Since the review of periodic flow phenomena by Berger & Wille (1972) in this journal, over twenty years ago, there has been a surge of activity regarding bluff body wakes. Many of the questions regarding wake vortex dynamics from the earlier review have now been answered in the literature, and perhaps an essential key to our new understandings (and indeed to new questions) has been the recent focus, over the past eight years, on the three-dimensional aspects of nominally two-dimensional wake flows. New techniques in experiment, using laser-induced fluorescence and PIV (Particle-Image-Velocimetry), are vigorously being applied to wakes, but interestingly, several of the new discoveries have come from careful use of classical methods. There is no question that strides forward in understanding of the wake problem are being made possible by ongoing three- dimensional direct numerical simulations, as well as by the surprisingly successful use of analytical modeling in these flows, and by secondary stability analyses. These new developments, and the discoveries of several new phenomena in wakes, are presented in this review.

Vortex Dynamics in the Cylinder Wake

Results are reported from a highly accurate, global numerical stability analysis of the periodic wake of a circular cylinder for Reynolds numbers between 140 and 300 The analysis shows that the two-dimensional wake becomes (absolutely) linearly unstable to three-dimensional perturbations at a critical Reynolds number of 1885±10 The critical spanwise wavelength is 396 ± 002 diameters and the critical Floquet mode corresponds to a ‘Mode A’ instability At Reynolds number 259 the two-dimensional wake becomes linearly unstable to a second branch of modes with wavelength 0822 diameters at onset Stability spectra and corresponding neutral stability curves are presented for Reynolds numbers up to 300

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Three-dimensional Floquet stability analysis of the wake of a circular cylinder

A system for detecting non-verbal acoustic energy generated by a subject is provided. The system includes a sensor mountable on or in a body region of the subject, the sensor being capable of sensing the non-verbal acoustic energy; and a processing unit being capable of processing the non-verbal acoustic energy sensed by the sensor and deriving an activity related signature therefrom, thereby enabling identification of a specific activity associated with the non-verbal acoustic energy.

Systems and Methods for Monitoring and Modifying Behavior

Apparatus and methods are provided for use with a subject who is undergoing respiration. A motion sensor senses motion of a subject. A breathing pattern analysis unit analyzes components of the sensed motion that result from the subject's respiration. The breathing pattern analysis unit includes double-movement-respiration-cycle-pattern-identification functionality that designates respiration cycles as being double-movement-respiration-cycles (DMRC's) by determining that the cycles define two subcycles. Double-movement-respiration-cycle-event-identification functionality of the breathing pattern analysis unit identifies a DMRC event by detecting that the subject has undergone a plurality of DMRC's. An output is generated that is indicative of the subject having used accessory muscles in breathing, in response to identification of the double-movement-respiration-cycle event. Other embodiments are also described.

Monitoring, predicting and treating clinical episodes

random data analysis and measurement procedures is available in our digital library an online access to it is set as public so you can get it instantly. Our book servers spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the random data analysis and measurement procedures is universally compatible with any devices to read.

Random Data Analysis And Measurement Procedures

Cardiovascular disease is a major cause of death worldwide. New diagnostic tools are needed to provide early detection and intervention to reduce mortality and increase both the duration and quality of life for patients with heart disease. Seismocardiography (SCG) is a technique for noninvasive evaluation of cardiac activity. However, the complexity of SCG signals introduced challenges in SCG studies. Renewed interest in investigating the utility of SCG accelerated in recent years and benefited from new advances in low-cost lightweight sensors, and signal processing and machine learning methods. Recent studies demonstrated the potential clinical utility of SCG signals for the detection and monitoring of certain cardiovascular conditions. While some studies focused on investigating the genesis of SCG signals and their clinical applications, others focused on developing proper signal processing algorithms for noise reduction, and SCG signal feature extraction and classification. This paper reviews the recent advances in the field of SCG.

Recent Advances in Seismocardiography

An analytical solution is developed for the problem of surface wave generation on a linear viscoelastic half-space by a finite rigid circular disk located on the surface and oscillating normal to it. The solution is an incremental advancement of theoretical work reported in articles focused on seismology. Since the application of interest here is medical diagnostics, the solution is verified experimentally using a viscoelastic phantom with material properties comparable to biological soft tissue. Findings suggest that prior estimates in the literature of the shear viscosity in human soft tissue may not be accurate in the low audible frequency range. Measurement of wave motion on the skin surface caused by internal biological functions or external stimuli has been studied by a few researchers for rapid, nonintrusive diagnosis of a variety of specific medical ailments. It is hoped that the developments reported here will advance these techniques and also provide insight into related diagnostic methods, such as sonoelastic imaging and other methodologies that utilize disease-related variations in tissue shear elasticity or variations in density due to gaseous inclusions.

Excitation and propagation of surface waves on a viscoelastic half-space with application to medical diagnosis

Endotracheal tube (ETT) malpositioning into a mainstem bronchus or the esophagus may result in significant hypoxemia. Current methods to determine correct ETT position include auscultation, radiography, and bronchoscopy, although the current acceptable standard procedure for proper endotracheal (versus esophageal) intubation is detection of end-tidal carbon dioxide (ETco(2)) by capnography, capnometry, or colorimetric ETco(2) devices. Unfortunately, capnography may be unavailable or unreliable in nonhospital/emergency settings or in low cardiac output states, and it does not detect endobronchial intubation. The purpose of this study was to quantify and assess breath sound characteristics using electronic stethoscopes placed over each hemithorax and epigastrium to determine their ability to detect ETT malposition. We recorded breath sounds in 19 healthy, non-obese adults before general surgical procedures. After intubation of the trachea, the ETT was bronchoscopically positioned 3 cm above the carina, after which 3 breaths of 500 mL were given and breath sounds were recorded. A second ETT was placed in the esophagus and the same series of breaths and recordings were performed. Finally, the tracheal ETT was advanced into the right mainstem bronchus and breath sounds were recorded. Using computerized analysis, breath sounds were digitized and filtered to remove selected frequencies, and acoustic signals and energy ratios were obtained for all 3 positions. Total energy ratios using band-pass filtering of the acoustic signals accurately identified all esophageal and endobronchial intubation (P < 0.001). These preliminary results suggest that this technique, when incorporated into a 3-component, electronic stethoscope-type device, may be an accurate, portable mechanism to reliably detect ETT malposition in adults when ETco(2) may be unavailable or unreliable.

Identification of Endotracheal Tube Malpositions Using Computerized Analysis of Breath Sounds via Electronic Stethoscopes

A sensor for use with a biological entity includes a housing and an acoustic transducer disposed within the housing. The acoustic transducer is adapted to detect a biological sound impinging on a surface of the biological entity. The sensor may also include an electrode integral with the sensor. The electrode is adapted to detect an electric potential associated with the surface of the biological entity. A plurality of sensors can be held in a predetermined pattern on the surface of the biological entity using a flexible carrier that provides a plurality of sensor mounting locations.

Sensors and sensor assemblies for monitoring biological sounds and electric potentials

Accurate estimation of seismocardiographic (SCG) signal features can help successful signal characterization and classification in health and disease. This may lead to new methods for diagnosing and monitoring heart function. Time-frequency distributions (TFD) were often used to estimate the spectrotemporal signal features. In this study, the performance of different TFDs (e.g., short-time Fourier transform (STFT), polynomial chirplet transform (PCT), and continuous wavelet transform (CWT) with different mother functions) was assessed using simulated signals, and then utilized to analyze actual SCGs. The instantaneous frequency (IF) was determined from TFD and the error in estimating IF was calculated for simulated signals. Results suggested that the lowest IF error depended on the TFD and the test signal. STFT had lower error than CWT methods for most test signals. For a simulated SCG, Morlet CWT more accurately estimated IF than other CWTs, but Morlet did not provide noticeable advantages over STFT or PCT. PCT had the most consistently accurate IF estimations and appeared more suited for estimating IF of actual SCG signals. PCT analysis showed that actual SCGs from eight healthy subjects had multiple spectral peaks at 9.20 ± 0.48, 25.84 ± 0.77, 50.71 ± 1.83 Hz (mean ± SEM). These may prove useful features for SCG characterization and classification.

Hansen A. Mansy

Papers

Recent Advances in Seismocardiography

Excitation and propagation of surface waves on a viscoelastic half-space with application to medical diagnosis

Identification of Endotracheal Tube Malpositions Using Computerized Analysis of Breath Sounds via Electronic Stethoscopes

Sensors and sensor assemblies for monitoring biological sounds and electric potentials

Time-Frequency Distribution of Seismocardiographic Signals: A Comparative Study.