Evaluating Quality of Photoplethymographic Signal on Wearable Forehead Pulse Oximeter With Supervised Classification Approaches

• Published in: IEEE access Vol. 8; pp. 185121 - 185135
• Main Authors: Liu, Shing-Hong, Liu, Han-Chi, Chen, Wenxi, Tan, Tan-Hsu
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Classification; CNN; Forehead; Motion artifacts; Oximetry; Oxygen content; oxygen saturation ratio; photoplethysmography; Probes; Pulse measurements; Pulse oximeter; Pulse oximetry; Segments; Sensors; Signal quality; Support vector machines; SVM; Treadmills; Wearable technology
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3029842

Pulse oximeter is a common and important instrument in medical clinic, which uses the photoplethysmography to measure oxygen saturation ratio (SpO 2 ). However, the photoplethysmographic (PPG) signal is easily corrupted by the motion artifact when SpO 2 is measured in a dynamic scenario. Moreover, t...