LightWAVE: Waveform and Annotation Viewing and Editing in a Web Browser.

Area of Science:

• Biomedical Engineering
• Computational Biology
• Medical Informatics

Background:

• Physiologic waveform data, including electrocardiograms (ECGs), are crucial for medical research.
• Efficient tools for viewing, annotating, and managing these signals are essential for data analysis and collection.
• Existing software may lack flexibility or ease of use for interactive annotation tasks.

Purpose of the Study:

• To describe LightWAVE, a novel open-source software solution for visualizing and annotating physiologic waveforms.
• To highlight LightWAVE's capabilities for interactive creation and modification of annotations, facilitating research data collection.
• To present the software's modular architecture, enabling extensibility and customization.

Main Methods:

• LightWAVE employs a client-server architecture with a C-based CGI back end for data retrieval and a JavaScript-based web application front end.
• Data are accessed from PhysioNet's PhysioBank archives or similarly structured repositories.
• A Perl-based CGI application, 'scribe,' handles the recording of user annotations.

Main Results:

• LightWAVE provides an efficient, interactive platform for viewing ECGs and other physiologic signals.
• The software supports the creation and modification of event markers (annotations) essential for research.
• Its open-source nature and modular design allow for easy enhancement and integration.

Conclusions:

• LightWAVE offers a flexible and accessible solution for researchers working with physiologic waveform data.
• The software streamlines the process of building and refining research datasets through interactive annotation.
• Its web-based, no-installation design enhances accessibility across various devices and platforms.