Effect of Respiration on the Characteristic Ratios of Oscillometric Pulse Amplitude Envelope in Blood Pressure Measurement

Systolic and diastolic blood pressures (BPs) are important physiological parameters for disease diagnosis. Systolic and diastolic characteristic ratios derived from oscillometric pulse waveform have been widely used to estimate automated non-invasive BPs in oscillometric BP measurement devices. The oscillometric pulse waveform is easily influenced by respiration, which may cause variability to the characteristic ratios and subsequently BP measurement. This study quantitatively investigated how respiration patterns (i.e., normal breathing and deep breathing) affect the systolic and diastolic characteristic ratios. The study was performed with clinical data collected from 39 healthy subjects, and each subject conducted BP measurements during normal and deep breathings. Analytical results showed that the systolic characteristic ratio increased significantly from 0.52 ± 0.13 under normal breathing to 0.58 ± 0.14under deep breathing (p < 0.05), and the diastolic characteristic ratio was not significantly affected from 0.75 ± 0.12 under normal breathing to 0.76 ± 0.13 under deep breathing (p = 0.48). In conclusion, deep breathing significantly affected the systolic characteristic ratio, suggesting that automated oscillometric BP device which is validated under resting condition should be strictly used for measurements under resting condition

How volatilities nonlocal in time affect the price dynamics in complex financial systems

What is the dominating mechanism of the price dynamics in financial systems is of great interest to scientists. The problem whether and how volatilities affect the price movement draws much attention. Although many efforts have been made, it remains challenging. Physicists usually apply the concepts and methods in statistical physics, such as temporal correlation functions, to study financial dynamics. However, the usual volatility-return correlation function, which is local in time, typically fluctuates around zero. Here we construct dynamic observables nonlocal in time to explore the volatility-return correlation, based on the empirical data of hundreds of individual stocks and 25 stock market indices in different countries. Strikingly, the correlation is discovered to be non-zero, with an amplitude of a few percent and a duration of over two weeks. This result provides compelling evidence that past volatilities nonlocal in time affect future returns. Further, we introduce an agent-based model with a novel mechanism, that is, the asymmetric trading preference in volatile and stable markets, to understand the microscopic origin of the volatility-return correlation nonlocal in time.Comment: 16 pages, 7 figure

Correntropy Maximization via ADMM - Application to Robust Hyperspectral Unmixing

In hyperspectral images, some spectral bands suffer from low signal-to-noise ratio due to noisy acquisition and atmospheric effects, thus requiring robust techniques for the unmixing problem. This paper presents a robust supervised spectral unmixing approach for hyperspectral images. The robustness is achieved by writing the unmixing problem as the maximization of the correntropy criterion subject to the most commonly used constraints. Two unmixing problems are derived: the first problem considers the fully-constrained unmixing, with both the non-negativity and sum-to-one constraints, while the second one deals with the non-negativity and the sparsity-promoting of the abundances. The corresponding optimization problems are solved efficiently using an alternating direction method of multipliers (ADMM) approach. Experiments on synthetic and real hyperspectral images validate the performance of the proposed algorithms for different scenarios, demonstrating that the correntropy-based unmixing is robust to outlier bands.Comment: 23 page

Understanding low-pass-filtered Mandarin sentences: Effects of fundamental frequency contour and single-channel noise suppression

The present work assessed the effects of flattening the fundamental frequency (F0) contour and processing by single-channel noise suppression on the intelligibility of low-pass (LP)-filtered (LPF) sentences. The original F0 contour was replaced by an average flat F0 contour or treated by single-channel noise suppression, followed by application of LP filtering to Mandarin sentences. Processed stimuli were presented to normal-hearing listeners to recognize. Flattening the F0 contour significantly affected the understanding of LPF sentences. Noise suppression by existing single-channel algorithms did not improve the intelligibility of LPF sentences

Effects of noise suppression and envelope dynamic range compression on the intelligibility of vocoded sentences for a tonal language

Vocoder simulation studies have suggested that the carrier signal type employed affects the intelligibility of vocoded speech. The present work further assessed how carrier signal type interacts with additional signal processing, namely, single-channel noise suppression and envelope dynamic range compression, in determining the intelligibility of vocoder simulations. In Experiment 1, Mandarin sentences that had been corrupted by speech spectrum-shaped noise (SSN) or two-talker babble (2TB) were processed by one of four single-channel noise-suppression algorithms before undergoing tone-vocoded (TV) or noise-vocoded (NV) processing. In Experiment 2, dynamic ranges of multiband envelope waveforms were compressed by scaling of the mean-removed envelope waveforms with a compression factor before undergoing TV or NV processing. TV Mandarin sentences yielded higher intelligibility scores with normal-hearing (NH) listeners than did noise-vocoded sentences. The intelligibility advantage of noise-suppressed vocoded speech depended on the masker type (SSN vs 2TB). NV speech was more negatively influenced by envelope dynamic range compression than was TV speech. These findings suggest that an interactional effect exists between the carrier signal type employed in the vocoding process and envelope distortion caused by signal processing