Key result
A cyclic moving average filter based on signal similarity can eliminate motion artifacts without damaging the underlying photoplethysmogram signal.
A novel cyclic moving average filter effectively reduces motion artifacts in PPG signals, potentially improving the reliability of this diagnostic tool.
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May enhance PPG motion artifact removal in wearables; leaves open prospective clinical validation before adoption.
The photoplethysmogram (PPG) is an extremely useful medical diagnostic tool. However, PPG signals are highly susceptible to motion artifacts. In this paper, we propose a cyclic moving average filter that use similarity of Photoplethysmogram. This filtering method has the average value of each samples through separating the cycle of PPG signal. If there are some motion artifacts in continuous PPG signal, disjoin the signal based on cycle. And then, we made these signals to have same cycle by coordinating the number of sample. After arrange these cycles in 2 dimension, we put the average value of each samples from starting till now. So, we can eliminate the motion artifacts without damaged PPG signal.
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Junyeon Lee (2014) studied Motion artifacts in photoplethysmogram (PPG) signals. Cyclic moving average filter was evaluated on Motion artifact reduction. A cyclic moving average filter based on signal similarity can eliminate motion artifacts without damaging the underlying photoplethysmogram signal.
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