), and is controlled by the subject. A series of studies using both reaction time and accuracy measures is presented, which traces these concepts in the form of automatic detection and controlled, search through the areas of detection, search, and attention. Results in these areas are shown to arise from common

. The stress-detection accuracy obtained is 99.5 % by acquiring HR and GSR during a period of 10 s, and what is more, rates over 90 % of success are achieved by decreasing that acquisition period to 3–5 s. Finally, this paper comes up with a proposal that an accurate stress detection only requires two

to distinguish three levels of driver stress with an accuracy of over 97% across multiple drivers and driving days. In Analysis II, continuous physiological features were correlated with a continuous metric of observable stressors showing that on a real-time basis metrics of skin conductivity and heart rate were

Abstract StressEraser is a commercially marketed biofeedback device designed to enhance heart rate vari-ability. StressEraser makes its internal calculations on beat-to-beat measures of finger pulse intervals. However, the accuracy and precision of StressEraser in quantifying interbeat intervals

Background: This study was designed to investigate the accuracy of dobutamine stress echocardiography (DSE) in detect-ing the post-revascularization recovery rate of contractile reserve (CR) in ischemic myocardium. Methods: A total of 112 segments from seven patients with low ejection fraction (<

Sense classifier can robustly identify stress across multiple individuals in diverse acoustic environments: using model adaptation StressSense achieves 81 % and 76 % accuracy for indoor and outdoor environments, respectively. We show that StressSense can be implemented on commodity Android phones and run in real

ABSTRACT: Studies have shown that distortion introduced by stress or emotion can severely reduce speech recognition accuracy. Techniques for detecting or assessing the presence of stress could help neutralize stressed speech and improve robustness of speech recognition systems. The performance of a

We present a study on the use of lexical stress classification to aid in the recognition of phonetically similar words. In this study, we use a simple pattern recognition approachto determine which syllable is lexically stressed for phonetically similar word pairs (e.g., PERfect, perFECT) extracted

is challenged and it is asserted that useful correlation exists in intensities of spatially proximal pixels. This correlation is exploited to sustain high levels of detection accuracy in the presence of dynamic backgrounds. By using a non-parametric density estimation method over a joint domain

High-resolution color infrared (CIR) aerial images were used for detecting in-field spatial patterns, especially due to nitrogen stress in a corn field. Digital images were processed and classified into groups using unsupervised learning method and analyzed using a GIS package. The CIR images