Data Mining - Concepts and Techniques.

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

Theory of fuzzy integrals and its applications

Aging is associated with progressive loss of neuromuscular function that often leads to progressive disability and loss of independence. The term sarcopenia is now commonly used to describe the loss of skeletal muscle mass and strength that occurs in concert with biological aging. By the seventh and eighth decade of life, maximal voluntary contractile strength is decreased, on average, by 20-40% for both men and women in proximal and distal muscles. Although age-associated decreases in strength per unit muscle mass, or muscle quality, may play a role, the majority of strength loss can be accounted for by decreased muscle mass. Multiple factors lead to the development of sarcopenia and the associated impact on function. Loss of skeletal muscle fibers secondary to decreased numbers of motoneurons appears to be a major contributing influence, but other factors, including decreased physical activity, altered hormonal status, decreased total caloric and protein intake, inflammatory mediators, and factors leading to altered protein synthesis, must also be considered. The prevalence of sarcopenia, which may be as high as 30% for those ≥60 yr, will increase as the percentage of the very old continues to grow in our populations. The link between sarcopenia and disability among elderly men and women highlights the need for continued research into the development of the most effective interventions to prevent or at least partially reverse sarcopenia, including the role of resistance exercise and other novel pharmacological and nutritional interventions.

Invited review: Aging and sarcopenia.

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications.

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Techniques of EMG signal analysis: detection, processing, classification and applications

The rate of motor unit (MU) loss and its influence on the progression of sarcopenia is not well understood. Therefore, the main purpose of this study was to estimate and compare numbers of MUs in the tibialis anterior (TA) of young men ( approximately 25 years) and two groups of older men ( approximately 65 years and >/=80 years). Decomposition-enhanced spike-triggered averaging was used to collect surface and intramuscular electromyographic signals during isometric dorsiflexions at 25% of maximum voluntary contraction. The mean surface-MU potential size was divided into the maximum M wave to calculate the motor unit number estimate (MUNE). The MUNE was significantly reduced in the old (91) compared to young (150) men, and further reduced in the very old men (59). Despite the smaller MUNE at age 65, strength was not reduced until beyond 80 years. This suggests that age-related MU loss in the TA does not limit function until a critical threshold is reached.

Motor unit number estimates in the tibialis anterior muscle of young, old, and very old men.

A model of the motor unit action potential was developed to investigate the amplitude and frequency spectrum contributions of motor units, located at various depths within muscle, to the surface detected electromyographic (EMG) signal. A dipole representation of the transmembrane current in a three-dimensional muscle volume was used to estimate detected individual muscle fiber action potentials. The effects of anisotropic muscle conductance, innervation zone location, propagation velocity, fiber length, electrode area, and electrode configuration were included in the fiber action potential model. A motor unit action potential was assumed to be the sum of the individual muscle fiber action potentials. A computational procedure, based on the notion of isopotential layers, was developed which substantially reduced the calculation time required to estimate motor unit action potentials. The simulations indicated that: 1) only those motor units with muscle fibers located within 10---12 mm of the electrodes would contribute significant signal energy to the surface EMG, 2) variation in surface area of electrodes has little effect on the detection depth of motor unit action potentials, 3) increased interelectrode spacing moderately increases detection depth, and 4) the frequency content of action potentials decreases steeply with increased electrode-motor unit territory distance.

Detection of motor unit action potentials with surface electrodes: influence of electrode size and spacing

EMG signal decomposition: how can it be accomplished and used?

Decomposition and quantitative analysis of clinical electromyographic signals.

Introduction: Numerous methods for motor unit number estimation (MUNE) have been developed. The objective of this article is to summarize and compare the major methods and the available data regarding their reproducibility, validity, appli- cation, refinement, and utility. Methods: Using specified search criteria, a systematic review of the literature was performed. Reproducibility, normative data, application to specific diseases and conditions, technical refinements, and practicality were com- piled into a comprehensive database and analyzed. Results: The most commonly reported MUNE methods are the incremental, multiple-point stimulation, spike-triggered averaging, and statistical methods. All have established normative data sets and high reproducibility. MUNE provides quantitative assessments of motor neuron loss and has been applied successfully to the study of many clinical conditions, including amyotrophic lateral sclerosis and normal aging. Conclusions: MUNE is an important research technique in human subjects, providing important data regarding motor unit populations and motor unit loss over time. Muscle Nerve 50: 884-893, 2014

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Daniel W. Stashuk

Papers

Motor unit number estimates in the tibialis anterior muscle of young, old, and very old men.

Detection of motor unit action potentials with surface electrodes: influence of electrode size and spacing

EMG signal decomposition: how can it be accomplished and used?

Decomposition and quantitative analysis of clinical electromyographic signals.

Motor unit number estimation: a technology and literature review