Analysis of Muscle's Electrical Activity During Dynamic Fatiguing Exercise Using Visibility Graph and Degree Statistics
01 Oct 2018-
TL;DR: In this article, the degree distribution of visibility graphs was used to analyze surface electromyography (sEMG) signals in non-fatigue and fatigue conditions with a total of 58 subjects volunteered for the study.
Abstract: The reduction in muscle force is a common symptom of several neuromuscular diseases. This phenomenon is called muscle fatigue. In normal subjects, it is generally reversible. Surface electromyography (sEMG) signals are commonly used to analyze muscle fatigue. These signals are nonlinear and nonstationary in nature. In this work, an attempt is made to analyse sEMG signals in nonfatigue and fatigue conditions using the degree distribution of visibility graphs. The sEMG signals are recorded from the upper limb muscle namely the biceps brachii during dynamic contraction with a six-kilogram load. A total of 58 subjects volunteered for the study. The signals are preprocessed, and visibility graphs are constructed. The variation in the degree distribution is studied and characterized. The results indicate that the signals recorded are complex in nature. The degree distributions are distinct between nonfatigue and fatigue conditions. In fatigue, the percentage of higher degree nodes are more. Further, the decay rate of degree is larger in the case of nonfatigue indicating the signal is comparatively random. The statistical test indicates that the features extracted are significant with a $\mathbf{p} . It appears that this method of analysis would be useful for characterizing various neuromuscular conditions.
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TL;DR: This book serves as an introduction to the field of biomedical engineering for students with undergraduate training in engineering, physics, and mathematics and serves as a background for students or practitioners whose prior training has not included this material.
Abstract: Biomedical Engineering Principles Arthur B. Ritter, Stanley Reisman, and Bozena B. Michniak, CRC Press, Taylor and Francis Group, 2005. ISBN: 0824796160, 680 pages, US$99.95. This book serves as an introduction to the field of biomedical engineering for students with undergraduate training in engineering, physics, and mathematics. This book can be used for senioror graduate-level classes at universities, for short courses, or as a general knowledge book for practicing engineers wanting to learn more about biomedical engineering. The classic description of biomedical engineering is that it is the application of engineering analysis to problems in medicine and life sciences. Biomedical engineering is not one discipline but several interacting disciplines that coexist within the same field. Since biomedical engineering cuts across several engineering disciplines, the book is divided into several sections. Each section is intended to be complementary and to serve as a background for students or practitioners whose prior training has not included this material. The first section addresses modeling, transport processes, cell physiology, and the cardiovascular system. Chapter 1 presents an overview and introduction to engineering analysis of physiological systems, the nature of biological data, and the role of models and simulation in experimental design. The chapter introduces the concepts of conservation of mass, compartments, convection, and diffusion. It also develops pharmacokinetic models for drug distribution. Chapter 2 covers cell physiology and transport, introducing the primary mechanisms by which water and solutes get into and out of cells. Chapter 3 covers the fundamentals of hemodynamics and the nature of blood and blood vessels as engineering materials. Chapter 4 is an introduction to the cardiovascular system, covering the cardiac conduction pathway, control of heart rate, EKG measurement and interpretation, cardiac output, cardiac work, and autonomic and local regulation of blood flow. The second section of the book reviews the concepts of biomedical signal processing. Chapter 5 discusses biomedical signals and how to represent them. The frequency content of a signal, periodic functions, and Fourier series are reviewed. Chapter 6 discusses signal acquisition and processing. Topics include sampling theorem, sampling rate, and aliasing. Chapter 7 discusses techniques for physiological signal processing. Topics include AR modeling, time-frequency analysis, short-time Fourier transforms, and quadratic distributions. Chapter 8 contains examples of physiological signal processing. The third section of the book contains an introduction to and practical applications of biomechanics. Chapter 9 is an introduction to the principles of biomechanics and discusses the analysis of human movement, human dynamics, measurements of muscle force, electrical stimulation of skeletal muscle, mechanical characteristics of biological materials, bone remodeling, body cycles, thermal regulation, and hypothermia. Chapter 10 contains a discussion of some practical applications of biomechanics, using the principles developed in Chapter 9. The fourth section of the book presents an introduction to tissue engineering. Chapter 11 covers the history of tissue engineering, materials, biological interactions, and the role of cells in tissue engineering. Applications of tissue engineering in skin equivalents, cardiovascular components, bone regrowth, muscle tissue, and nerve regeneration are also discussed. Chapter 12 looks at future developments in biomedical engineering. For university faculty, the book is an excellent textbook for a class. Each chapter contains numerous examples and contains many figures to enhance learning. References and suggestions for further reading are included at the end of each chapter. Problems are included at the end of chapters, where they will best test the student's knowledge. For practicing engineers without a biomedical engineering background, the book provides an excellent resource to explain the many intricacies of biomedical engineering and provides sufficient background material to make the subject understandable. —Richard C. Fries, PE, CRE Baxter Healthcare, Inc.
145 citations
TL;DR: Surface electromyography is a non-invasive technique to assess the electrical activity of contracting skeletal muscles that plays a key role in muscle fatigue detection in sports medicine.
Abstract: Surface electromyography (sEMG) is a non-invasive technique to assess the electrical activity of contracting skeletal muscles. sEMG-based muscle fatigue detection plays a key role in sports medicin...
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TL;DR: A simple and fast computational method, the visibility algorithm, that converts a time series into a graph, which inherits several properties of the series in its structure, enhancing the fact that power law degree distributions are related to fractality.
Abstract: In this work we present a simple and fast computational method, the visibility algorithm, that converts a time series into a graph. The constructed graph inherits several properties of the series in its structure. Thereby, periodic series convert into regular graphs, and random series do so into random graphs. Moreover, fractal series convert into scale-free networks, enhancing the fact that power law degree distributions are related to fractality, something highly discussed recently. Some remarkable examples and analytical tools are outlined to test the method's reliability. Many different measures, recently developed in the complex network theory, could by means of this new approach characterize time series from a new point of view.
1,320 citations
"Analysis of Muscle's Electrical Act..." refers background or methods in this paper
...One such method of reconstruction is the visibility graph method [10-12]....
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...The variation in the degree and the rate of decay has been used to understand the level of randomness of a signal [10]....
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...Recently, visibility graph-based techniques have been introduced to understand the self-similar properties of the signals [10]....
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28 Jan 2005
TL;DR: This work focuses on the development of models for Surface EMG Signal Generation based on the principles of Structure--Based SEMG models, which were developed in the context of motor control and Muscle Contraction.
Abstract: Introduction. Contributors. 1 BASIC PHYSIOLOGY AND BIOPHYSICS OF EMG SIGNAL GENERATION (T. Moritani, D. Stegeman, R. Merletti). 1.1 Introduction. 1.2 Basic Physiology of Motor Control and Muscle Contraction. 1.3 Basic Electrophysiology of the Muscle Cell Membrane. References. 2 NEEDLE AND WIRE DETECTION TECHNIQUES (J. V. Trontelj, J. Jabre, M. Mihelin). 2.1 Anatomical and Physiological Background of Intramuscular Recording. 2.2 Recording Characteristics of Needle Electrodes. 2.3 Conventional Needle EMG. 2.4 Special Needle Recording Techniques. 2.5 Physical Characteristics of Needle EMG Signals. 2.6 Recording Equipment. References. 3 DECOMPOSITION OF INTRAMUSCULAR EMG SIGNALS (D. W. Stashuk, D. Farina, K. Sogaard). 3.1 Introduction. 3.2 Basic Steps for EMG Signal Decomposition. 3.3 Evaluation of Performance of EMG Signal Decomposition Algorithms. 3.4 Applications of Results of the Decomposition of an Intramuscular EMG Signal. 3.5 Conclusions. References. 4 BIOPHYSICS OF THE GENERATION OF EMG SIGNALS (D. Farina, R. Merletti, D. F. Stegeman). 4.1 Introduction. 4.2 EMG Signal Generation. 4.3 Crosstalk. 4.4 Relationships between Surface EMG Features and Developed Force. 4.5 Conclusions. References. 5 DETECTION AND CONDITIONING OF THE SURFACE EMG SIGNAL (R. Merletti, H. Hermens). 5.1 Introduction. 5.2 Electrodes: Their Transfer Function. 5.3 Electrodes: Their Impedance, Noise, and dc Voltages. 5.4 Electrode Configuration, Distance, Location. 5.5 EMG Front--End Amplifiers. 5.6 EMG Filters: Specifications. 5.7 Sampling and A/D Conversion. 5.8 European Recommendations on Electrodes and Electrode Locations. References. 6 SINGLE--CHANNEL TECHNIQUES FOR INFORMATION EXTRACTION FROM THE SURFACE EMG SIGNAL (E. A. Clancy, D. Farina, G. Filligoi). 6.1 Introduction. 6.2 Spectral Estimation of Deterministic Signals and Stochastic Processes. 6.3 Basic Surface EMG Signal Models. 6.4 Surface EMG Amplitude Estimation. 6.5 Extraction of Information in Frequency Domain from Surface EMG Signals. 6.6 Joint Analysis of EMG Spectrum and Amplitude (JASA). 6.7 Recurrence Quantification Analysis of Surface EMG Signals. 6.8 Conclusions. References. 7 MULTI--CHANNEL TECHNIQUES FOR INFORMATION EXTRACTION FROM THE SURFACE EMG (D. Farina, R. Merletti, C. Disselhorst--Klug). 7.1 Introduction. 7.2 Spatial Filtering. 7.3 Spatial Sampling. 7.4 Estimation of Muscle--Fiber Conduction Velocity. 7.5 Conclusions. References. 8 EMG MODELING AND SIMULATION (D. F. Stegeman, R. Merletti, H. J. Hermens). 8.1 Introduction. 8.2 Phenomenological Models of EMG. 8.3 Elements of Structure--Based SEMG Models. 8.4 Basic Assumptions. 8.5 Elementary Sources of Bioelectric Muscle Activity. 8.6 Fiber Membrane Activity Profiles, Their Generation, Propagation, and Extinction. 8.7 Structure of the Motor Unit. 8.8 Volume Conduction. 8.9 Modeling EMG Detection Systems. 8.10 Modeling Motor Unit Recruitment and Firing Behavior. 8.11 Inverse Modeling. 8.12 Modeling of Muscle Fatigue. 8.13 Other Applications of Modeling. 8.14 Conclusions. References. 9 MYOELECTRIC MANIFESTATIONS OF MUSCLE FATIGUE (R. Merletti, A. Rainoldi, D. Farina). 9.1 Introduction. 9.2 Definitions and Sites of Neuromuscular Fatigue. 9.3 Assessment of Muscle Fatigue. 9.4 How Fatigue Is Reflected in Surface EMG Variables. 9.5 Myoelectric Manifestations of Muscle Fatigue in Isometric Voluntary Contractions. 9.6 Fiber Typing and Myoelectric Manifestations of Muscle Fatigue. 9.7 Factors Affecting Surface EMG Variable. 9.8 Repeatability of Estimates of EMG Variables and Fatigue Indexes. 9.9 Conclusions. References. 10 ADVANCED SIGNAL PROCESSING TECHNIQUES (D. Zazula, S. Karlsson, C. Doncarli). 10.1 Introduction. 10.2 Theoretical Background. 10.3 Decomposition of EMG Signals. 10.4 Applications to Monitoring Myoelectric Manifestations of Muscle Fatigue. 10.5 Conclusions. Acknowledgment. References. 11 SURFACE MECHANOMYOGRAM (C. Orizio). 11.1 The Mechanomyogram (MMG): General Aspects during Stimulated and Voluntary Contraction. 11.2 Detection Techniques and Sensors Comparison. 11.3 Comparison between Different Detectors. 11.4 Simulation. 11.5 MMG Versus Force: Joint and Adjunct Information Content. 11.6 MMG Versus EMG: Joint and Adjunct Information Content. 11.7 Area of Application. References. 12 SURFACE EMG APPLICATIONS IN NEUROLOGY (M. J. Zwarts, D. F. Stegeman, J. G. van Dijk). 12.1 Introduction. 12.2 Central Nervous System Disorders and SEMG. 12.3 Compound Muscle Action Potential and Motor Nerve Conduction. 12.4 CMAP Generation. 12.5 Clinical Applications. 12.6 Pathological Fatigue. 12.7 New Avenues: High--Density Multichannel Recording. 12.8 Conclusion. References. 13 APPLICATIONS IN ERGONOMICS (G. M. Hagg, B. Melin, R. Kadefors). 13.1 Historic Perspective. 13.2 Basic Workload Concepts in Ergonomics. 13.3 Basic Surface EMG Signal Processing. 13.4 Load Estimation and SEMG Normalization and Calibration. 13.5 Amplitude Data Reduction over Time. 13.6 Electromyographic Signal Alterations Indicating Muscle Fatigue in Ergonomics. 13.7 SEMG Biofeedback in Ergonomics. 13.8 Surface EMG and Musculoskeletal Disorders. 13.9 Psychological Effects on EMG. References. 14 APPLICATIONS IN EXERCISE PHYSIOLOGY (F. Felici). 14.1 Introduction. 14.2 A Few "Tips and Tricks". 14.3 Time and Frequency Domain Analysis of sEMG: What Are We Looking For? 14.4 Application of sEMG to the Study of Exercise. 14.5 Strength and Power Training. 14.6 Muscle Damage Studied by Means of sEMG. References. 15 APPLICATIONS IN MOVEMENT AND GAIT ANALYSIS (C. Frigo, R. Shiavi). 15.1 Relevance of Electromyography in Kinesiology. 15.2 Typical Acquisition Settings. 15.3 Study of Motor Control Strategies. 15.4 Investigation on the Mechanical Effect of Muscle Contraction. 15.5 Gait Analysis. 15.6 Identification of Pathophysiologic Factors. 15.7 Workload Assessment in Occupational Biomechanics. 15.8 Biofeedback. 15.9 The Linear Envelope. 15.10 Information Enhancement through Multifactorial Analysis. References. 16 APPLICATIONS IN REHABILITATION MEDICINE AND RELATED FIELDS (A. Rainoldi, R. Casale, P. Hodges, G. Jull). 16.1 Introduction. 16.2 Electromyography as a Tool in Back and Neck Pain. 16.3 EMG of the Pelvic Floor: A New Challenge in Neurological Rehabilitation. 16.4 Age--Related Effects on EMG Assessment of Muscle Physiology. 16.5 Surface EMG and Hypobaric Hipoxia. 16.6 Microgravity Effects on Neuromuscular System. References. 17 BIOFEEDBACK APPLICATIONS (J. R. Cram). 17.1 Introduction. 17.2 Biofeedback Application to Impairment Syndromes. 17.3 SEMG Biofeedback Techniques. 17.4 Summary. References. 18 CONTROL OF POWERED UPPER LIMB PROSTHESES (P. A. Parker, K. B. Englehart, B. S. Hudgins). 18.1 Introduction. 18.2 Myoelectric Signal as a Control Input. 18.3 Conventional Myoelectric Control. 18.4 Emerging MEC Strategies. 18.5 Summary. References. Index.
1,078 citations
TL;DR: Results indicate that the variability of the instantaneous median frequency is related to the repeatability of the biomechanics of the exercise, and a novel approach is proposed for calculating spectral parameters from the surface myoelectric signal during cyclic dynamic contractions.
Abstract: The time-dependent shift in the spectral content of the surface myoelectric signal to lower frequencies has proven to be a useful tool for assessing localized muscle fatigue. Unfortunately, the technique has been restricted to constant-force, isometric contractions because of limitations in the processing methods used to obtain spectral estimates. A novel approach is proposed for calculating spectral parameters from the surface myoelectric signal during cyclic dynamic contractions. The procedure was developed using Cohen class time-frequency transforms to define the instantaneous median and mean frequency during cyclic dynamic contractions. Changes in muscle length, force, and electrode position contribute to the nonstationarity of the surface myoelectric signal. These factors, unrelated to localized fatigue, can be constrained and isolated for cyclic dynamic contractions, where they are assumed to be constant for identical phases of each cycle. Estimation errors for the instantaneous median and mean frequency are calculated from synthesized signals. It is shown that the instantaneous median frequency is affected by an error slightly lower than that related to the instantaneous mean frequency. In addition, the authors present a sample application to surface myoelectric signals recorded from the first dorsal interosseous muscle during repetitive abduction/adduction of the index finger against resistance. Results indicate that the variability of the instantaneous median frequency is related to the repeatability of the biomechanics of the exercise.
272 citations
"Analysis of Muscle's Electrical Act..." refers background in this paper
...The major function of the muscle is force production [1]....
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TL;DR: The reliability of the psychological and clinical neurophysiological assessment techniques available today allows a multidisciplinary approach to fatigue in neurological patients, which may contribute to the elucidation of the pathophysiological mechanisms of chronic fatigue, with the ultimate goal to develop tailored treatments for fatigue in Neurological patients.
Abstract: Fatigue is a multidimensional concept covering both physiological and psychological aspects. Chronic fatigue is a typical symptom of diseases such as cancer, multiple sclerosis (MS), Parkinson's disease (PD) and cerebrovascular disorders but is also presented by people in whom no defined somatic disease has been established. If certain criteria are met, chronic fatigue syndrome can be diagnosed. The 4-item Abbreviated Fatigue Questionnaire allows the extent of the experienced fatigue to be assessed with a high degree of reliability and validity. Physiological fatigue has been well defined and originates in both the peripheral and central nervous system. The condition can be assessed by combining force and surface-EMG measurements (including frequency analyses and muscle-fibre conduction estimations), twitch interpolation, magnetic stimulation of the motor cortex and analysis of changes in the readiness potential. Fatigue is a well-known phenomenon in both central and peripheral neurological disorders. Examples of the former conditions are multiple sclerosis, Parkinson's disease and stroke. Although it seems to be a universal symptom of many brain disorders, the unique characteristics of the concomitant fatigue also point to a specific relationship with several of these syndromes. As regards neuromuscular disorders, fatigue has been reported in patients with post-polio syndrome, myasthenia gravis, Guillain-Barre syndrome, facioscapulohumeral dystrophy, myotonic dystrophy and hereditary motor and sensory neuropathy type-I. More than 60% of all neuromuscular patients suffer from severe fatigue, a prevalence resembling that of patients with MS. Except for several rare myopathies with specific metabolic derangements leading to exercise-induced muscle fatigue, most studies have not identified a prominent peripheral cause for the fatigue in this population. In contrast, the central activation of the diseased neuromuscular system is generally found to be suboptimal. The reliability of the psychological and clinical neurophysiological assessment techniques available today allows a multidisciplinary approach to fatigue in neurological patients, which may contribute to the elucidation of the pathophysiological mechanisms of chronic fatigue, with the ultimate goal to develop tailored treatments for fatigue in neurological patients. The present report discusses the different manifestations of fatigue and the available tools to assess peripheral and central fatigue.
207 citations
"Analysis of Muscle's Electrical Act..." refers background in this paper
...These patients experience fatigue as a common symptom [2,3]....
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TL;DR: This book serves as an introduction to the field of biomedical engineering for students with undergraduate training in engineering, physics, and mathematics and serves as a background for students or practitioners whose prior training has not included this material.
Abstract: Biomedical Engineering Principles Arthur B. Ritter, Stanley Reisman, and Bozena B. Michniak, CRC Press, Taylor and Francis Group, 2005. ISBN: 0824796160, 680 pages, US$99.95. This book serves as an introduction to the field of biomedical engineering for students with undergraduate training in engineering, physics, and mathematics. This book can be used for senioror graduate-level classes at universities, for short courses, or as a general knowledge book for practicing engineers wanting to learn more about biomedical engineering. The classic description of biomedical engineering is that it is the application of engineering analysis to problems in medicine and life sciences. Biomedical engineering is not one discipline but several interacting disciplines that coexist within the same field. Since biomedical engineering cuts across several engineering disciplines, the book is divided into several sections. Each section is intended to be complementary and to serve as a background for students or practitioners whose prior training has not included this material. The first section addresses modeling, transport processes, cell physiology, and the cardiovascular system. Chapter 1 presents an overview and introduction to engineering analysis of physiological systems, the nature of biological data, and the role of models and simulation in experimental design. The chapter introduces the concepts of conservation of mass, compartments, convection, and diffusion. It also develops pharmacokinetic models for drug distribution. Chapter 2 covers cell physiology and transport, introducing the primary mechanisms by which water and solutes get into and out of cells. Chapter 3 covers the fundamentals of hemodynamics and the nature of blood and blood vessels as engineering materials. Chapter 4 is an introduction to the cardiovascular system, covering the cardiac conduction pathway, control of heart rate, EKG measurement and interpretation, cardiac output, cardiac work, and autonomic and local regulation of blood flow. The second section of the book reviews the concepts of biomedical signal processing. Chapter 5 discusses biomedical signals and how to represent them. The frequency content of a signal, periodic functions, and Fourier series are reviewed. Chapter 6 discusses signal acquisition and processing. Topics include sampling theorem, sampling rate, and aliasing. Chapter 7 discusses techniques for physiological signal processing. Topics include AR modeling, time-frequency analysis, short-time Fourier transforms, and quadratic distributions. Chapter 8 contains examples of physiological signal processing. The third section of the book contains an introduction to and practical applications of biomechanics. Chapter 9 is an introduction to the principles of biomechanics and discusses the analysis of human movement, human dynamics, measurements of muscle force, electrical stimulation of skeletal muscle, mechanical characteristics of biological materials, bone remodeling, body cycles, thermal regulation, and hypothermia. Chapter 10 contains a discussion of some practical applications of biomechanics, using the principles developed in Chapter 9. The fourth section of the book presents an introduction to tissue engineering. Chapter 11 covers the history of tissue engineering, materials, biological interactions, and the role of cells in tissue engineering. Applications of tissue engineering in skin equivalents, cardiovascular components, bone regrowth, muscle tissue, and nerve regeneration are also discussed. Chapter 12 looks at future developments in biomedical engineering. For university faculty, the book is an excellent textbook for a class. Each chapter contains numerous examples and contains many figures to enhance learning. References and suggestions for further reading are included at the end of each chapter. Problems are included at the end of chapters, where they will best test the student's knowledge. For practicing engineers without a biomedical engineering background, the book provides an excellent resource to explain the many intricacies of biomedical engineering and provides sufficient background material to make the subject understandable. —Richard C. Fries, PE, CRE Baxter Healthcare, Inc.
145 citations
"Analysis of Muscle's Electrical Act..." refers methods in this paper
...Traditionally, sEMG signals are analyzed using root mean square value (RMS), number zero crossing, median frequency and power [4, 5]....
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