted by using the non-overlapping sliding window with 0.33 sec length. The input variables in the data set were reduced by PCA and classified by DT, RF and K-NN algorithms. According to the preliminary study findings, the K-NN method was the most successful algorithm among the algorithms tested with 0.922 accuracy.

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Evaluating NeuroSky’s Single-Channel EEG Sensor for Drowsiness Detection

Cited by 9 publications

References 18 publications

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

Exploring user experience and performance of a tedious task through human–agent relationship

Otonom Araçların Görsel Eğitimi için EEG, EMG ve IMU ile Etiketleme Sistemi

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