相关论文: Hearables: Ear EEG Based Driver Fatigue Detection
Cognitive fatigue has been a common problem among workers which has become an increasing global problem since the emergence of COVID-19 as a global pandemic. While existing multi-modal wearable sensors-aided automatic cognitive fatigue…
As fatigue is normally revealed in the eyes and mouth of a person's face, this paper tried to construct a XGBoost Algorithm-Based fatigue recognition model using the two indicators, EAR (Eye Aspect Ratio) and MAR(Mouth Aspect Ratio). With…
A limiting factor towards the wide routine use of wearables devices for continuous healthcare monitoring is their cumbersome and obtrusive nature. This is particularly true for electroencephalography (EEG) recordings, which require the…
The monitoring of sleep patterns without patient's inconvenience or involvement of a medical specialist is a clinical question of significant importance. To this end, we propose an automatic sleep stage monitoring system based on an…
Prolonged exposure to virtual reality (VR) systems leads to visual fatigue, impairs user comfort, performance, and safety, particularly in high-stakes or long-duration applications. Existing fatigue detection approaches rely on subjective…
Researches show that fatigue driving is one of the important causes of road traffic accidents, so it is of great significance to study the driver fatigue recognition algorithm to improve road traffic safety. In recent years, with the…
Mental fatigue related behavioral performance decline precipitates catastrophic accidents in sustained attention tasks. While existing neurophysiological systems effectively detect current behavioral performance, they often lack the…
Recent promising results in auditory attention decoding (AAD) using scalp electroencephalography (EEG) have motivated the exploration of cEEGrid, a flexible and portable ear-EEG system. While prior cEEGrid-based studies have confirmed the…
Research indicates that monotonous automated driving increases the incidence of fatigued driving. Although many prediction models based on advanced machine learning techniques were proposed to monitor driver fatigue, especially in manual…
We present a hybrid brain-machine interface (BMI) that integrates steady-state visually evoked potential (SSVEP)-based EEG and facial EMG to improve multimodal control and mitigate fatigue in assistive applications. Traditional BMIs relying…
Driver vigilance estimation is an important task for transportation safety. Wearable and portable brain-computer interface devices provide a powerful means for real-time monitoring of the vigilance level of drivers to help with avoiding…
Current assistive hearing devices, such as hearing aids and cochlear implants, lack the ability to adapt to the listener's focus of auditory attention, limiting their effectiveness in complex acoustic environments like cocktail party…
Nowadays, there are many fatigue detection methods and the majority of them are tracking eye in real-time using one or two cameras to detect the physical responses in eyes. It is indicated that the responses in eyes have high relativity…
Drivers' role changes with increasing automation from the primary driver to a system supervisor. This study investigates how supervising an SAE L2 and L3 automated vehicle (AV) affects drivers' mental workload and sleepiness compared to…
In this paper, we aimed at reviewing present literature on employing nonlinear analysis in combination with machine learning methods, in depression detection or prediction task. We are focusing on an affordable data-driven approach,…
Earable devices, wearables positioned in or around the ear, are undergoing a rapid transformation from audio-centric accessories into multifunctional systems for interaction, contextual awareness, and health monitoring. This evolution is…
Observing brain activity in real-world settings offers exciting possibilities like the support of physical health, mental well-being, and thought-controlled interaction modalities. The development of such applications is, however, strongly…
Electroencephalography (EEG) is an integral tool in neurocognitive research worldwide. However, research grade EEG (32/64ch) systems are expensive and have cumbersome setup designed for clinical usage not suited for rugged environment of…
Noninvasive EEG (electroencephalography) based auditory attention detection could be useful for improved hearing aids in the future. This work is a novel attempt to investigate the feasibility of online modulation of sound sources by…
In healthy sleepers, cortical alpha oscillations are present during the transition from wakefulness to sleep, and dissipate at sleep onset. For individuals with insomnia, alpha power is elevated during the wake-sleep transition and can…