[HTML][HTML] The detection of alcohol intoxication using electrooculography signals from smart glasses and machine learning techniques
The operation of a motor vehicle under the influence of alcohol poses a significant risk to the
safety of the driver, passengers, and other road users. Electrooculographic (EOG) signal …
safety of the driver, passengers, and other road users. Electrooculographic (EOG) signal …
[PDF][PDF] Sieci nski, S
N Piaseczna, R Doniec - Osadcha, O - researchgate.net
As the automotive industry undergoes a phase of rapid transformation driven by
technological advancements, the integration of driving simulators stands out as an important …
technological advancements, the integration of driving simulators stands out as an important …
Classification of Recorded Electrooculographic Signals on Drive Activity for Assessing Four Kind of Driver Inattention by Bagged Trees Algorithm: A Pilot Study
The act of engaging in secondary activities while driving can cause safety risks on public
roads due to the driver's distracted attention. The objective of the research was to predict …
roads due to the driver's distracted attention. The objective of the research was to predict …
[HTML][HTML] Driving Reality vs. Simulator: Data Distinctions
As the automotive industry undergoes a phase of rapid transformation driven by
technological advancements, the integration of driving simulators stands out as an important …
technological advancements, the integration of driving simulators stands out as an important …
Cardiovascular Disease Preliminary Diagnosis Application Using SQL Queries: Filling Diagnostic Gaps in Resource-Constrained Environments
Cardiovascular diseases (CVDs) are chronic diseases associated with a high risk of
mortality and morbidity. Early detection of CVD is crucial to initiating timely interventions …
mortality and morbidity. Early detection of CVD is crucial to initiating timely interventions …
RFDANet: an FMCW and TOF radar fusion approach for driver activity recognition using multi-level attention based CNN and LSTM network
M Gu, K Chen, Z Chen - Complex & Intelligent Systems, 2024 - Springer
Dangerous driving behavior is a major contributing factor to road traffic accidents. Identifying
and intervening in drivers' unsafe driving behaviors is thus crucial for preventing accidents …
and intervening in drivers' unsafe driving behaviors is thus crucial for preventing accidents …
One-Dimensional Deep Residual Network with Aggregated Transformations for Internet of Things (IoT)-Enabled Human Activity Recognition in an Uncontrolled …
S Mekruksavanich, A Jitpattanakul - Technologies, 2024 - mdpi.com
Human activity recognition (HAR) in real-world settings has gained significance due to the
growth of Internet of Things (IoT) devices such as smartphones and smartwatches …
growth of Internet of Things (IoT) devices such as smartphones and smartwatches …
Distinguishing Drivers via Wearable Sensor Data and Machine Learning
This article uses machine learning analysis of wearable sensor data to explore the topic of
driver differentiation. The study focuses on using detailed analyzes of data collected from …
driver differentiation. The study focuses on using detailed analyzes of data collected from …
[PDF][PDF] Systems and Soft Computing
The operation of a motor vehicle under the influence of alcohol poses a significant risk to the
safety of the driver, passengers, and other road users. Electrooculographic (EOG) signal …
safety of the driver, passengers, and other road users. Electrooculographic (EOG) signal …