title: Statistical approach for the detection of motion/noise artifacts in Photoplethysmogram.
abstract: Motion and noise artifacts (MNA) have been a serious obstacle in realizing the potential of Photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a statistical approach based on the computation of kurtosis and Shannon Entropy (SE) for the accurate detection of MNA in PPG data. The MNA detection algorithm was verified on multi-site PPG data collected from both laboratory and clinical settings. The accuracy of the fusion of kurtosis and SE metrics for the artifact detection was 99.0%, 94.8% and 93.3% in simultaneously recorded ear, finger and forehead PPGs obtained in a clinical setting, respectively. For laboratory PPG data recorded from a finger with contrived artifacts, the accuracy was 88.8%. It was identified that the measurements from the forehead PPG sensor contained the most artifacts followed by finger and ear. The proposed MNA algorithm can be implemented in real-time as the computation time was 0.14 seconds using Matlab®.
authors.affiliation: Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA. nselvaraj@wpi.edu
authors.forename: Nandakumar
authors.initials: N
authors.lastname: Selvaraj
authors.forename: Yitzhak
authors.initials: Y
authors.lastname: Mendelson
authors.forename: Kirk H
authors.initials: KH
authors.lastname: Shelley
authors.forename: David G
authors.initials: DG
authors.lastname: Silverman
authors.forename: Ki H
authors.initials: KH
authors.lastname: Chon
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D009068:Movement; D010100:Oxygen / Q000097:blood*; D017156:Photoplethysmography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D010100:Oxygen