0000000000652835

AUTHOR

Maxime Yochum

showing 11 related works from this author

Estimation of Muscular Fatigue under Electromyostimulation Using CWT

2012

International audience; The aims of this study are to investigate muscular fatigue and to propose a new fatigue index based on the continuous wavelet transform (CWT) which is compared to the standard fatigue indexes from literature. Fatigue indexes are all based on the electrical activity of muscles (electromyogram) acquired during an electrically stimulated contraction thanks to two modules (electromyostimulation + electromyography recording) that can analyze EMG signals in real time during electromyostimulation. The extracted parameters are compared with each other and their sensitivity to noise is studied. The effect of truncation of M waves is then investigated, enlightening the robustn…

AdultMaletruncationwavelet.Acoustics0206 medical engineeringBiomedical EngineeringWavelet Analysis02 engineering and technologyElectromyography03 medical and health sciences0302 clinical medicineWaveletwaveletmedicineHumansContinuous wavelet transformMathematicsMuscle fatiguemedicine.diagnostic_testMuscle fatigueElectromyographyBiomechanicsWavelet transform020601 biomedical engineering[SPI.TRON] Engineering Sciences [physics]/ElectronicsElectric StimulationElectromyogram[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsForearmMuscular fatigueArmElectromyostimulation030217 neurology & neurosurgeryBiomedical engineering
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Multi axis representation and Euclidean distance of muscle fatigue indexes during evoked contractions

2014

International audience; In this article, we proposed a new representation of muscular fatigue during evoked muscle contractions based on fatigue indexes such as peak to peak amplitude, RMS of the M wave, mean and median frequency and fatigue index calculated from continuous wavelet transform (I CWT). These new representations of muscle fatigue using multi axis represented and Euclidean distance give better insights on changes in physiological characteristics during muscle fatigue. This technique provides a fatigue index using several muscle characteristics. The use of other kinds of fatigue characteristics as force could also be possible.

medicine.diagnostic_testMuscle fatigueSpeech recognitionMulti axis0206 medical engineeringMathematical analysis02 engineering and technologyElectromyography[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing020601 biomedical engineering[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsEuclidean distance03 medical and health sciences0302 clinical medicineAmplitudeMuscular fatiguemedicineRepresentation (mathematics)[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing030217 neurology & neurosurgeryContinuous wavelet transform[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMathematics
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Mise en œuvre d’une chaîne d’acquisition et de traitement du signal : Application à la mesure du rythme cardiaque en licence 1ère année

2014

International audience; Dans le cadre de cet article, nous présentons un projet de travaux pratiques mis en place dans le cadre d’un module intitulé « Sciences et Traitement de l’Information ». L’objectif pédagogique de ce module est de donner aux étudiants de 1ère année de Licence un aperçu applicatif de l’électronique, du traitement du signal et de l’informatique. Cette découverte se fait au travers de la réalisation d’un système d’acquisition et de traitement, ce projet étant découpé en fonctions de base qui sont étudiées d’abord séparément avant d’être regroupées pour aboutir à une application réelle. La mise en place de ce module date de la rentrée 2012-2013 et le retour d’expérience m…

[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/Electronics
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Automatic detection of P, QRS and T patterns in 12 leads ECG signal based on CWT

2016

International audience; In this paper, a new method based on the continuous wavelet transform is described in order to detect the QRS, P and T waves. QRS, P and T waves may be distinguished from noise, baseline drift or irregular heartbeats. The algorithm, described in this paper, has been evaluated using the Computers in Cardiology (CinC) Challenge 2011 database and also applied on the MIT-BIH Arrhythmia database (MITDB). The data from the CinC Challenge 2011 are standard 12 ECG leads recordings with full diagnostic bandwidth compared to the MITDB which only includes two leads for each ECG signal. Firstly, our algorithm is validated using fifty 12 leads ECG samples from the CinC collection…

[ MATH ] Mathematics [math][ INFO ] Computer Science [cs]Computer science0206 medical engineeringYouden's J statisticHealth Informatics[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyQRS[SPI]Engineering Sciences [physics]QRS complexT waveT waves0202 electrical engineering electronic engineering information engineering[ SPI ] Engineering Sciences [physics][INFO]Computer Science [cs][MATH]Mathematics [math]wavelet transformContinuous wavelet transformECGPdelineationECGP waveWavelet transformP020601 biomedical engineering3. Good healthSignal Processing020201 artificial intelligence & image processingEcg leadEcg signalAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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A mixed FES/EMG system for real time analysis of muscular fatigue

2010

International audience; In this article, we present a functional electrical stimulator allowing the extraction in real time of M-wave characteristics from resulting EMG recodings in order to quantify muscle fatigue. This system is composed of three parts. A Labview software managing the stimulation output and electromyogram (EMG) input signal, a hardware part amplifying the output and input signal and a link between the two previous parts which is made up from input/output module (NIdaq USB 6251). In order to characterize the fatigue level, the Continuous Wavelet Transform is applied yielding a local maxima detection. The fatigue is represented on a scale from 0 for a fine shaped muscle to …

Engineering0206 medical engineering02 engineering and technologyElectromyographyUSBSensitivity and SpecificitySignallaw.invention03 medical and health sciences0302 clinical medicinelawElectronic engineeringmedicineHumansMuscle SkeletalSimulationContinuous wavelet transformMuscle fatiguemedicine.diagnostic_testElectromyographybusiness.industryReproducibility of ResultsWavelet transformEquipment Design020601 biomedical engineeringElectric Stimulation[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsEquipment Failure AnalysisMaxima and minimaMuscle Fatiguemedicine.symptombusinessAlgorithmsSoftware030217 neurology & neurosurgeryMuscle ContractionMuscle contraction2010 Annual International Conference of the IEEE Engineering in Medicine and Biology
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Truncation effects on muscular fatigue indexes based on M waves analysis

2012

International audience; In this paper, we investigate muscular fatigue. We propose a new fatigue index based on the continuous wavelet transform (CWT) and compare it with the standard fatigue indexes from literature. Fatigue indexes are all based on the electrical activity of muscles (electromyogram) acquired during an electrically stimulated contraction (ES). The stimulator and electromyogram system, which were presented in a previous work, allows real-time analysis. The extracted fatigue parameters are compared between each other and their sensitivity to noise is studied. The effect of truncation of M waves is then investigated, enlightening the robustness of the index obtained using CWT.

medicine.diagnostic_testElectromyographyAcousticsSpeech recognition0206 medical engineering02 engineering and technologyElectromyography020601 biomedical engineering[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/Electronics03 medical and health sciences0302 clinical medicineMuscular fatigueMuscle FatiguemedicineHumans030217 neurology & neurosurgeryContinuous wavelet transformMathematics
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EMG artifacts removal during electrical stimulation, a CWT based technique

2014

International audience; A technique of artifacts removal based on the continuous wavelet transform is presented. It uses common mother wavelets to find the temporal localization of stimulation artifacts on electromyogram (EMG) signal during an electrically evoked contraction of a muscle. This method can be used with standard stimulation pulse waveforms like monophasics or biphasics ones. It uses a histogram representation to find the best threshold to apply on the CWT domain. The algotithm is presented with Haar wavelet and then it is used with common wavelet famillies such as Daubechies or Symlets.

Discrete wavelet transformstimulation artifacts0206 medical engineering02 engineering and technologyElectromyography[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing03 medical and health sciences0302 clinical medicineWaveletHistogramwaveletmedicineSource separationWaveformComputer visionContinuous wavelet transformMathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing030222 orthopedicsmedicine.diagnostic_testbusiness.industryhistogram representationPattern recognition020601 biomedical engineeringHaar waveletElectromyogram[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronicssource separationArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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A real time electromyostimulator linked with EMG analysis device

2013

International audience; In this study, a new system composed of two modules (electromyostimulation + electromyography recording) is presented. It can analyze in real time EMG signals during electromyostimulation. In addition, we propose a new method based on wavelet decomposition to analyze changes in M-wave characteristics. It leads to introduce a new index related to muscular fatigue.

EngineeringIndex (economics)medicine.diagnostic_testbusiness.industrySpeech recognition0206 medical engineeringBiomedical EngineeringBiophysics02 engineering and technologyElectromyography020601 biomedical engineering[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/Electronics03 medical and health sciences0302 clinical medicineWavelet decompositionMuscular fatiguemedicinebusiness030217 neurology & neurosurgery
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On the control of a muscular force model including muscular fatigue

2015

Electromyostimulation has been used for several decades by athletes or physiotherapists in order to create a muscular reinforcement. However, the efficiency of electromyostimulation is limited by muscular fatigue and by induced pain. Currently, the systems of electromyostimulation do not adapt the stimulation parameters automatically by taking into account physiological parameters such as muscular fatigue. To adapt the stimulation parameters to muscular responses and in order to optimize the rehabilitation sessions, a control of force using an indicator of muscular fatigue could be used. In this paper, we propose two ways to control the force by using a physiological model which includes th…

musculoskeletal diseasesPhysiological modelmedicine.medical_specialtyRehabilitationPhysical medicine and rehabilitationmedicine.medical_treatmentMuscular fatiguemedicineMuscular forcePsychology2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)
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QUANTIFICATION OF MUSCLE FATIGUE WITHWAVELET ANALYSIS BASED ON EMG DURING MYOELECTRICAL STIMULATION

2012

6; International audience; We propose a device dedicated to real time analysis of electromyograms (EMG) under myoelectrical stimulation (ES). The muscular fatigue analysis, which is obtained by the use of a dedicated analog circuit and a processing part, is the main purpose of this study. The description of a hardware device which incorporates an electro-stimulator and an electromyogram amplifier combined to a computer is detailed. Then, we present a muscular fatigue analysis part based on wavelet decomposition in order to extract a fatigue index, which is confronted with synthetic and experimental data. We conclude that the CWT index applies well to M waves. The noise sensitivity is invest…

Electrical stimulation.Electrical stimulationWavelet[SPI.TRON] Engineering Sciences [physics]/ElectronicsFatigueElectromyogram[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/Electronics
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Contribution to the design of a smart electromyostimulator

2013

This project aims to develop a new tool for neuromuscular reeducation. Its function is to improve the quality and the duration of muscular strengthening training sessions and training of motor function for patients suffering from muscle deconditioning. A "smart" electromyostimulator using, at the same time, techniques of electrostimulation (EMS) and analysis of electromyography (EMG) allows the control in real time electrical stimulation parameters considering the physiological fatigue of the stimulated muscle. This control, performed on stimulation parameters depending on electrical response of muscles (M wave), allows the muscle stimulation taking into account the muscular reaction to the…

[SDV.MHEP] Life Sciences [q-bio]/Human health and pathologyÉlectromyostimulateurElectromyostimulatorOnde MAnalyse en ondeletteWavelet analysisM-waveFatigue musculaireElectromyogramÉlectromyogrammeMuscle fatigue
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