Measuring body composition in overweight individuals by dual energy x-ray absorptiometry

BACKGROUND: Dual energy x-ray absorptiometry (DXA) is widely used for body composition measurements in normal-weight and overweight/obese individuals. The limitations of bone densitometers have been frequently addressed. However, the possible errors in assessing body composition in overweight individuals due to incorrect positioning or limitations of DXA to accurately assess both bone mineral density and body composition in obese individuals have not received much attention and are the focus of this report. DISCUSSION: We discuss proper ways of measuring overweight individuals and point to some studies where that might not have been the case. It appears that currently, the most prudent approach to assess body composition of large individuals who cannot fit under the scanning area would be to estimate regional fat, namely the regions of thigh and/or abdomen. Additionally, using two-half body scans, although time consuming, may provide a relatively accurate measurement of total body fat, however, more studies using this technique are needed to validate it. SUMMARY: Researchers using bone densitometers for body composition measurements need to have an understanding of its limitations in overweight individuals and address them appropriately when interpreting their results. Studies on accuracy and precision in measurements of both bone and soft tissue composition in overweight individuals using available densitometers are needed

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

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

Evidence of Potential Averaging over the Finite Surface of a Bioelectric Surface Electrode

Most bioelectric signals are not only functions of time but also exhibit a variation in spatial distribution. Surface EMG signals are often "summarized" by a large electrode. The effect of such an electrode is interpreted as averaging the potential at the surface of the skin beneath the electrode. We first introduce an electrical equivalent model to delineate this principle of averaging. Next, in a realistic finite element model of EMG generation, two outcome variables are evaluated to assess the validity of the averaging principle. One is the change in voltage distribution in the volume conductor after electrode application. The other is the change in voltage across the high impedance double layer between tissue and electrode. We found that the principle of averaging is valid, once the impedance of the double layer is sufficiently high. The simulations also revealed that skin conductivity plays a role. High-density surface EMG provided experimental evidence consistent with the simulation results. A grid with 120 small electrodes was placed over the thenar muscles of the hand. Electrical nerve stimulation assured a reproducible compound muscle response. The averaged grid response was compared with a single electrode matching the surface of the high-density electrodes. The experimental results showed relatively small errors indicating that averaging of the surface potential by the electrode is a valid principle under most practical conditions. © 2009 Biomedical Engineering Society

Age-dependent motor unit remodelling in human limb muscles.

Voluntary control of skeletal muscle enables humans to interact with and manipulate the environment. Lower muscle mass, weakness and poor coordination are common complaints in older age and reduce physical capabilities. Attention has focused on ways of maintaining muscle size and strength by exercise, diet or hormone replacement. Without appropriate neural innervation, however, muscle cannot function. Emerging evidence points to a neural basis of muscle loss. Motor unit number estimates indicate that by age around 71 years, healthy older people have around 40 % fewer motor units. The surviving low- and moderate-threshold motor units recruited for moderate intensity contractions are enlarged by around 50 % and show increased fibre density, presumably due to collateral reinnervation of denervated fibres. Motor unit potentials show increased complexity and the stability of neuromuscular junction transmissions is decreased. The available evidence is limited by a lack of longitudinal studies, relatively small sample sizes, a tendency to examine the small peripheral muscles and relatively few investigations into the consequences of motor unit remodelling for muscle size and control of movements in older age. Loss of motor neurons and remodelling of surviving motor units constitutes the major change in ageing muscles and probably contributes to muscle loss and functional impairments. The deterioration and remodelling of motor units likely imposes constraints on the way in which the central nervous system controls movements