Samuel Boudet

Expanded Disability Status Scale (EDSS) estimation in multiple sclerosis from posturographic data

Expanded Disability Status Scale (EDSS) is the most widely used clinical scale to evaluate levels of multiple sclerosis (MS). As MS can lead to disruptions in the regulation of balance and the disability can be evaluated by force platform posturography, we have developed in this study a new strategy to estimate EDSS from posturographic data. 118 volunteers with EDSS ranging from 0 to 4.5 participated in this study, with eyes closed. By using second-order polynomial regression models, EDSS was estimated from two postural sway parameters, respectively, the length and the surface and four recurrence quantification analysis (RQA) parameters: percentage of recurrence (%Rec), Shannon entropy (Ent), mean diagonal line length (LL) and trapping time (TT). In addition, all four RQA parameters were calculated for position, instantaneous velocity and acceleration of the center of pressure. In order to select the most accurate method for estimating EDSS, four statistical indices (percentage of agreement, underestimation and overestimation, as well as Mean error) were calculated comparing clinical and estimated EDSS scores. The results demonstrate that estimations of EDSS from surface, %Rec and LL of position, best agreed with clinical scores. This study emphasizes the possibility of distinguishing EDSS scores using postural sway and RQA parameters.

Improvements of Adaptive Filtering by Optimal Projection to filter different artifact types on long duration EEG recordings

Adaptive Filtering by Optimal Projection (AFOP) is an automatic method for reducing ocular and muscular artifacts on electro-encephalographic (EEG) recordings. This paper presents two additions to this method: an improvement of the stability of ocular artifact filtering and an adaptation of the method for filtering electrode artifacts. With these improvements, it is possible to reduce almost all the current types of artifacts, while preserving brain signals, particularly those characterising epilepsy. This generalised method consists of dividing the signal into several time-frequency windows, and in applying different spatial filters to each. Two steps are required to define one of these spatial filters: the first step consists of defining artifact spatial projection using the Common Spatial Pattern (CSP) method and the second consists of defining EEG spatial projection via regression. For this second step, a progressive orthogonalisation process is proposed to improve stability. This method has been tested on long-duration EEG recordings of epileptic patients. A neurologist quantified the ratio of removed artifacts and the ratio of preserved EEG. Among the 330 artifacted pages used for evaluation, readability was judged better for 78% of pages, equal for 20% of pages, and worse for 2%. Artifact amplitudes were reduced by 80% on average. At the same time, brain sources were preserved in amplitude from 70% to 95% depending on the type of waves (alpha, theta, delta, spikes, etc.). A blind comparison with manual Independent Component Analysis (ICA) was also realised. The results show that this method is competitive and useful for routine clinical practice.

A global approach for automatic artifact removal for standard EEG record.

The EEG signal is a record of the brain activity using multiple electrodes placed on the scalp. Unfortunately, it can be hardly contaminated by a lot of noises called artifacts. These latter can be generated by various actions such as eye blinks, eye movements or the skeletal muscle activities (jaw, forehead, ...). This study will focus on a global artifact removal method using independent component analysis (ICA) on signals cut in frequency bands. The interest of this method resides in automatizing the artifactual source identification and enables a global filtering of records using constant bases. A brief overview of the project will be made in order to introduce the method used. Next, the results will be presented and their validation will be discussed in the conclusion

BioSigPlot: An opensource tool for the visualization of multi-channel biomedical signals with Matlab

This paper presents a Matlab-based software (MathWorks inc.) called BioSigPlot for the visualization of multi-channel biomedical signals, particularly for the EEG. This tool is designed for researchers on both engineering and medicine who have to collaborate to visualize and analyze signals. It aims to provide a highly customizable interface for signal processing experimentation in order to plot several kinds of signals while integrating the common tools for physician. The main advantages compared to other existing programs are the multi-dataset displaying, the synchronization with video and the online processing. On top of that, this program uses object oriented programming, so that the interface can be controlled by both graphic controls and command lines. It can be used as EEGlab plug-in but, since it is not limited to EEG, it would be distributed separately. BioSigPlot is distributed free of charge (http://biosigplot.sourceforge.net), under the terms of GNU Public License for non-commercial use and open source development.

A Robust Method to Filter Various Types of Artifacts on Long Duration EEG Recordings

EEG is a system used to measure electrical brain activity using multiple electrodes placed on the scalp. Unfortunately, the signals can be easily contaminated by noises called artifacts. These can be generated by various actions such as eye blinks, eye movements, muscle activities or small electrode movements. This paper presents a global artifact removal method corresponding to an evolution of the AFOP method (Adaptive Filtering by Optimal Projection) in order to improve its stability. This evolution automatically filters ocular, muscular and heart beat artifacts. The results are validated on long duration EEG recordings containing pathological activities. An expert analysis shows that the cerebral signal is well conserved while a lot of artifacts are removed.

Evaluation of the AFOP/DAFOP method for automatic filtering of EEGs of patients with epilepsy.

Objective: Further developments in EEG monitoring necessitate new methods of filtering to eliminate artifacts, without transforming relevant signals. This article presents an automatic filtering of EEG recordings, based on a spatio-temporal method called Adaptive Filtering by Optimal Projection or Dual Adaptive Filtering by Optimal Projection. Evaluation of filtering methods is difficult, and comparisons between methods remain a challenge; here, we present a method to score the visual assessment of the EEG. The aim of this study was to evaluate an automatic filtering method, called Adaptive Filtering by Optimal Projection, improved by Dual Adaptive Filtering by Optimal Projection, of EEG recordings of patients with epilepsy. Methods: Two hundred forty-eight nonfiltered EEG segments of 20 seconds each were selected from 35 EEG recordings of 27 different patients by 3 clinical neurophysiologists based on their content. The reading quality as well as the proportions of artifacts and of cerebral activity removed after filtering were evaluated on a scale of 0 to 4. The mean square difference of amplitude before and after filtering was computed in specific spectral band. Results: The artifacts were largely removed (82% for muscular, 72% for ocular, and 71% for electrode artifacts). The readability was improved on an average by two points for pages containing epileptic seizures, and by one point for those containing alpha rhythms, slow waves, and spikes. After filtering, consistency tests showed a consensus (Spearman correlation [0.69–0.79]) on the removal of the artifact versus loss of information. The spectral analysis showed equivalent results (0.16% mean square difference in the alpha band). Conclusions: Our filtering method is effective in removing artifacts without altering relevant signals. The significance is that we evaluated a new automated method of filtering EEG that is easy to use for both for the analysis of routine EEG and in the field of epilepsy at large.

Semi-automated image analysis of gel electrophoresis of cerebrospinal fluid for oligoclonal band detection

Detection of oligoclonal electrophoretic bands in cerebrospinal fluid (CSF) is an important diagnostic tool for Multiple Sclerosis (MS). Electrophoretic profiles are difficult to interpret due to low contrast and artefacts. A semi-automated method to ease analysis and to reduce subjectivity is presented. The method sequentially converts color images to grayscale, realigns bands, removes artifacts, then converts 2D images to a signal, before detecting, thresholding and editing peaks to optimize profiles. Such treated profiles (21 positive and 15 negative) are compared to ground truth analysis of an expert biologist. 16 profiles over 21 are well detected positive and 12 profiles over 15 are detected negative, results seem similar to inter-experts variability reported in literature.Detection of oligoclonal electrophoretic bands in cerebrospinal fluid (CSF) is an important diagnostic tool for Multiple Sclerosis (MS). Electrophoretic profiles are difficult to interpret due to low contrast and artefacts. A semi-automated method to ease analysis and to reduce subjectivity is presented. The method sequentially converts color images to grayscale, realigns bands, removes artifacts, then converts 2D images to a signal, before detecting, thresholding and editing peaks to optimize profiles. Such treated profiles (21 positive and 15 negative) are compared to ground truth analysis of an expert biologist. 16 profiles over 21 are well detected positive and 12 profiles over 15 are detected negative, results seem similar to inter-experts variability reported in literature.

An Online Viewer of FHR Signal for Research, E-Learning and Tele-Medicine

This paper presents a web viewer of Fetal Heart Rate (FHR) signals developed on HTML5/JavaScript. It provides an easy solution to remotely consult an FHR signal on a web browser without installing any specific software and it can be used either on a computer or on mobile device. There are three major applications of this tool. First, it is used to build up our FHR database used for research on signal processing and analysis. Secondly, it is used on our E-learning website e.RCF in order to train midwives and obstetricians to interpret FHR signals. At last, it could be used on telemedicine either on tele-monitoring to remotely check the fetal welfare, or on tele-expertise to enable practitioners to ask for specialists’ opinion. This viewer is designed to correspond to practitioners’ habits while including tools to ease the interpretation the FHR signal.

Arm-trunk coordination in wheelchair initiation displacement: A study of anticipatory and compensatory postural adjustments during different speeds and directions of propulsion

Arm-trunk coordination during the initiation of displacement in manual wheelchair is a complex task. The objective of this work is to study the arm-trunk coordination by measuring anticipatory and compensatory postural adjustments. Nine healthy subjects participated in the study after being trained in manual wheelchair. They were asked to initiate a displacement in manual wheelchair in three directions (forward vs. left vs. right), with two speeds (spontaneous vs. maximum) and with two initial hands positions (hands on thighs vs. hands on handrails). Muscular activities in the trunk (postural component) and the arms (focal component) were recorded bilaterally. The results show two strategies for trunk control: An anticipatory adjustment strategy and a compensatory adjustment strategy with a dominance of compensation. These two strategies are influenced by the finalities of displacement in terms of speed and direction depending on the hands positions. Arm-trunk coordination is characterized by an adaptability of anticipatory and compensatory postural adjustments. The study of this type of coordination for subjects with different levels of spinal cord injury could be used to predict the forthcoming displacement and thus assist the user in a complex task.

Benefits of physical activities centered on the trunk for pregnant women

ABSTRACT Objective: To examine the effect of a trunk exercise program on pain, quality of life (QoL) and physical health (PH) in the late pregnancy and post-partum periods as well as baby weight and size and delivery. Methods: 90 nulliparous women were allocated based on voluntarism to a training group (TG) or to a control group (CG). TG carried out a structured program with exercises for flexibility, balance and strengthening for the majority of skeletal muscles specifically for the spinal ones, between the 24th and 36th week of pregnancy. Both TG and CG were evaluated for pain at the beginning of the program (T1), at the end of the program (T2) and two months’ post-partum (T3). QoL was assessed at T1,T2 and T3, and PH at T1 and T3. Mann-Whitney test was utilized to compare TG and CG on each period and to compare the periods two by two. Results: At T1, no significant difference was found between the two groups in pain intensity (pain interference p = 0.317), QoL (p = 0.18) and PH (flexibility p = 0.06; walking p = 0.85). At T2, women of TG had a lower intensity of pain than CG (legs (p = 0.029), lower back (p < 0.0001), upper back (p = 0.022), pelvis (p = 0.017), groins (p = 0.043), lower pelvis (p = 0.009) and interference of pain (p < 0.0001)). At T3, TG had a lower intensity of pain than CG, in lower back and upper back (p < 0.0001) and interference of pain (p < 0.0001). Best scores of QoL were observed in TG compared to CG at T2 (p < 0.0001) and at T3 (p < 0.0001). PH in TG compared to CG was not different between the groups in T1 but was different in in T3 (flexibility p = 0.002, walking, balance, curling-ups and Ruffier p < 0.0001). TG were four times less likely to have a caesarean (p = 0.049) and had 4.5 h less of labor time (p < 0.0001). No difference was observed between the TG vs CG concerning the weight (p = 0.22) and the baby’s size (p = 0.11). Conclusion: Strengthening exercises centered on the trunk reduce pain, improve QoL and PH in late pregnancy and at two months in the post-partum period. Strengthening exercises also ease the delivery.