Motion artifact removal from photoplethysmographic signals by combining temporally constrained independent component analysis and adaptive filter.

BACKGROUND: The calculation of arterial oxygen saturation (SpO2) relies heavily on the amplitude information of the high-quality photoplethysmographic (PPG) signals, which could be contaminated by motion artifacts (MA) during monitoring. METHODS: A new method combining temporally constrained independent component analysis (cICA) and adaptive filters is presented here to extract the clean PPG signals from the MA corrupted PPG signals with the amplitude information reserved. The underlying PPG signal could be extracted from the MA contaminated PPG signals automatically by using cICA algorithm. Then the amplitude information of the PPG signals could be recovered by using adaptive filters. RESULTS: Compared with conventional ICA algorithms, the proposed approach is permutation and scale ambiguity-free. Numerical examples with both synthetic datasets and real-world MA corrupted PPG signals demonstrate that the proposed method could remove the MA from MA contaminated PPG signals more effectively than the two existing FFT-LMS and moving average filter (MAF) methods. CONCLUSIONS: This paper presents a new method which combines the cICA algorithm and adaptive filter to extract the underlying PPG signals from the MA contaminated PPG signals with the amplitude information reserved. The new method could be used in the situations where one wants to extract the interested source automatically from the mixed observed signals with the amplitude information reserved. The results of study demonstrated the efficacy of this proposed method.

Quantitative analysis of lymphocytes morphology and motion in intravital microscopic images.

Studying the morphology and interior movement of lymphocytes in intravital microscopic images is essential to understanding and treating various biological processes and pathological situations. A method combing features of shape, deformation, and intracellular motion for quantitatively characterizing the dynamic behavior of a single lymphocyte is proposed in this paper. The method is tested on a set of image sequences of lymphocytes obtained from the peripheral blood of mice undergoing skin transplantation using a phase contrast microscope. Experimental results coincide with the clinical observation and pathological analysis, demonstrating that the extracted cell morphology and motion features can provide new insights into the relationship between the dynamic behavior of lymphocytes and the occurrence of graft rejection.