Classification of Daily-Life Grasping Activities sEMG Fractal Dimension

Elmer Escandón, Christian Flores

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)


Applications in pattern recognition and feature extraction for hand tasks are widely applied in prosthesis design through superficial electromyographic signals (sEMG) characterization. Novel applications still require higher classification accuracies and inter-subject invariability. Moreover, as machine learning techniques are implemented in a prosthesis, higher interest is focused on the training data, considering real-life variables as muscle fatigue and continuous data collection. This paper presents the detection of three different grasping action groups using two electrodes positioned in the extensor and flexor digitorum from a benchmark database with acquired real-life signals. Higuchi’s Fractal Dimension feature extraction technique is applied to determine a feature vector as training input data. Consequently, the training algorithm with a Support Vector Machine (SVM) technique for two kernel functions: linear and radial. Results indicate accuracies of 97.2%, 92.2%, 89.7% for two, three, and four task grasping actions with a Radial Basis Function kernel, respectively.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 6th Brazilian Technology Symposium, BTSym 2020 - Emerging Trends and Challenges in Technology
EditoresYuzo Iano, Osamu Saotome, Guillermo Kemper, Ana Claudia Mendes de Seixas, Gabriel Gomes de Oliveira
EditorialSpringer Science and Business Media Deutschland GmbH
Número de páginas8
ISBN (versión impresa)9783030756796
EstadoPublicada - 2021
Evento6th Brazilian Technology Symposium, BTSym 2020 - Virtual, Online
Duración: 26 oct. 202028 oct. 2020

Serie de la publicación

NombreSmart Innovation, Systems and Technologies
ISSN (versión impresa)2190-3018
ISSN (versión digital)2190-3026


Conferencia6th Brazilian Technology Symposium, BTSym 2020
CiudadVirtual, Online


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