Adaptive pulse segmentation and artifact detection in photoplethysmography for mobile applications

Author

Karlen, Walter ; Ansermino, J. Mark ; Dumont, Georges

Author_Institution

Depts. of Electr. & Comput. Eng. & Anesthesiology, Pharmacology & Therapeutics, Univ. of British Columbia (UBC), Vancouver, BC, Canada

fYear

2012

fDate

Aug. 28 2012-Sept. 1 2012

Firstpage

3131

Lastpage

3134

Abstract

Pulse oximeters non-invasively measure heart rate and oxygen saturation and have great potential for predicting critical illness. The photoplethysmogram (PPG) recorded from pulse oximetry is often corrupted with artifacts. These artifacts render the derived vital signs inaccurate.

Keywords

cardiology; feature extraction; medical signal processing; mobile handsets; oximetry; photoplethysmography; sensitivity; signal classification; time-domain analysis; Complex System Laboratory Benchmark dataset; adaptive pulse segmentation; adaptive thresholds; artifact detection; artifacts classification; incremental-merge segmentation algorithm; mobile applications; mobile phone pulse oximetry; morphological feature extraction; noninvasive heart rate measurement; oxygen saturation; photoplethysmography; real-time algorithm; sensitivity; time domain; vital signs; Algorithm design and analysis; Benchmark testing; Diseases; Heart rate; Mobile handsets; Prediction algorithms; Real-time systems; Algorithms; Heart Rate; Humans; Photoplethysmography;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE

Conference_Location

San Diego, CA

ISSN

1557-170X

Print_ISBN

978-1-4244-4119-8

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/EMBC.2012.6346628

Filename

6346628