We present an estimation of fatigue level within individual operators using voice analysis. One advantage of voice analysis is its utilization of already existing operator communications hardware (2-way radio). From the driver viewpoint it's an unobtrusive, non-interfering, secondary task. The expected fatigue induced speech changes refer to the vo...
Jarek Krajewski Udo Trutschel Martin Golz David J Edwards
Todd Dawson Udo Trutschel W. Sirois Martin Moore-Ede
This study was designed to evaluate the viabililty of utilizing Tachograms for estimating fatigue in industrial and transportation applications. To explore this possibility Tachograms were recorded continuously and several heart rate measures were calculated and correlated with other well established fatigue measures. It was anticipated that ch...
Robert Hefner David J Edwards Christian Heinze Udo Trutschel
Robust and reliable determination of hypovigi¬lance is required in many areas, particularly transportation. Here, new products of Fatigue Monitoring Tech¬nologies (FMT) emerge. Their development and assessment requires an independent reference standard of driver’s hypovigi¬lance. Until recently most approaches utili¬zed electrooculography (EOG) and...
David Sommer Martin Golz Udo Trutschel David J Edwards
When subjects are monitored over long time spans and when several biosignals are derived a large amount of data has to be processed. In consequence, the number of features which has to be extracted is mostly very restricted in order to avoid the so-called “curse of high dimensionality”. Donoho [1] stated that this applies only if algorithms perform...
Martin Golz David Sommer Udo Trutschel
The aim of this study is to detect the occurrence of microsleep events in an overnight driving task. We propose a biosignal analysis method for the detection and extraction of microsleep events. This is achieved by employing blind source extraction method based on a cascaded nonlinear estimator to extract the relevant microsleep events. The cascade...
wai yie Leong Danilo P. Mandic Martin Golz David Sommer
The ability to adapt our sleep/wake cycle (SWC) to strongly altering time cues is crucial to maintain nowadays round-the-clock society [7]. However, many accidents are caused by sudden losses of attention when working during regular sleep hours where a proper adaptation of the SWC did not occur. We suggest a combined bio-mathematical model to simul...
Sven Schirmer Christian Heinze Martin Golz
A framework for automated scoring of sleep stages during afternoon naps of healthy humans is introduced. This is achieved by sequential fusion of nonlinear features extracted from three physiological channels: the electroencephalogram (EEG), electrooculogram (EOG) and respiratory trace (RES). These features are generated by means of the recently in...
Mo Chen David Sommer Vanessa Goh Danilo Mandic
The issue of Automatic Relevance Determination (ARD) has attracted attention over the last decade for the sake of efficiency and ac- curacy of classifiers, and also to extract knowledge from discriminant functions adapted to a given data set. Based on Learning Vector Quanti- zation (LVQ), we recently proposed an approach to ARD utilizing genetic al...
Martin Golz David Sommer
Karel Marsalek René Gerber Martin Golz Alexander Gundel
A novel approach for Microsleep Event detection is presented. This is achieved based on multisensor electroencephalogram (EEG) and electrooculogram (EOG) measurements recorded during an overnight driving simulation task. First, using video clips of the driving, clear Microsleep (MSE) and Non-Microsleep (NMSE) events were identified. Next, segments...
David Sommer Mo Chen Martin Golz Danilo P. Mandic
An overview of data fusion approaches is provided from the signal processing viewpoint. The general concept of data fusion is introduced, together with the related architectures, algorithms and performance aspects. Benefits of such an approach are highlighted and potential applications are identified. Case studies illustrate the merits of applying...
Danilo P. Mandic Dragan Obradovic Anthony Kuh Jonathon Chambers
We compare two comprehensive classification algorithms, support vector machines (SVM) and several variants of learning vector quantization (LVQ), with respect to different validation methods. The generalization ability is estimated by “multiple-hold-out” (MHO) and by “leave-one-out” (LOO) cross v method. The ξα-method, a further estimation method,...
David Sommer Martin Golz
EEG segments recorded during microsleep events were transformed to the frequency domain and were subsequently clustered without the common summation of power densities in spectral bands. Any knowledge about the number of clusters didn’t exist. The hierarchical agglomerative clustering procedures were terminated with several standard measures of int...
David Sommer Martin Golz
ABSTRACT: Slow eye movements were detected in the electro- oculogram of eleven subjects during nighttime driving simulations. Simultaneously recorded EEG segments were transformed to the frequency domain with discrete Fourier transform. A subsequent clustering without the common summation in spectral bands sought to analyze how many types of EEG se...
David Sommer Martin Golz Udo Trutschel Martin Moore-Ede
The eye gaze point and the pupil size of five subjects were recorded during an overnight driving simulation task. By scoring the recorded videos, clear microsleep events (MSE) and clear non-microsleep events were detected, and the measured signals in the preceding five seconds were analyzed. The spectral densities of these segments were classified...
Martin Golz David Sommer A. Seyfarth Martin Moore-Ede
