LATIDIA · Robótica

Telecontrol basado en sEMG en tiempo real de un brazo robótico de asistencia utilizando una red neuronal convolucional 1D

arXiv: 2607.16310v2Tipo de anuncio: reemplazar Resumen: Las deficiencias motoras que afectan a la extremidad superior reducen significativamente la autonomía en las actividades diarias, en particular para las tareas que implican la manipulación de objetos.

La noticia

arXiv:2607.16310v2 Announce Type: replace Abstract: Motor impairments affecting the upper limb significantly reduce autonomy in daily activities, particularly for tasks involving object manipulation. Assistive robotic arms offer a promising solution, provided they can be controlled in an intuitive, reliable, and responsive manner. Among human--machine interface approaches, surface electromyography (sEMG) enables non-invasive access to muscle activity and thus to the user's motor intentions. This work proposes a real-time sEMG-based interface for the teleoperation of an assistive robotic arm. The system relies on four-channel sEMG acquisition, signal preprocessing, segmentation into sliding windows, and classification using a one-dimensional convolutional neural network (CNN). Several real-time strategies are investigated, including threshold-based onset detection, a two-stage