Motion artifact reduction in photoplethysmography using independent component analysis

By Byung S. Kim, S. Yoo. IEEE Transactions on Biomedical Engineering, 2006

427 citations recorded by the source corpus.

Removing the motion artifacts from measured photoplethysmography (PPG) signals is one of the important issues to be tackled for the accurate measurement of arterial oxygen saturation during movement. In this paper, the motion artifacts were reduced by exploiting the quasi-periodicity of the PPG signal and the independence between the PPG and the motion artifact signals. The combination of independent component analysis and block interleaving with low-pass filtering can reduce the motion artifacts under the condition of general dual-wavelength measurement. Experiments with synthetic and real data were performed to demonstrate the efficacy of the proposed algorithm.

Subfields: Analytical Chemistry, Biomedical Engineering, Cardiology and Cardiovascular Medicine

View Paper: https://www.semanticscholar.org/paper/2fc950ce3b8f532a287dfa34f9f54dd742dd71a7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Zhouyue Pi
2. Zhilin Zhang
3. Axel Schäfer
4. Benyuan Liu
5. J. Vagedes

In Biomedical Engineering

1. Zhilin Zhang
2. Zhouyue Pi
3. Axel Schäfer
4. Benyuan Liu
5. J. Vagedes
6. Nitish V. Thakor
7. Yu Sun

In Cardiology and Cardiovascular Medicine

1. Zhilin Zhang
2. Zhouyue Pi
3. Axel Schäfer
4. Benyuan Liu
5. J. Vagedes
6. Nitish V. Thakor
7. Yu Sun

Citations in the corpus

• Photoplethysmography-Based Heart Rate Monitoring in Physical Activities via Joint Sparse Spectrum Reconstruction (2015, methodology): “So far, many noise-reduction techniques have been proposed, such as independent component analysis [6], adaptive noise”
• How accurate is pulse rate variability as an estimate of heart rate variability? A review on studies comparing photoplethysmographic technology with an electrocardiogram. (2013, methodology): “by describing them as linear factors modulating the coupling of light [78] or by combining the inherently quasi-periodic method and independent component analysis [79].”
• A Novel Approach for Motion Artifact Reduction in PPG Signals Based on AS-LMS Adaptive Filter (2012, positive): “3) ICA method: ICA is a quite-powerful signal processing technique [17], which expresses a set of random variables as linear combination of statistically independent component variables.”
• Wearable Photoplethysmographic Sensors—Past and Present (2014, background): “In addition, by exploiting the independence between PPG and motion artifacts, Kim and Yoo proposed that the combination of ICA and block interleaving with a low-pass filter can reduce the motion artifacts under the conditions used in general dual-wavelength measurements [72].”
• TROIKA: A General Framework for Heart Rate Monitoring Using Wrist-Type Photoplethysmographic Signals During Intensive Physical Exercise (2014, methodology): “For example, Kim and Yoo [3] suggested to use a basic ICA algorithm and block interleaving to remove MA.”