A deep learning-based telemonitoring application to automatically assess oral diadochokinesis in patients with bulbar amyotrophic lateral sclerosis.

Journal: Computer methods and programs in biomedicine
PMID: 37832429

Abstract

BACKGROUND AND OBJECTIVES: Timely identification of dysarthria progression in patients with bulbar-onset amyotrophic lateral sclerosis (ALS) is relevant to have a comprehensive assessment of the disease evolution. To this goal literature recognized the utmost importance of the assessment of the number of syllables uttered by a subject during the oral diadochokinesis (DDK) test.

Authors

  • Lucia Migliorelli
  • Lorenzo Scoppolini Massini
    Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy; AIDAPT S.r.l., Ancona, Italy.
  • Michela Coccia
    Centro Clinico NeuroMuscular Omnicentre (NeMO), Fondazione Serena Onlus, Ancona, Italy.
  • Laura Villani
    Department of Neuroscience, Neurorehabilitation Clinic, Azienda Ospedaliero-Universitaria delle Marche, Ancona, Italy.
  • Emanuele Frontoni
  • Stefano Squartini
    Department of Information Engineering, Università Politecnica delle Marche, Via Brecce Bianche, 60131 Ancona, Italy.

Keywords

External Resources

Popular Topics
Recent Journals