Laurent Peyrodie

• PhD, Associate Professor
• Lecturer at Junia

Introduction Music has a profound impact on human emotions, capable of eliciting a wide range of emotional responses, a phenomenon that has been effectively harnessed in the field of music therapy. Given the close relationship between music and language, researchers have begun to explore how music influences brain activity and cognitive processes b...

This paper explores the transformative potential of artificial intelligence (AI) in revolutionizing hospital management practices, particularly in enhancing operational and financial performance. The incorporation of artificial intelligence (AI) technologies, including machine learning, predictive analytics, and natural language processing, hospita...

Abstract Objectives: The objective of this study is to develop a bionic hand prototype that is optimized formedical prosthetic applications. Methods: The prototype would be designed to demonstrate structural integrity, functionaladaptability and long-term durability. The design incorporates a multi-degree-of-freedom (MDOF)structure and bio-inspired...

In recent years, osteoarthritis of the knee, a common degenerative joint disease, often occurs in the elderly population. This disease has a significant impact on the quality of life of patients. For treating knee osteoarthritis, physical therapy is highly regarded as a very effective treatment method. This article delves deeply into commonly used...

Objectives: Since it was first reported in 1943, the incidence of autism spectrum disorders has increased, and there have been numerous interventions, but there is no quantitative measure of diagnose effectiveness. Starting with traditional intervention methods for autism, this paper listed common intervention methods and found that the essential n...

This study examines the role of exercise prescriptions in controlling medical insurance costs amidst the increasing prevalence of chronic diseases and rising healthcare expenses. Exercise prescriptions are customized physical activity plans issued by healthcare professionals that aim to improve health outcomes and reduce the financial burden on hea...

Abstract Background: The application of music therapy spans a wide range of fields, including clinical medicine, psychology, and rehabilitation education, and has gained widespread recognition. In particular, music therapy is regarded as a significant intervention in the rehabilitation education of children with cerebral palsy, attracting attention...

The integration of exerciseprescription (EP) into health financialproducts represents an innovative approachto enhancing public health and managinghealthcare costs. This study explores thedesign and implementation of EP-basedhealth financial products, emphasizing thepotential health, economic, and socialbenefits. Through a comprehensiveliterature r...

Corporate health managementhas emerged as a pivotal strategic elementin today's competitive business landscape,emphasizing the indispensable role ofemployee health in enhancing productivityand driving business success. Exerciseprescription, tailored fitness programsdesigned specifically for individualemployees, stands as a cornerstone of thisholist...

This paper explores theintegration of operations research (OR)methodologies into exercise prescription toenhance the precision and effectiveness ofpersonalized exercise programs. Traditionalexercise prescriptions often fail to considerthe unique physiological and psychologicalfactors influencing an individual's responseto exercise. By leveraging OR...

Wound care is a critical aspect ofhealthcare, particularly in managingchronic and complex wounds, which requiremultifaceted approaches involving accurateassessment, appropriate intervention,continuous monitoring, and efficientresource allocation. The advent of artificialintelligence (AI) offers innovative solutionsto these long-standing challenges....

With the advancement of technology, the application of Artificial Intelligence (AI) in the field of medicine and rehabilitation is becoming increasingly widespread. However, how to effectively use these advanced technologies to improve rehabilitation outcomes remains an unresolved issue. This paper proposes a new AI-based VR rehabilitation method,...

Automatic and reliable detection of R Peak from electrocardiogram (ECG) signal is essential in both pathological and non-pathological applications. The presence of various kinds of noises and artifacts makes it still a challenging problem in the accurate and reliable extraction of ECG parameters in ambulatory conditions. In this paper, we present a...

Lower-limb exoskeletons have been proven to be beneficial for motor function disability patients, in both clinical rehabilitation settings and daily activities. However, exoskeletons for the pediatric field are still very limited. In this paper, a novel lower-limb exoskeleton design for children is presented. Based on the anthropometric data of the...

Assistive single-joint lower-limb exoskeletons have shown potential clinical benefits in patients with gait deficiencies. Torque-controlled exoskeletons, unlike position-controlled exoskeletons, do not restrict voluntary movements, allowing for safer interaction with the user. A torque-controlled hip flexion/extension exoskeleton intended for indiv...

Introduction: Cerebrospinal fluid (CSF) restricted oligoclonal bands (OCB) are the established immunological biomarker for multiple sclerosis diagnosis. Isoelectric focusing (IEF) and immunoblotting is the gold standard technique to detect OCB. Quantifying OCB remains a complex task: IEF lanes are often contaminated by band-like artefacts. Moreover...

We have developed deep learning models for automatic identification of the maternal heart rate (MHR) and, more generally, false signals (FSs) on fetal heart rate (FHR) recordings. The models can be used to preprocess FHR data prior to automated analysis or as a clinical alert system to assist the practitioner. Three models were developed and used t...

We have developed deep learning models for automatic identification of the maternal heart rate (MHR) and, more generally, false signals (FSs) on fetal heart rate (FHR) recordings. The models can be used to preprocess FHR data prior to automated analysis or as a clinical alert system to assist the practitioner. Three models were developed and used t...

The detection of immunoglobulin G (IgG) oligoclonal bands (OCB) in cerebrospinal fluid (CSF) by isoelectric focusing (IEF) is a valuable tool for the diagnosis of multiple sclerosis. Over the last decade, the results of our clinical research have suggested that tears are a non-invasive alternative to CSF. However, since tear samples have a lower Ig...

The fetal heart rate (FHR) is a screening signal for preventing fetal hypoxia during labor. When experts analyze this signal, they have to position a baseline and then identify decelerations and accelerations. These steps can potentially be automated and made more objective by signal processing analysis. Various methods have been described in the l...

The latest revision of multiple sclerosis diagnosis guidelines emphasizes the role of oligoclonal band detection in isoelectric focusing images of cerebrospinal fluid. Recent studies suggest tears as a promising noninvasive alternative to cerebrospinal fluid. We are developing the first automatic method for isoelectric focusing image analysis and o...

Balance impairment is one of the most common symptoms in people with multiple sclerosis (MS), even found in the early stages. In this chapter, we present an advanced technique to characterize balance disorders in MS using a static force platform, called static posturography. Many linear (temporal and spectral) parameters and nonlinear indicators ca...

Background: Automated fetal heart rate (FHR) analysis removes inter- and intra-expert variability, and is a promising solution for reducing the occurrence of fetal acidosis and the implementation of unnecessary medical procedures. The first steps in automated FHR analysis are determination of the baseline, and detection of accelerations and decele...

The fetal heart rate (FHR) is a screening signal for preventing fetal hypoxia during labor. When experts analyze this signal, they have to position a baseline and identify decelerations and accelerations. These steps can potentially be automated and made more objective by data processing analysis, but training and evaluation datasets are required....

The fetal heart rate (FHR) is a screening signal for preventing fetal hypoxia during labor. When experts analyze this signal, they have to position a baseline and then identify decelerations and accelerations. These steps can potentially be automated and made more objective by signal processing analysis. Various methods have been described in the l...

Abstract Background The fetal heart rate (FHR) serves as a guide to fetal well-being during the first stage of delivery. The visual morphological analysis of the FHR during labor is subject to inter- and intra-observer variability – particularly when the FHR is abnormal. It has been suggested that automatic analysis of the FHR can reduce this vari...

Background IgG concentrations in cerebrospinal fluid generally range from 20 to 45 mg/L. In multiple sclerosis immune reactions lead to intrathecal synthesis of specific IgGs that can be detected in biological fluid samples both quantitatively and qualitatively by isoelectric focusing of supplementary oligoclonal IgG bands. Method A simple tool, u...

A model-free based neural network control with time-delay estimation (TDE-MFNNC) for lower extremity exoskeleton is presented in this paper. The lower limb exoskeleton which has 5 DOFs for each leg is established in Solidworks as a virtual prototype which is used as a platform to build the control system in SimMechanics. In an attempt to get the ef...

Purpose Adolescent idiopathic scoliosis (AIS) is a three-dimensional deformity of the spine associated with disturbed postural control. Cervical proprioception participates in controlling orthostatic posture via its influence on head stabilization. We hypothesized that patients with AIS exhibit altered cervical proprioception. Methods We conducted...

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 image...

Visual analysis of fetal heart rate (FHR) during labor is subject to inter- and intra-observer variability that is particularly troublesome for anomalous recordings. Automatic FHR analysis has been proposed as a promising way to reduce this variability. The major difficulty with automatic analysis is to determine the baseline from which acceleratio...

The Expanded Disability Status Scale (EDSS) is the most widely used scale to evaluate the degree of neurological impairment in multiple sclerosis (MS). In this paper, we report on the evaluation of an EDSS modeling strategy based on recurrence quantification analysis (RQA) of posturographic data (i.e., center of pressure, COP). A total of 133 volun...

Walk training research with children having multiple disabilities is presented. Orthosis aid in walking for children with multiple disabilities such as Cerebral Palsy continues to be a clinical and technological challenge. In order to reduce pain and improve treatment strategies, an intermediate structure – humanoid robot NAO – is proposed as an as...

In this paper, we have proposed a new framework to use both PET and CT images simultaneously for tumor segmentation. Our method combines the strength of each imaging modality: the superior contrast of PET and the superior spatial resolution of CT. We formulate this problem as a Non-Local Active Contours (NL-AC) based-variational segmentation framew...

Prostate contours delineation on Magnetic Resonance (MR) images is a challenging and important task in medical imaging with applications of guiding biopsy, surgery and therapy. While a fully automated method is highly desired for this application, it can be a very difficult task due to the structure and surrounding tissues of the prostate gland. Tr...

Cone-beam computed tomography (CBCT) image-guided radiotherapy (IGRT) systems are widely used tools to verify and correct the target position before each fraction, allowing to maximize treatment accuracy and precision. In this study, we evaluate automatic three-dimensional intensity-based rigid registration (RR) methods for prostate setup correctio...

Objectives: A new artificial intelligent method ‘Support Center Machines’ (SCM) for helping diagnosis and prognosis is applied to a medical system. Methods In data processing, SCM seeks the true centers of each class during machine learning. For application in the medical system, it makes these centers as health-situation models and translates all...

Muscle artifacts constitute one of the major problems in electroencephalogram (EEG) examinations, particularly for the diagnosis of epilepsy, where pathological rhythms occur within the same frequency bands as those of artifacts. This paper proposes to use the method dual adaptive filtering by optimal projection (DAFOP) to automatically remove arti...

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 f...

In this paper, we study Active Contours (AC) based globally segmentation for vector valued images using evidential Kullback-Leibler (KL) distance. We investigate the evidential framework to fuse multiple features issued from vector-valued images. This formulation has two main advantages: 1) by the combination of foreground/background issued from th...

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 si...

We propose to evaluate automatic three-dimensional gray-value rigid registration (RR) methods for prostate localization on cone-beam computed tomography (CBCT) scans. In total, 103 CBCT scans of 9 prostate patients have been analyzed. Each one was registered to the planning CT scan using different methods: (a) global RR, (b) pelvis bone structure R...

We evaluated automatic three-dimensional intensity-based rigid registration (RR) methods for prostate localization on CBCT scans and studied the impact of rectum distension on registration quality. 106 CBCT scans of 9 prostate patients were used. Each one was registered to the planning computed tomography (CT) scan using different methods: (a) glob...

We present a new interactive segmentation framework to delineate the prostate from MR images. We first explicitly address the segmentation problem based on fast globally Finsler Active Contours (FAC) by incorporating both statistical and geometric shape prior knowledge. In doing so, we are able to exploit the more global aspects of segmentation by...

We implemented the shape-based interpolation method described by Raya and Udupa in 1990 for three-dimensional images, and created two standalone filters using the Insight Toolkit ITK. The image to be interpolated must be a 3D binary image which represents an object as a series of 2D slices with pixel values at 1 inside the object and 0 outside by c...

In this paper, we propose a new framework for Binary Active Contours (AC) that incorporates a new texture descriptor. The texture descriptor is split into inside/ outside region descriptors. Both the inside and outside texture descriptors discriminate the texture using Kullback-Leibler distance. Using these two descriptors, the AC incorporates both...

We present a new unsupervised segmentation based active contours model and local region texture descriptor. The proposed local region texture descriptor intrinsically describes the geometry of textural regions using the shape operator defined in Beltrami framework. The local texture descriptor is incorporated in the active contours using the Cauchy...

We present a new globally supervised segmentation method in the characteristic function framework based on an active contours (AC) model incorporating both shape prior and texture descriptors. The shape prior descriptor is formulated as the traditional Legendre moment and the texture descriptor as a linear combination of local inside/outside textur...

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 vo...

Objective: A general method was developed to analyze and describe tree-like structures needed for evaluation of complex morphology, such as the cerebral vascular tree. Clinical application of the method in neurosurgery includes planning of the surgeon's intraoperative gestures. Method: We have developed a 3D skeletonization method adapted to tub...

We present a new interactive segmentation framework to segment the prostate from MR prostate imagery. We first explicitly address the segmentation problem based on fast globally Finsler Active Contours (FAC) by incorporating both statistical and geometric shape prior knowledge. In doing so, we are able to exploit the more global aspects of segmenta...

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 i...

In this paper we proposed a new segmentation method based Fast Finsler Active Contours (FFAC). The FFAC is formulated in the Total Variation (TV) framework incorporating both region and shape descriptors. In the Finsler metrics, the anisotropic boundary descriptor favorites strong edge locations and suitable directions aligned with dark to bright i...

One drawback of the growth in conformal radiotherapy and image-guided radiotherapy is the increased time needed to define the volumes of interest. This also results in inter- and intra-observer variability. However, developments in computing and image processing have enabled these tasks to be partially or totally automated. This article will provid...

One drawback of the growth in conformal radiotherapy and image-guided radiotherapy is the increased time needed to define the volumes of interest. This also results in inter- and intra-observer variability. However, developments in computing and image processing have enabled these tasks to be partially or totally automated. This article will provid...

We propose a new semi-automatic segmentation based Active Contour Model and statistic prior knowledge of Multiple Sclerosis (MS) Lesions in Regions Of Interest (RIO) within brain Magnetic Resonance Images(MRI). Reliable segmentation of MS lesion is important for at least three types of practical applications: pharmaceutical trails, making decision...

This paper describes the methodology and the evaluation of a 3D skeletonization algorithm applied on brain vascular structure. This method is based on the application of the minimum cost-spanning tree using Dijkstra's algorithm and seems well appropriate to tubular objects. We briefly describe the different steps, from the segmentation to the skele...

Neurological diseases can cause atrophy of the corpus callosum resulting in a change in its size and shape. The measurement and analysis of this change is one of the goals of clinical research. We perform statistical analysis of the shape of the corpus callosum extracted from MR brain scans of a group of multiple sclerosis patients undergoing a lon...

Le but de cette étude est d’établir la corrélation entre le niveau de handicap évalué par l’Expanded Disability Status Scale (EDSS) et les données issues d’une plateforme de mesure d’équilibre pour des sujets atteints de Sclérose En Plaques (SEP).La base de données est constituée de 96 patients et de 90 sujets sains appariés par age et sexe. Aucun...

The aim of this work is to present an automatic system to determine in vivo movement of prosthesis elements using fluoroscopy video. During continuous flexion-extension knee movements for different components of the prosthesis are recorded on a PC. The contours of the prosthesis's parts are segmented using based level set segmentation method. Final...

We present a new unsupervised segmentation based active contours model and texture descriptor. The proposed texture descriptor intrinsically describes the geometry of textural regions using the shape operator defined in Beltrami framework. We use Bhattacharyya distance to discriminate textures by maximizing distance between the probability density...

We present a new unsupervised segmentation of textural images based on integration of texture descriptor in formulation of active contour. The proposed texture descriptor intrinsically describes the geometry of textural regions using the shape operator defined in Beltrami framework. We use Battachryya distance to define an active contour model whic...

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...

HEI (Ecole des Hautes Etudes d’ingénieur), école généraliste, possédant un ensemble de cursus professionnalisant appelés « Domaines » a ouvert un domaine de formation en ingénierie médicale et santé depuis deux ans. De profil généraliste, sa connaissance des structures de santé et sa formation permettront à l’ingénieur issu de cette formation d’êtr...

Cet article met en évidence des phénomènes physiologiques apparaissant dans le P300 speller. La méthode Common Spatial Pattern (CSP) est utilisée pour amplifier les potentiels évoqués (ERP) endogènes utilisés pour la classification. Cette méthode est également utilisée pour montrer le processus de propagation du signal dans le cerveau. Les résultat...

A new approach to filter multi-channel signals is presented, called filtering by optimal projection (FOP) in this paper. This approach is based on common spatial subspace decomposition (CSSD) theory. Moreover, an evolution of this method for non-stationary signals is also introduced which is called adaptative FOP (AFOP). As ICA, a filtering matrix...

Introduction L’EEG a été utilisé dans la sclérose en plaques (SEP) à partir de l’analyse visuelle puis spectrale et enfin de la cohérence. Nous proposons de recourir ici aux méthodes mathématiques d’analyse non linéaire. Objectifs L’objectif est d’utiliser l’analyse dynamique du signal EEG afin de déceler des modifications précoces présentes dès l...

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...

Epilepsy is characterized by the sudden occurrence of seizures disturbing the epileptic patients. Several nonlinear methods have been suggested to predict the onset of epileptic seizures from intracranial or scalp electroencephalogram (EEG) data as "dynamical similarity index analysis" and the "correlation dimension method". Here, special interest...

The application of the nonlinear mathematical methods to the electroencephalographic signals (EEG signals) began in 1985. One of the most promising approaches to define and determine, complexity, nonlinearity and nonstationnarity of EEG signals is recurrences method initiated by Eckmann, Kamphorst and Ruelle in 1987 under RP name then by Webber, Zb...

The EEG signal, a recording of the brain activity using multiple electrodes placed on the scalp, can be hardly contaminated by a lot of noises called artifacts. The artifacts are generated by the action of the skeletal muscles such as: eye movements, jaw clenching, etc. Indeed, the signals recorded are mixture of phenomenon from multiple generators...

Very early after the discovery of the EEG, a certain number of authors tried to apply the mathematical tools to the treatment of this signal which appears complex, in spite of its relatively narrow band-width. The goal of this work is to show that the simple mathematical tools resulting from the theory of chaos, seem particularly promising to appre...