BackgroundThe 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.MethodsA 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.ResultsCompared 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.ConclusionsThis 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.

Abstract. Directional modulation (DM) can be achieved based on uniform linear arrays (ULAs)where the maximum spacing between adjacent antennas is half wavelength of the frequency of interest in order to avoid spatial aliasing. To exploit the additional degrees of freedom (DOFs) provided in the spatial domain, sparse antenna arrays can be employed for more effective DM. In this work, the spare array design problem in the context of DM is formulated from the viewpoint of compressive sensing (CS), so that it can be solved using standard convex optimisation toolboxes in the CS area. In detail, we need to find a common set of active antennas for all modulation symbols generating a response close to the desired one. The key to the solution is to realise that we have to employ the group sparsity concept, as a common antenna set cannot be guaranteed if we optimise antenna locations for each modulation symbol individually. Moreover, we have also considered two practical scenarios for our proposed design: robust design with model errors, and design with practical non-zero-sized antennas, and corresponding solutions are found by modifying the proposed standard solution.

No abstract

Many researchers have studied the various affective variables which influence the use of the target language. Willingness to communicate is often regarded to be main causes of the frequency of L2 use. At first, the concept and importance of willingness to communicate is illustrated. Next, the essay argues about the personality-based variables underlying willingness. Finally, the correlation of the personality-based variables will be illustrated. The purpose of this essay is to make a literature of willingness to communicate and provide a theoretical support on the further research on willingness to communicate.