Abstract
Despite multiple advances with myoelectric control, currently there is still an important need to develop more effective methods for controlling prosthesis and exoskeletons in a natural way. This work describes the design and development of a research tool for the design, development and evaluation of algorithms of myoelectric control which base on intention detection from neuromuscular activation patterns. This platform provides integrated hardware and software tools for real-time acquisition, preprocessing, visualization, storage and analysis of biological signals. It is composed of a bio-instrumentation system controlled by a real-time software created in Simulink and executed on the xPC-target platform and, a Java based software application that allows to manage the acquisition and storage processes by a system operator. System evaluation was performed by the comparison with reference signals provided by a function generator and, as an example of the application of the developed acquisition platform, it was carried out a set of experiments to decode movements at the upper-limb level.
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Acknowledgement
This work was supported by the Vice-rectory of Research of Universidad Antonio Nariño under project 2015227.
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Ruiz-Olaya, A.F., Díaz, G.M., López-Delis, A. (2018). A Real-Time Research Platform for Intent Pattern Recognition: Implementation, Validation and Application. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2018. Lecture Notes in Computer Science(), vol 10814. Springer, Cham. https://doi.org/10.1007/978-3-319-78759-6_11
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DOI: https://doi.org/10.1007/978-3-319-78759-6_11
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