Motion Artifact Reduction In Photoplethysmography For Reliable Signal Selection

Photoplethysmography (PPG) is a non-invasive and economical technique to extract vital signs of the human body. Although it has been widely used in consumer and research grade wrist devices to track a user's physiology, the PPG signal is very sensitive to motion which can corrupt the signal...

Full description

Saved in:
Bibliographic Details
Published inarXiv.org
Main Authors Mao, Runyu, Mackenzie Tweardy, Wegerich, Stephan W, Goergen, Craig J, Wodicka, George R, Zhu, Fengqing
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 06.09.2021
Subjects
Activities of daily living
Heart rate
Reduction
Segments
Signal processing
Signal quality
Wrist
Online AccessGet full text

Cover

More Information
Summary:Photoplethysmography (PPG) is a non-invasive and economical technique to extract vital signs of the human body. Although it has been widely used in consumer and research grade wrist devices to track a user's physiology, the PPG signal is very sensitive to motion which can corrupt the signal's quality. Existing Motion Artifact (MA) reduction techniques have been developed and evaluated using either synthetic noisy signals or signals collected during high-intensity activities - both of which are difficult to generalize for real-life scenarios. Therefore, it is valuable to collect realistic PPG signals while performing Activities of Daily Living (ADL) to develop practical signal denoising and analysis methods. In this work, we propose an automatic pseudo clean PPG generation process for reliable PPG signal selection. For each noisy PPG segment, the corresponding pseudo clean PPG reduces the MAs and contains rich temporal details depicting cardiac features. Our experimental results show that 71% of the pseudo clean PPG collected from ADL can be considered as high quality segment where the derived MAE of heart rate and respiration rate are 1.46 BPM and 3.93 BrPM, respectively. Therefore, our proposed method can determine the reliability of the raw noisy PPG by considering quality of the corresponding pseudo clean PPG signal.
ISSN:2331-8422