A review of wearable and unobtrusive sensing technologies for chronic disease management
With the rapidly increasing number of patients with chronic disease, numerous recent
studies have put great efforts into achieving long-term health monitoring and patient …
studies have put great efforts into achieving long-term health monitoring and patient …
Sensor applications and physiological features in drivers' drowsiness detection: A review
A Chowdhury, R Shankaran, M Kavakli… - IEEE sensors …, 2018 - ieeexplore.ieee.org
Drowsiness in drivers has become a serious cause of concern due to the occurrences of a
large number of fatalities on the road each year. Lives of pedestrians and passengers are …
large number of fatalities on the road each year. Lives of pedestrians and passengers are …
Wearable device-based system to monitor a driver's stress, fatigue, and drowsiness
This paper proposes a wearable device-based system to monitor the abnormal conditions of
a driver, including stress, fatigue, and drowsiness. The system measures the motional and …
a driver, including stress, fatigue, and drowsiness. The system measures the motional and …
Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open …
Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to
detect driver inattention is essential in building a safe yet intelligent transportation system …
detect driver inattention is essential in building a safe yet intelligent transportation system …
Driver fatigue detection systems using multi-sensors, smartphone, and cloud-based computing platforms: a comparative analysis
Q Abbas, A Alsheddy - Sensors, 2020 - mdpi.com
Internet of things (IoT) cloud-based applications deliver advanced solutions for smart cities
to decrease traffic accidents caused by driver fatigue while driving on the road …
to decrease traffic accidents caused by driver fatigue while driving on the road …
Machine learning and end-to-end deep learning for monitoring driver distractions from physiological and visual signals
It is only a matter of time until autonomous vehicles become ubiquitous; however, human
driving supervision will remain a necessity for decades. To assess the driver's ability to take …
driving supervision will remain a necessity for decades. To assess the driver's ability to take …
A new feature selection approach for driving fatigue EEG detection with a modified machine learning algorithm
Y Zheng, Y Ma, J Cammon, S Zhang, J Zhang… - Computers in Biology …, 2022 - Elsevier
This study aims to identify new electroencephalography (EEG) features for the detection of
driving fatigue. The most common EEG feature in driving fatigue detection is the power …
driving fatigue. The most common EEG feature in driving fatigue detection is the power …
Stress events detection of driver by wearable glove system
This paper is focused to develop a wearable glove system to detect driver stress events in
real time. The driver's stress is estimated by the use of physiological signals and steering …
real time. The driver's stress is estimated by the use of physiological signals and steering …
Hybrid of discrete wavelet transform and adaptive neuro fuzzy inference system for overall driving behavior recognition
HR Eftekhari, M Ghatee - Transportation research part F: traffic psychology …, 2018 - Elsevier
Monitoring and evaluating of driving behavior is the main goal of this paper that encourage
us to develop a new system based on Inertial Measurement Unit (IMU) sensors of …
us to develop a new system based on Inertial Measurement Unit (IMU) sensors of …
Driver monitoring using sparse representation with part-based temporal face descriptors
Many driver monitoring systems (DMSs) have been proposed to reduce the risk of human-
caused accidents. Traditional DMSs focus on detecting specific predefined abnormal driving …
caused accidents. Traditional DMSs focus on detecting specific predefined abnormal driving …