Biased instantaneous regional muscle activation maps: Embedded fuzzy topology and image feature analysis

Carlos De la Fuente, Alejandro Weinstein, Alejandro Neira, Oscar Valencia, Carlos Cruz-Montecinos, Rony Silvestre, Patricio A. Pincheira, Felipe Palma, Felipe P. Carpes*

*Autor correspondiente de este trabajo

Producción científica: Contribución a una revistaArtículorevisión exhaustiva


The instantaneous spatial representation of electrical propagation produced by muscle contraction may introduce bias in surface electromyographical (sEMG) activation maps. Here, we described the effect of instantaneous spatial representation (sEMG segmentation) on embedded fuzzy topological polyhedrons and image features extracted from sEMG activation maps. We analyzed 73,008 topographic sEMG activation maps from seven healthy participants (age 21.4 ± 1.5 years and body mass 74.5 ± 8.5 kg) who performed submaximal isometric plantar flexions with 64 surface electrodes placed over the medial gastrocnemius muscle. Window lengths of 50, 100, 150, 250, 500, and 1,000 ms and overlap of 0, 25, 50, 75, and 90% to change sEMG map generation were tested in a factorial design (grid search). The Shannon entropy and volume of global embedded tri-dimensional geometries (polyhedron projections), and the Shannon entropy, location of the center (LoC), and image moments of maps were analyzed. The polyhedron volume increased when the overlap was [removed]75%. Entropy decreased when the overlap was [removed]75% and when the window length was [removed]500 ms. The LoC in the x-axis, entropy, and the histogram moments of maps showed effects for overlap (p < 0.001), while the LoC in the y-axis and entropy showed effects for both overlap and window length (p < 0.001). In conclusion, the instantaneous sEMG maps are first affected by outer parameters of the overlap, followed by the length of the window. Thus, choosing the window length and overlap parameters can introduce bias in sEMG activation maps, resulting in distorted regional muscle activation.
Idioma originalInglés
Número de artículo934041
PublicaciónFrontiers in Bioengineering and Biotechnology
EstadoPublicada - 22 dic. 2022

Nota bibliográfica

Publisher Copyright:
Copyright © 2022 De la Fuente, Weinstein, Neira, Valencia, Cruz-Montecinos, Silvestre, Pincheira, Palma and Carpes.

Palabras clave

  • Activation analysis
  • Chemical activation
  • Geometry
  • Image analysis
  • Image segmentation
  • Topology


Profundice en los temas de investigación de 'Biased instantaneous regional muscle activation maps: Embedded fuzzy topology and image feature analysis'. En conjunto forman una huella única.

Citar esto