UMass Chan Medical School Faculty Publications
Title
A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) Signals
UMMS Affiliation
Division of Cardiovascular Medicine, Department of Medicine
Publication Date
2018-10-16
Document Type
Article
Disciplines
Analytical, Diagnostic and Therapeutic Techniques and Equipment | Biomedical Engineering and Bioengineering | Cardiology | Health Information Technology | Medical Biotechnology
Abstract
Photoplethysmography (PPG) is a technique to detect blood volume changes in an optical way. Representative PPG applications are the measurements of oxygen saturation, heart rate, and respiratory rate. However, PPG signals are sensitive to motion and noise artifacts (MNAs) especially when they are obtained from smartphone cameras. Moreover, PPG signals are different among users and each individual's PPG signal has a unique characteristic. Hence, an effective MNA detection and reduction method for smartphone PPG signals, which adapts itself to each user in a personalized way, is highly demanded. Here, a concept of the probabilistic neural network (PNN) is introduced to be used with the proposed extracted parameters. The signal amplitude, standard deviation of peak to peak time intervals and amplitudes, along with the mean of moving standard deviation, signal slope changes, and the optimal autoregressive (AR) model order are proposed for effective MNA detection. Accordingly, the performance of the proposed personalized algorithm is compared with conventional MNA detection algorithms. As performance metrics, we considered accuracy, sensitivity, and specificity. The results show that the overall performance of the personalized MNA detection is enhanced compared to the generalized algorithm. The average values of the accuracy, sensitivity and specificity of the personalized one are 98.07%, 92.6%, and 99.78%, respectively, while these are 89.92%, 84.21%, and 93.63% for the general one.
Keywords
Personalization, Photoplethysmography, PPG, Motion Noise Artifacts, Signal Quality Index
DOI of Published Version
10.1109/ACCESS.2018.2875873
Source
Tabei F, Kumar R, Phan TN, McManus DD, Chong JW. A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) Signals. IEEE Access. 2018;6:60498-60512. doi: 10.1109/ACCESS.2018.2875873. Epub 2018 Oct 16. PMID: 31263653; PMCID: PMC6602087. Link to article on publisher's site
Related Resources
Journal/Book/Conference Title
IEEE access : practical innovations, open solutions
PubMed ID
31263653
Repository Citation
Tabei F, Kumar R, Phan TN, McManus DD, Chong JW. (2018). A Novel Personalized Motion and Noise Artifact (MNA) Detection Method for Smartphone Photoplethysmograph (PPG) Signals. UMass Chan Medical School Faculty Publications. https://doi.org/10.1109/ACCESS.2018.2875873. Retrieved from https://escholarship.umassmed.edu/faculty_pubs/1745