Neuromuscular changes with age: a simulation study

The neuromuscular system in the human body shows age-associated change from the third decade of life. For people aged 60-75 (the young-old population group), physiological changes are evident, but the effects of these changes such as unsteadiness and falls are far less apparent than in the elderly. Work to quantify muscular changes in the young-old is lacking. Present techniques are inaccurate or invasive - suitable only for small, isolated studies.

In this work, simulation of the surface electromyogram (sEMG) signal is proposed as a method for investigating age-related muscle degeneration. By adapting the model's parameters to reproduce experimental results, the characteristics of ageing muscles can be estimated.

A sEMG/force model capable of simulating signals from human muscles is presented. The model covers four stages of EMG generation; neuronal stimulating pulse, muscle fibre action potential, motor unit action potential and surface EMG simulation. When populated with accurate simulation parameters, it generates both sEMG and force signals that are shown to correlate closely with experimental data.

The model has been implemented and verified against experimental results from two different muscles of the human arm; the biceps brachii and the brachioradialis. Both the sEMG and force outputs are shown to match experimental data recorded from the contracting muscles of human subjects.

The verified model was utilised to study the way in which muscle composition alters with age. Two groups of subjects were studied. The younger group were aged 20-28 years old, while the older group were aged 60-68 years old. Both groups were asked to contract their biceps brachii isometrically at maximum effort while the sEMG and force signals were recorded. Signal features representing the amplitude and spectrum of the sEMG were then calculated.

The sEMG/force model developed for this work was simulated to generate signals representing the muscles of healthy, young adults. Parameter values were taken from distributions based on experimental studies.

The experimental work presented agrees with current literature which proposes that fast muscle fibre types reduce in number more rapidly with age than slow muscle fibres.

This work has shown that an appropriately designed and implemented sEMG/force model can be used to quantify muscular changes from the norm, such as those detected in ageing adults.