title: [Study on motion artifact reduction based on periodic component analysis using ECG as a case].
abstract: Motion artifacts are a main interference source of ambulatory physiology signals. The interference in wearable detection systems is more serious because of using dry electrodes. On account of the instantaneity in motion artifacts and periodicity in physiological signal, we presented a new method based on periodic component analysis for motion artifact reduction. The single channel signal is transformed into multi-channel signal with multi resolution analysis, and then periodic component analysis can help us to separate the normal physiological signal from motion artifacts. A case study in electrocardiogram (ECG) demonstrates that periodic component analysis is better than the empirical mode decomposition and adaptive filtering methods. Periodic component analysis as a time domain method can discriminate the signal with frequency aliasing, and recover the ECG waveform feature corrupted. This method can be easily extended to other physiological signal processing.
authors.affiliation: School of Automation, Wuhan University of Technology, Wuhan 430070, China. xkarcher@126.com
authors.forename: Kui
authors.initials: K
authors.lastname: Xiang
authors.forename: Qiao
authors.initials: Q
authors.lastname: Luo
authors.forename: Jing
authors.initials: J
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D000553:Ambulatory Care / Q000379:methods; D016477:Artifacts; D015716:Electrocardiography, Ambulatory / Q000379:methods*; D006801:Humans; D008991:Monitoring, Physiologic / Q000379:methods; D025341:Principal Component Analysis / Q000379:methods*; D012815:Signal Processing, Computer-Assisted