Bart Wyns

Multisubject learning for common spatial patterns in motor-imagery BCI

Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern filter (CSP) as preprocessing step before feature extraction and classification. The CSP method is a supervised algorithm and therefore needs subject-specific training data for calibration, which is very time consuming to collect. In order to reduce the amount of calibration data that is needed for a new subject, one can apply multitask (from now on called multisubject) machine learning techniques to the preprocessing phase. Here, the goal of multisubject learning is to learn a spatial filter for a new subject based on its own data and that of other subjects. This paper outlines the details of the multitask CSP algorithm and shows results on two data sets. In certain subjects a clear improvement can be seen, especially when the number of training trials is relatively low.

DAS28 best reflects the physician's clinical judgment of response to infliximab therapy in rheumatoid arthritis patients: validation of the DAS28 score in patients under infliximab treatment

This study is based on an expanded access program in which 511 patients suffering from active refractory rheumatoid arthritis (RA) were treated with intravenous infusions of infliximab (3 mg/kg+methotrexate (MTX)) at weeks 0, 2, 6 and every 8 weeks thereafter. At week 22, 474 patients were still in follow-up, of whom 102 (21.5%), who were not optimally responding to treatment, received a dose increase from week 30 onward. We aimed to build a model to discriminate the decision to give a dose increase. This decision was based on the treating rheumatologists clinical judgment and therefore can be considered as a clinical measure of insufficient response. Different single and composite measures at weeks 0, 6, 14 and 22, and their differences over time were taken into account for the model building. Ranking of the continuous variables based on areas under the curve of receiver-operating characteristic (ROC) curve analysis, displayed the momentary DAS28 (Disease Activity Score including a 28-joint count) as the most important discriminating variable. Subsequently, we proved that the response scores and the changes over time were less important than the momentary evaluations to discriminate the physicians decision. The final model we thus obtained was a model with only slightly better discriminative characteristics than the DAS28. Finally, we fitted a discriminant function using the single variables of the DAS28. This displayed similar scores and coefficients as the DAS28. In conclusion, we evaluated different variables and models to discriminate the treating rheumatologists decision to increase the dose of infliximab (+MTX), which indicates an insufficient response to infliximab at 3 mg/kg in patients with RA. We proved that the momentary DAS28 score correlates best with this decision and demonstrated the robustness of the score and the coefficients of the DAS28 in a cohort of RA patients under infliximab therapy.

Four-year follow-up of infliximab therapy in rheumatoid arthritis patients with long-standing refractory disease: attrition and long-term evolution of disease activity

Although there is strong evidence supporting the short-term efficacy and safety of anti-tumour necrosis factor-α agents, few studies have examined the long-term effects. We evaluated 511 patients with long-standing refractory rheumatoid arthritis treated with intravenous infusions of infliximab 3 mg/kg at weeks 0, 2, 6, and 14 and every 8 weeks thereafter for 4 years. Among the initial 511 patients included in the study, 479 could be evaluated; of these, 295 (61.6%) were still receiving infliximab treatment at year 4 of follow-up. The most common reasons for treatment discontinuation were lack of efficacy (65 patients, 13.6%), safety (81 patients, 16.9%), and elective change (38 patients, 7.9%). Analysis of disease activity scores (DAS28 [disease activity score based on the 28-joint count]) over time showed that, after the initial rapid improvement during the first 6 to 22 weeks of therapy, a further decrease in disease activity of 0.2 units in the DAS28 score per year was observed. DAS28 scores, measured at week 14 or 22, were found to predict subsequent discontinuation due to lack of efficacy. In conclusion, long-term maintenance therapy with infliximab 3 mg/kg is effective in producing further reductions in disease activity. Disease activity measured by the DAS28 at week 14 or 22 of infliximab therapy was the best predictor of long-term attrition.

A Remote Laboratory for Mobile Robot Applications

Abstract This paper presents the architecture and the implementation of a remote laboratory for mobile robot applications. The implementation is based on Matlab and Easy Java Simulations (EJS). The aim of the remote laboratory is that students perform – via the Internet – experiments on a group of non-holonomic mobile robots. The robot application presented in this paper is leader-follower formation control using image processing.

Classifying carpets based on laser scanner data

Nowadays the quality of carpets is in industry still determined through visual assessment by human experts, although this procedure suffers from a number of drawbacks. Existing computer models for automatic assessment of carpet wear are at this moment not capable of matching the human expertise. Therefore, we present a completely new approach to tackle this problem. A three-dimensional laser scanner is used to obtain a digital copy of the carpet. Due to the specific characteristics of the laser scanner data, new algorithms are developed to extract relevant information from the raw data. These features are used as input to a classifier system that defines a partial ranking over the objects. To this end, ordinal regression and multi-class classification models are applied. Experiments demonstrate that our approach gives rise to promising results with correlations up to 0.77 between extracted features and quality labels. The performance obtained with nested cross-validation, including a C-index of more than 0.95, an accuracy of 76% and only 3% serious errors of a full point, gives rise to a substantial improvement compared to other approaches mentioned in the literature.

Robust and two-level (nonlinear) predictive control of switched dynamical systems with unknown references for optimal wet-clutch engagement

Modeling and control of clutch engagement has been recognized as a challenging control problem, due to nonlinear and time-varying dynamics, that is, switching between two discontinuous dynamic phases: the fill and the slip. Furthermore, the reference trajectories for obtaining an optimal clutch engagement are not a priori known and may require adaptation to varying operating conditions. Two (nonlinear) model predictive control strategies are proposed based on the partial or full (non)linear identification of these two phases. First, a local linear model of the fill phase is identified and a robust model predictive control is designed to account for the consequent uncertainty in the slip phase. Second, (non)linear models of both the fill and the slip phases are identified and a two-level (nonlinear) model predictive control controller is proposed, where two (nonlinear) model predictive control controllers are designed for the two phases tracking references generated and continuously adapted by high-level iterative learning controllers. The robust and two-level (nonlinear) model predictive controls are validated on a real clutch. The results obtained from the real setup show that the proposed control strategies lead to an optimal engagement of the wet-clutch system.

Leader-follower string formation using cascade control for mobile robots

This paper proposes a simple yet effective control algorithm for a platoon of “car-like” robots. The formation used is a line, leader-follower formation, i. e. each robot is a follower for the previous robot and a leader for the next robot. The formation is implemented using speed measurements from optical encoders and distance measurements from image processing, but there is no communication between robots. String stability analysis on the resulting formation is performed. The results of the proposed method are verified by both simulations in Matlab® as well as measured data from the actual mobile robots.

Characterizing diversity in genetic programming

In many evolutionary algorithms candidate solutions run the risk of getting stuck in local optima after a few generations of optimization. In this paper two improved approaches to measure population diversity are proposed and validated using two traditional test problems in genetic programming literature. Code growth gave rise to improve pseudo-isomorph measures by eliminating non-functional code using an expression simplifier. Also, Roscas entropy to measure behavioral diversity is updated to cope with problems producing a more continuous fitness value. Results show a relevant improvement with regard to the original diversity measures.

A comparative study of two different regression methods for radiographs in Polish youngsters estimating chronological age on third molars

AIM The aim of this study was to establish a third molar developmental database to model dental age of Polish youngsters, to investigate the rating level of the scores when dividing a year interval into a quarter of a year and to examine sex differences, left-right and upper-lower jaw asymmetry. MATERIAL AND METHODS A cross-sectional sample of 1048 orthopantomograms of 644 females and 404 males aged between 12 and 26 years was investigated using the scoring system of Gleiser and Hunt modified by Köhler. Reference tables according to age were split in a whole year and in quarters of a year using descriptive statistics. The various developmental stages between males and females were analyzed with a paired t-test and the cusum method. Differences in mineralization between the quadrants were analyzed with a two-factor ANOVA and the Duncan post hoc test. The single quadratic and support vector regression were performed to describe the relationship between score and age. RESULTS Dividing age classes in quarters of a year discriminated better between individuals provided that there is a sufficient sampling size for all age classes. The mineralization tempo occurred significantly at a faster rate in males. The maturational events in the upper arch developed significantly at earlier ages for both genders. Obtained chronological age had nearly the same standard error of estimate when calculated with both regression methods. DISCUSSION AND CONCLUSION Comparing the results of the present study with those of other population groups suggests that there are differences in the ageing process of the wisdom tooth. This is the first database of Polish youngsters (15-24 years) with their respective regression equations to yield age estimations.

Prediction of arthritis using a modified Kohonen mapping and case based reasoning

Abstract Rheumatoid arthritis and spondyloarthropathy are the two most frequent forms of chronic autoimmune arthritis. These diseases lead to important inflammatory symptoms resulting in an important functional impairment. In this paper we apply a topological mapping combined with a case based reasoning evaluation criterion to predict early arthritis. The first part presents a brief introduction to the problem and self-learning neural networks while the second part of this paper will apply this technique together with a case based reasoning evaluation criterion to diagnostic classification. Finally the paper shows that the Kohonen neural network achieves good performance that exceeds the results of other neural network approaches and decision trees.