Early Detection of Dysphagia Signs in Parkinson’s Disease: An Artificial Intelligence-Based Approach Using Non-Invasive Sensors

The present study evaluates the effectiveness of a non-invasive wearable sensor system, combining accelerometers, surface electromyography, and artificial intelligence, to objectively characterize swallowing in elderly individuals affected by Parkinson’s Disease, without clinically manifested dyspha...

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Egile Nagusiak:	Michele Antonio Gazzanti Pugliese di Cotrone, Nidà Farooq Akhtar, Martina Patera, Silvia Gallo, Umberto Mosca, Marco Ghislieri, Claudia Ferraris, Antonio Suppa, Carlo Alberto Artusi, Alessandro Zampogna, Gianluca Amprimo, Gabriele Imbalzano, Serena Cerfoglio, Veronica Cimolin, Luigi Borzì, Gabriella Olmo, Fernanda Irrera
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	MDPI AG 2025-11-01
Saila:	Sensors
Gaiak:	wearable sensors artificial intelligence surface electromyography swallowing features principal component analysis dysphagia signs
Sarrera elektronikoa:	https://www.mdpi.com/1424-8220/25/22/6834
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