title: A motion-tolerant adaptive algorithm for wearable photoplethysmographic biosensors.
abstract: The performance of portable and wearable biosensors is highly influenced by motion artifact. In this paper, a novel real-time adaptive algorithm is proposed for accurate motion-tolerant extraction of heart rate (HR) and pulse oximeter oxygen saturation ( SpO2) from wearable photoplethysmographic (PPG) biosensors. The proposed algorithm removes motion artifact due to various sources including tissue effect and venous blood changes during body movements and provides noise-free PPG waveforms for further feature extraction. A two-stage normalized least mean square adaptive noise canceler is designed and validated using a novel synthetic reference signal at each stage. Evaluation of the proposed algorithm is done by Bland-Altman agreement and correlation analyses against reference HR from commercial ECG and SpO2 sensors during standing, walking, and running at different conditions for a single- and multisubject scenarios. Experimental results indicate high agreement and high correlation (more than 0.98 for HR and 0.7 for SpO2 extraction) between measurements by reference sensors and our algorithm.
authors.forename: Rasoul
authors.initials: R
authors.lastname: Yousefi
authors.forename: Mehrdad
authors.initials: M
authors.lastname: Nourani
authors.forename: Sarah
authors.initials: S
authors.lastname: Ostadabbas
authors.forename: Issa
authors.initials: I
authors.lastname: Panahi
mesh_terms: D000328:Adult; D000465:Algorithms; D004562:Electrocardiography; D006801:Humans; D008297:Male; D008875:Middle Aged; D009068:Movement / Q000502:physiology; D017156:Photoplethysmography / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult