24th EANN 2023, 14 - 17 June 2023, León, Spain

Toward an Epidermal patch for voice prosthesis and diseases prediction by a fuzzy-neuro paradigm

Mario Malcangi, Giovanni Felisati, Alberto Saibene, Enrico Alfonsi, Mauro Fresia, Pasquale Cambiaghi


  Voice rehabilitation and diseases prediction is required today because neural degeneration or neurological injury alters the motor component of the speech system in the phonation area of the brain. A novel approach to voice rehabilitation consists in predicting the phonetic control by the EMG. In a previous work we demonstrated that the voice-production apparatus (tongue muscle) generates a specific EMG signal that identify the phoneme emitted. The inference paradigm is EFuNN (Evolving Fuzzy Neural Network) trained by the sampled EMG (Electro Myo Gram) signal at phonation-. time. A phoneme-to-speech non-invasive epidermal patch is to be designed with energy harvestimg and MEMS loudspeakers.  

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