Precision Enhancement of Driver Assistant System Using EEG Based Driver Consciousness Analysis &amp; Classification

Nissimagoudar, Prabha; Nandi, Ashis Kumar

doi:10.1007/978-981-32-9585-8_21

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…Nissimagoudar and Nandi ( 2020 ) detailed an EEG detection system using alpha power, and using SVM for classification. The study used 10 subjects.…”

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.

116

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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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“…Nissimagoudar and Nandi ( 2020 ) detailed an EEG detection system using alpha power, and using SVM for classification. The study used 10 subjects.…”

Section: Resultsmentioning

confidence: 99%

“…However, the study was limited by its scope and length, precluding a definitive result on the device's performance. Nissimagoudar and Nandi (2020) detailed an EEG detection system using alpha power, and using SVM for classification. The study used 10 subjects.…”

Section: Neurosky Mindwavementioning

confidence: 99%

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

LaRocco

Paeng

2020

Front. Neuroinform.

116

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“…In this early solution, the Arduino microcontroller was used along with its software as a signal processing unit to control various safety systems of the vehicle. The experimental results have shown that the system was able to reliably increase the safety of drivers [ 116 , 117 ].…”

Section: Overview Of Already Existing Methodsmentioning

confidence: 99%

Vital Sign Monitoring in Car Seats Based on Electrocardiography, Ballistocardiography and Seismocardiography: A Review

Šidiková

Martínek

Kawala-Sterniuk

et al. 2020

Sensors

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This paper focuses on a thorough summary of vital function measuring methods in vehicles. The focus of this paper is to summarize and compare already existing methods integrated into car seats with the implementation of inter alia capacitive electrocardiogram (cECG), mechanical motion analysis Ballistocardiography (BCG) and Seismocardiography (SCG). In addition, a comprehensive overview of other methods of vital sign monitoring, such as camera-based systems or steering wheel sensors, is also presented in this article. Furthermore, this work contains a very thorough background study on advanced signal processing methods and their potential application for the purpose of vital sign monitoring in cars, which is prone to various disturbances and artifacts occurrence that have to be eliminated.

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“…Existing works on driver vital sign monitoring include the sensor-based methods [153]- [158], vision-based methods [262]- [265] and radio frequency (RF)-based methods [266]- [278]. The sensor-based methods require wearable sensors such as photoplethysmography (PPG) [156], ECG [154], [155], EEG [153], [279], voltage-controlled oscillators [157], and electromagnetic coupled sensor [158] to capture physiological signals for vital sign analysis. They are accurate due to the direct contact with a human body but tend to be cumbersome, uncomfortable, and distracting for a driver when driving, thus hindering practical applications.…”

Section: B Driver Vital Sign Monitoringmentioning

confidence: 99%

“…As there are so many factors that may cause driver's distraction, the existing research on distraction detection mainly focuses on analyzing the driver's behaviors/activities when operating the vehicle such as acceleration/braking, and mainly contains Driver vital sign monitoring can assist in preventing accidents caused by unpredictable sudden health deterioration of the driver as well as other in-vehicle sensing applications such as emotion sensing. Most of the conventional vital sign monitoring systems [153]- [158] require a user to wear a lot of sensor pads such as ECG/EEG, which may distract driving and thus are not applicable for driver's vital sign monitoring. Recent advances in wireless sensing techniques [159]- [163] have made contactless vital sensing possible and thus shed light on the future of driver's vital sign monitoring.…”

Section: Introductionmentioning

confidence: 99%

In-Vehicle Sensing for Smart Cars

Zeng

Wang

Wang³

et al. 2022

IEEE Open J. Veh. Technol.

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Precision Enhancement of Driver Assistant System Using EEG Based Driver Consciousness Analysis & Classification

Cited by 9 publications

References 7 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

Vital Sign Monitoring in Car Seats Based on Electrocardiography, Ballistocardiography and Seismocardiography: A Review

In-Vehicle Sensing for Smart Cars

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