WaveformECG is a web-based tool for managing and analyzing ECG data. Users can browse their files, and upload ECG data in GE MUSE XML Versions 7+, Philips ECG XML versions 1.03+, and WaveForm DataBase (WFDB) format. WaveformECG extracts and stores information from GE and Philips file headers, including analysis results. Digital ECG data is extracted and stored as a time-series. Users can select, view and scroll through individual digital ECG waveforms and lead signals, formatted to look like paper chart recordings. Points and time intervals can be annotated using ontology from the Bioportal1 ontology server. Annotations are then stored with waveforms. Users can select groups of ECGs for analysis. These ECGs are then passed to user-selected analysis algorithms. Analyses can be distributed across multiple CPUs to decrease processing time. Analysis results can be viewed as well as downloaded in csv format. A demo version of WaveformECG v3.0 is available here. Go to the Sign In page within Waveform to obtain an account. Waveform itself uses Globus to authenicate, so the Sign In page has a link to Globus for you to create an account. If you experience issues, contact Stephen Granite (email@example.com) for assistance. Contact Dr. Raimond Winslow (firstname.lastname@example.org) for additional details. Use of WaveformECG should be acknowledged as “Development of WaveformECG is supported by the NHLBI Cardiovascular Research Grid Project (R24HL085343)”.
#1Musen et al (2008) AMIA Annu Symp Proc. 2008; 2008: 76–80.
More details on the Waveform ECG tool can be found in the CVRG wiki at the links below:
- Deploying Waveform ECG locally: CVRG Waveform Development Environment Configuration
- Deploying an Amazon EC2 instance of Waveform ECG: CVRG Waveform EC2 Cloud Implementation