The article presents an algorithm for classifying the style of expression of violin playing based on IMU sensor, located on the violinists forearm. In the initial phase of research, the original set of measured signals was extended by transferring them to new coordinate systems. Additional motion dynamics signals, including estimated linear velocity, have been obtained using transformations typical for inertial navigation systems (INS). In the next part of the work, universal features as well as indicators typical for IMU signals were extracted. The final experiment concerned the comparative effectiveness of data classification, using features selected by mutual information and random forest algorithms. The evaluation of the performance of the proposed algorithm has been carried out using a publicly available database. The obtained level of classification accuracy exceeded 90%.
CITATION STYLE
Sawicki, A., & Zieliński, S. K. (2019). An algorithm for detecting the expressive musical gestures of violinists based on IMU signals. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11703 LNCS, pp. 59–71). Springer Verlag. https://doi.org/10.1007/978-3-030-28957-7_6
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