The influence of muscle noise on stiffness control
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2017-01-31
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en
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There is plenty of evidence that humans can control limb stiffness in response to different destabilizing force fields. Based on such experiments, an algorithm is developed to simulate arm stiffness control in humans. This algorithm is mainly applied for simulating stiffness control in force fields, where it was shown to be a representative way for human arm stiffness control. However, many daily life activities where this is required do not involve an external force field. Instead of instability arising from the force field, it is generated by the neuromuscular noise of the subject. Such a task will
be simulated, where I will mainly focus on the influence of different neuromuscular noise levels on the learning model. There is evidence that the simulations show more unstable trials with increasing neuromuscular noise, but it is still able to get in a stable condition by increasing muscle stiffness. At some point, the level of muscle noise is too high, resulting in a unstable system. This occurs because there is a trade-off between the amount of generated muscle force and noise, where stiffness control can not outweigh the amount of noise anymore.
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Faculteit der Sociale Wetenschappen