Improving care for amyotrophic lateral sclerosis with artificial intelligence and affective computing.

Journal: Journal of the neurological sciences
PMID: 39615150

Abstract

BACKGROUND: Patients with ALS often face difficulties expressing emotions due to impairments in facial expression, speech, body language, and cognitive function. This study aimed to develop non-invasive AI tools to detect and quantify emotional responsiveness in ALS patients, providing objective insights. Improved understanding of emotional responses could enhance patient-provider communication, telemedicine effectiveness, and clinical trial outcome measures.

Authors

  • Marc Garbey
    Department of Surgery, George Washington University School of Medicine & Health Sciences, Washington, DC, USA; Care Constitution Corp, Houston, TX, USA; Laboratoire des Sciences de l'Ingénieur pour l'Environnement (LaSIE) UMR-CNRS 7356 University of La Rochelle, France. Electronic address: garbeymarc@gwu.edu.
  • Quentin Lesport
    Care Constitution Corp, Houston, TX, USA; Laboratoire des Sciences de l'Ingénieur pour l'Environnement (LaSIE) UMR-CNRS 7356 University of La Rochelle, France.
  • Gülşen Öztosun
    Department of Neurology & Rehabilitation Medicine, George Washington University School of Medicine & Health Sciences, Washington, DC, USA.
  • Veda Ghodasara
    Department of Psychiatry, George Washington University - School of Medicine & Health Sciences, Washington, DC, USA.
  • Henry J Kaminski
    Department of Neurology & Rehabilitation Medicine, George Washington University School of Medicine & Health Sciences, Washington, DC, USA.
  • Elham Bayat
    Department of Neurology & Rehabilitation Medicine, George Washington University School of Medicine & Health Sciences, Washington, DC, USA. Electronic address: ebayat@mfa.gwu.edu.

Keywords

External Resources

Popular Topics
Recent Journals