During cyclic movements, the number of muscle activations and their timing are different from cycle to cycle. In a previous study, the CIMAP algorithm was proposed for grouping cycles showing similar EMG activation intervals, using dendrogram clustering. Even if the algorithm demonstrated good performances on a healthy population, the intra-cluster variability decreased when applied to datasets from pathological subjects. In this work we propose an optimized version of the CIMAP, comparing the performances of 8 different combinations of parameters used for the dendrogram construction. The cut-off point is also modified. The new and the original version of the algorithm are compared, in terms of intra-cluster variability, considering a population of 60 subjects, both healthy and pathological. The results show that the new CIMAP allows for obtaining clusters with lower variability with respect to the original version of the algorithm (p < 0.001).

Muscle contractions in cyclic movements: optimization of CIMAP algorithm / Rosati, Samanta; Castagneri, Cristina; Agostini, Valentina; Knaflitz, Marco; Balestra, Gabriella. - ELETTRONICO. - (2017), pp. 58-61. (Intervento presentato al convegno 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’17) tenutosi a Jeju, Korea nel July 11-15, 2017) [10.1109/EMBC.2017.8036762].

Muscle contractions in cyclic movements: optimization of CIMAP algorithm

ROSATI, SAMANTA;CASTAGNERI, CRISTINA;AGOSTINI, VALENTINA;KNAFLITZ, MARCO;BALESTRA, GABRIELLA
2017

Abstract

During cyclic movements, the number of muscle activations and their timing are different from cycle to cycle. In a previous study, the CIMAP algorithm was proposed for grouping cycles showing similar EMG activation intervals, using dendrogram clustering. Even if the algorithm demonstrated good performances on a healthy population, the intra-cluster variability decreased when applied to datasets from pathological subjects. In this work we propose an optimized version of the CIMAP, comparing the performances of 8 different combinations of parameters used for the dendrogram construction. The cut-off point is also modified. The new and the original version of the algorithm are compared, in terms of intra-cluster variability, considering a population of 60 subjects, both healthy and pathological. The results show that the new CIMAP allows for obtaining clusters with lower variability with respect to the original version of the algorithm (p < 0.001).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2676668
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