Abstract
The development of an optical fiber specklegram sensor for detection of force myography (FMG) signals produced by hand forces and movements is presented. The optomechanical transducers are attached to the user forearm, causing variations on speckle field intensities, which are processed and then correlated to particular hand postures. The results indicated the viability to identify changes on hand configurations and forces, in which the force retrieval can be implemented via artificial neural networks after a previous calibration. The fiber FMG sensor can be further applied on human-system interfaces, as well as integrated to glove-based sensors in order to provide a robust detection of hand movements and forces.
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