CapnoBase: Signal database and tools to collect, share and annotate respiratory signals

CapnoBase: Signal database and tools to collect, share and annotate respiratory signals. Karlen, W., Turner, M., Cooke, E., Dumont, G., A., & Ansermino, J., M. In Annual Meeting of the Society for Technology in Anesthesia (STA), pages 25, 2010.

Website doi abstract bibtex

The development of reliable and robust algorithms for the processing of biomedical signals in the operating room requires a series of high resolution signals recorded under different and known conditions. For algorithm tuning and validation, large datasets containing annotated clinical scenarios are required. These scenarios can be difficult to obtain, especially in the case of rare respiratory events recorded during anesthesia (e.g. rising end-tidal carbon dioxide (EtCO2) associated with malignant hyperthermia or anaphylaxis). The collection and annotation of data is very time consuming. In addition the comparative performance of an algorithm can only be assessed using a benchmark dataset. There is currently no public benchmarking dataset for respiratory signal analysis available. CapnoBase is a collaborative research project designed to provide easy to use research tools and a database of annotated respiratory signals including a benchmark dataset.

@inproceedings{
 title = {CapnoBase: Signal database and tools to collect, share and annotate respiratory signals},
 type = {inproceedings},
 year = {2010},
 keywords = {Capnogram,capnobase,database,flow,pressure,respiratory},
 pages = {25},
 websites = {www.capnobase.org,http://capnobase.org/literature/},
 city = {West Palm Beach},
 id = {aedbe729-f18d-3d5f-89e3-c4d16c97287d},
 created = {2009-12-09T18:16:12.000Z},
 accessed = {2010-06-28},
 file_attached = {true},
 profile_id = {6d353feb-efe4-367e-84a2-0815eb9ca878},
 last_modified = {2022-09-04T18:12:23.428Z},
 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Karlen2010},
 notes = {Cited more than 80 times},
 folder_uuids = {0560f016-99a0-4947-b8d2-af51a6797449,f1f67efc-95a7-4f1a-b181-c3670c667a34,470e1c72-5ded-4e47-a429-6f5172e01dcb,b7673acf-cf74-4294-9d7a-ff63418309e7,4afa9380-d8d6-102e-ac9a-0024e85ead87,4c3d8d03-453f-4372-a5a6-d6fc6eb5ad4a,5014f70c-d8d6-102e-ac9a-0024e85ead87,0d3ec8ac-06e7-459a-9eec-b845649cdc31,4afa93ee-d8d6-102e-ac9a-0024e85ead87,4afa947a-d8d6-102e-ac9a-0024e85ead87},
 private_publication = {false},
 abstract = {The development of reliable and robust algorithms for the processing of biomedical signals in the operating room requires a series of high resolution signals recorded under different and known conditions. For algorithm tuning and validation, large datasets containing annotated clinical scenarios are required. These scenarios can be difficult to obtain, especially in the case of rare respiratory events recorded during anesthesia (e.g. rising end-tidal carbon dioxide (EtCO2) associated with malignant hyperthermia or anaphylaxis). The collection and annotation of data is very time consuming. In addition the comparative performance of an algorithm can only be assessed using a benchmark dataset. There is currently no public benchmarking dataset for respiratory signal analysis available. CapnoBase is a collaborative research project designed to provide easy to use research tools and a database of annotated respiratory signals including a benchmark dataset.},
 bibtype = {inproceedings},
 author = {Karlen, Walter and Turner, M and Cooke, Erin and Dumont, Guy A and Ansermino, J Mark},
 doi = {20.500.11850/87887},
 booktitle = {Annual Meeting of the Society for Technology in Anesthesia (STA)}
}

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