Electrophysiological signal analysis and visualization using Cloudwave for epilepsy clinical research

Stud Health Technol Inform. 2013:192:817-21.

Abstract

Epilepsy is the most common serious neurological disorder affecting 50-60 million persons worldwide. Electrophysiological data recordings, such as electroencephalogram (EEG), are the gold standard for diagnosis and pre-surgical evaluation in epilepsy patients. The increasing trend towards multi-center clinical studies require signal visualization and analysis tools to support real time interaction with signal data in a collaborative environment, which cannot be supported by traditional desktop-based standalone applications. As part of the Prevention and Risk Identification of SUDEP Mortality (PRISM) project, we have developed a Web-based electrophysiology data visualization and analysis platform called Cloudwave using highly scalable open source cloud computing infrastructure. Cloudwave is integrated with the PRISM patient cohort identification tool called MEDCIS (Multi-modality Epilepsy Data Capture and Integration System). The Epilepsy and Seizure Ontology (EpSO) underpins both Cloudwave and MEDCIS to support query composition and result retrieval. Cloudwave is being used by clinicians and research staff at the University Hospital - Case Medical Center (UH-CMC) Epilepsy Monitoring Unit (EMU) and will be progressively deployed at four EMUs in the United States and the United Kingdomas part of the PRISM project.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Biomedical Research / methods*
  • Databases, Factual
  • Diagnosis, Computer-Assisted / methods*
  • Electroencephalography / methods*
  • Electroencephalography / statistics & numerical data
  • Epilepsy / diagnosis*
  • Epilepsy / physiopathology
  • Humans
  • Information Storage and Retrieval / methods*
  • Internet*
  • Software
  • User-Computer Interface*