@article{
 title = {A motion-tolerant adaptive algorithm for wearable photoplethysmographic biosensors},
 type = {article},
 year = {2014},
 identifiers = {[object Object]},
 keywords = {Adaptive filter,motion artifact,noise reduction,photoplethysmography (PPG),pulse oximeter,wearable biosensor},
 pages = {670-681},
 volume = {18},
 id = {afce659d-9236-3276-90b3-2ec5ca233973},
 created = {2015-04-30T11:14:27.000Z},
 file_attached = {true},
 profile_id = {5e73f9af-1f10-3a70-a285-d3fbb699efe2},
 group_id = {e134fb94-8118-3ebe-b82d-bfbf0a8ae633},
 last_modified = {2015-04-30T12:22:13.000Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 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.},
 bibtype = {article},
 author = {Yousefi, Rasoul and Nourani, Mehrdad and Ostadabbas, Sarah and Panahi, Issa},
 journal = {IEEE Journal of Biomedical and Health Informatics},
 number = {2}
}

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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.","bibtype":"article","author":"Yousefi, Rasoul and Nourani, Mehrdad and Ostadabbas, Sarah and Panahi, Issa","journal":"IEEE Journal of Biomedical and Health Informatics","number":"2","bibtex":"@article{\n title = {A motion-tolerant adaptive algorithm for wearable photoplethysmographic biosensors},\n type = {article},\n year = {2014},\n identifiers = {[object Object]},\n keywords = {Adaptive filter,motion artifact,noise reduction,photoplethysmography (PPG),pulse oximeter,wearable biosensor},\n pages = {670-681},\n volume = {18},\n id = {afce659d-9236-3276-90b3-2ec5ca233973},\n created = {2015-04-30T11:14:27.000Z},\n file_attached = {true},\n profile_id = {5e73f9af-1f10-3a70-a285-d3fbb699efe2},\n group_id = {e134fb94-8118-3ebe-b82d-bfbf0a8ae633},\n last_modified = {2015-04-30T12:22:13.000Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n abstract = {The performance of portable and wearable biosensors is highly influenced by motion artifact. 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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.},\n bibtype = {article},\n author = {Yousefi, Rasoul and Nourani, Mehrdad and Ostadabbas, Sarah and Panahi, Issa},\n journal = {IEEE Journal of Biomedical and Health Informatics},\n number = {2}\n}","author_short":["Yousefi, R.","Nourani, M.","Ostadabbas, S.","Panahi, I."],"urls":{"Paper":"http://bibbase.org/service/mendeley/5e73f9af-1f10-3a70-a285-d3fbb699efe2/file/13379d37-4140-603d-1e12-2fb9bb11f8e8/2014-A_motion-tolerant_adaptive_algorithm_for_wearable_photoplethysmographic_biosensors.pdf.pdf"},"bibbaseid":"yousefi-nourani-ostadabbas-panahi-amotiontolerantadaptivealgorithmforwearablephotoplethysmographicbiosensors-2014","role":"author","keyword":["Adaptive filter","motion artifact","noise reduction","photoplethysmography (PPG)","pulse oximeter","wearable biosensor"],"downloads":0},"search_terms":["motion","tolerant","adaptive","algorithm","wearable","photoplethysmographic","biosensors","yousefi","nourani","ostadabbas","panahi"],"keywords":["adaptive filter","motion artifact","noise reduction","photoplethysmography (ppg)","pulse oximeter","wearable biosensor"],"authorIDs":[]}