Atigue Posture Patterns News Today : Breaking News, Live Updates & Top Stories | Vimarsana

Stay updated with breaking news from Atigue posture patterns. Get real-time updates on events, politics, business, and more. Visit us for reliable news and exclusive interviews.

Top News In Atigue Posture Patterns Today - Breaking & Trending Today

"A Semantic Hybrid Temporal Approach for Detecting Driver Mental Fatigu" by Shahzeb Ansari, Haiping Du et al.

Driver mental fatigue is considered a major factor affecting driver behavior that may result in fatal accidents. Several approaches are addressed in the literature to detect fatigue behavior in a timely manner through either physiological or in-vehicle measurement methods. However, the literature lacks the implementation of hybrid approaches that combine the strength of individual approaches to develop a robust fatigue detection system. In this regard, a hybrid temporal approach is proposed in this paper to detect driver mental fatigue through the combination of driver postural configuration with vehicle longitudinal and lateral behavior on a study sample of 34 diverse participants. A novel fully adaptive symbolic aggregate approximation (faSAX) algorithm is proposed, which adaptively segments and assigns symbols to the segmented time-variant fatigue patterns according to the discrepancy in postural behavior and vehicle parameters. These multivariate symbols are then combined to prepar ....

Driver Mental Fatigue , Driver Safety , Atigue Posture Patterns , Ully Adaptive Sax , Ybrid Detection System , Emantic Learning , Ehicle Situations ,

"Automatic driver cognitive fatigue detection based on upper body postu" by Shahzeb Ansari, Haiping Du et al.

Driver cognitive fatigue can significantly affect driving and may lead to fatal accidents. In this regard, automatic detection of underload driver cognitive fatigue based on upper body posture dynamics is studied in this paper, where a semi-supervised approach is developed to identify the cognitive fatigue patterns of driver posture. Initially, an unsupervised Gaussian Mixture Model (GMM) clustering is applied to the acceleration data representing the driver's head, neck, and sternum obtained in a simulated driving through a motion capture suit. This provides the optimum clusters of the most-similar and correlated time-series data of driver upper posture. Then, an automatic labelling algorithm is developed that mines the maximal value and the standard deviation of each GMM cluster and assigns a symbol according to the discrepancy in postural behaviour. Finally, novel machine learning supervised classifiers, including Gaussian Support Vector Machines, and Bootstrap-Aggregating base ....

Gaussian Mixture Model , Gaussian Support Vector Machines , Ensemble Classifiers , Ognitive Driver Fatigue , River Posture , Atigue Posture Patterns , Semi Supervised Learning ,