Requirement Analysis for Data-Driven Electroencephalography Seizure Monitoring Software to Enhance Quality and Decision Making in Digital Care Pathways for Epilepsy: A Feasibility Study from the Perspectives of Health Care Professionals.

Journal: JMIR human factors
Published Date:

Abstract

BACKGROUND: Abnormal brain activity is the source of epileptic seizures, which can present a variety of symptoms and influence patients' quality of life. Therefore, it is critical to track epileptic seizures, diagnose them, and provide potential therapies to manage people with epilepsy. Electroencephalography (EEG) is helpful in the diagnosis and classification of the seizure type, epilepsy, or epilepsy syndrome. Ictal EEG is rarely recorded, whereas interictal EEG is more often recorded, and the results can be abnormal or normal even in the case of epilepsy. The current digital care pathway for epilepsy (DCPE) lacks the integration of data-driven seizure detection, which could potentially enhance epilepsy treatment and management.

Authors

  • Pantea Keikhosrokiani
    School of Computer Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia.
  • Johanna Annunen
    Oulu University Hospital, University of Oulu, Oulu, Finland.
  • Jonna Komulainen-Ebrahim
    Oulu University Hospital, University of Oulu, Oulu, Finland.
  • Jukka Kortelainen
  • Mika Kallio
    Oulu University Hospital, University of Oulu, Oulu, Finland.
  • Päivi Vieira
    Oulu University Hospital, University of Oulu, Oulu, Finland.
  • Minna Isomursu
    Empirical Software Engineering in Software Systems and Services, Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland.
  • Johanna Uusimaa
    Oulu University Hospital, University of Oulu, Oulu, Finland.