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Purpose: Low back pain is a common issue among older adults, often attributed to weakened trunk muscles. Understanding the relationship between muscle mass and abdominal pressure can offer valuable insights for managing low back pain. This study aimed to explore the correlation of external abdominal pressure using a novel device with abdominal muscle mass and low back pain.

Methods: Elderly individuals over the age of sixty-five were recruited. External abdominal pressure was measured using RECORE, while muscle mass and thickness were assessed via impedance measurement and ultrasound. The presence of low back pain was also investigated.

Results: Correlation analysis showed a weak correlation between abdominal pressure and trunk muscle mass, as well as a weak correlation with the thickness of deep muscles, transversus abdominis ($r$ = 0.37) and internal oblique ($r$ = 0.33). Logistic analysis demonstrated a significant association between abdominal pressure and the presence of low back pain.

Conclusion: Our findings suggest that abdominal pressure is weakly linked to abdominal muscle size, particularly the deep muscles, and that measuring external abdominal pressure can provide insights into abdominal muscle function and low back pain in older adults.

Image guidance using preoperative magnetic resonance imaging (MRI) and intraoperative ultrasound (US) can improve the outcome of spine surgery. Employing a robotic US system (RUSS) allows the automated acquisition of large 3D US volumes, facilitating accurate registration. However, such registration remains challenging due to the cross-modality discrepancy. To address this issue, we present a pipeline that extracts spine pointclouds from MRI and 3D US to perform per-vertebra registration. Experiments showed a registration accuracy of 1.82 mm in terms of residual root mean square error and 7.02 mm in terms of Chamfer distance. The pipeline exhibits superior robustness to suboptimal initial conditions compared with the two baseline methods. It also demonstrated good time efficiency under real-time conditions, demonstrating the potential applicability in RUSS-guided spine surgeries.

Gas bubbles are the most potent naturally-occurring entities that influence the acoustic environment in liquids. Upon entrainment under breaking waves, waterfalls, or rainfall over water, each bubble undergoes small amplitude decaying pulsations with a natural frequency that varies approximately inversely with the bubble radius, giving rise to the "plink" of a dripping tap or the roar of a cataract. When they occur in their millions per cubic metre in the top few metres of the ocean, bubbles can dominate the underwater sound field. Similarly, when driven by an incident sound field, bubbles exhibit a strong pulsation resonance. Acoustic scatter by bubbles can confound sonar in the shallow waters which typify many modern maritime military operations. If they are driven by sound fields of sufficient amplitude, the bubble pulsations can become highly nonlinear. These nonlinearities might be exploited to enhance sonar, or to monitor the bubble population. Such oceanic monitoring is important, for example, because of the significant contribution made by bubbles to the greenhouse gas budget. In industry, bubble monitoring is required for sparging, electrochemical processes, the production of paints, pharamaceuticals and foodstuffs. At yet higher amplitudes of pulsation, gas compression within the collapsing bubble can generate temperatures of several thousand Kelvin whilst, in the liquid, shock waves and shear can produce erosion and bioeffects. Not only can these effects be exploited in industrial cleaning and manufacturing, and research into novel chemical processes, but we need to understand (and if possible control) their occurrence when biomedical ultrasound is passed through the body. This is because the potential of such bubble-related physical and chemical processes to damage tissue will be desireable in some circumstances (e.g. ultrasonic kidney stone therapy), and undesireable in others (e.g. foetal scanning). This paper describes this range of behaviour. Further information on these topics, including sound and video files, can be found at .

The properties of ultrasonic propagation velocity in water-based and kerosene-based magnetic fluids and an MR fluid are examined experimentally. The ultrasonic frequency used is 1 MHz and the measurement scheme is based on the pulse method. The external magnetic field intensity is varied from 0 mT to 550 mT and is swept at a constant rate dB/dt (sweep rate). The ultrasonic propagation velocity changes with applied magnetic field and hysteresis is observed. The properties of ultrasonic propagation seem to be highly influenced by the formation of chain-like clusters (in the magnetic fluids) and robust clusters (in the MR fluid).

A mole of Mercury was suitably treated by ultrasound in order to generate in it the same conditions of local Lorentz invariance violation that were generated in a sonicated cylindrical bar of AISI 304 steel and that are the cause of neutron emission during the sonication. After 3 min, part of the mercury turned into a solid material which turned out to contain isotopes having a different mass (higher and lower) with respect to the isotopes already present in the initial material (mercury). These transformations in the atomic weight without gamma production above the background are brought about during Deformed Space–Time reactions. We present the results of the analyses performed on samples taken from the transformation product. The analyses have been done in two groups, the first one using five different analytical techniques: ICP-OES, XRF, ESEM-EDS, ICP-MS, INAA. In the second group of analyses, we used only two techniques: INAA and ICP-MS. The second group of analyses confirmed the occurring of the transformations in mercury.

We propose a novel ultrasonic sensor structure composed of Cantilever arm structure slot dual-micro-ring resonators (DMRR). We present a theoretical analysis of transmission by using the coupled mode theory. The mode field distributions and sound pressure distributions of transmission spectrum are obtained from 3D simulations based on Comsol Multi-physics (COMSOL) method. Our ultrasonic sensor exhibits theoretical sensitivity as high as $1462.5\mathrm{\text{mV}}/\mathrm{\text{kPa}}$, which is 22 times higher than that of the single slot-based micro-ring ultrasonic sensor. Our ultrasonic sensor offers higher sensitivity and a larger detection frequency range than conventional piezoelectric-based ultrasound transducer. The results show that the sensing characteristics of our system can be optimized through changing the position and the angle of sound field. Our ultrasonic sensor is with an area of $25\mu \mathrm{\text{m}}\times 60\mu \mathrm{\text{m}}$, the $Q$-factor can be approximately $1.54\times 10^3$ with radius of $5\mu \mathrm{\text{m}}$. We detect an angular range of $-90^{\circ }$ to $90^{\circ }$ and a minimum distance of $0.01\mu \mathrm{\text{m}}$. Finally, we calculate the Cantilever arm structure slot DMRR array ultrasonic sensor’s optical performance. Our proposed design provides a promising candidate for a hydrophone.

Neural networks differ from traditional approaches to image processing in terms of their ability to adapt to regularities in image structure and to self-organize so as to implement directed transformations. Biomedical ultrasonic images are often degraded in quality by noise and other factors, making enhancement techniques particularly important. This paper describes use of back propagation and competitive learning for enhancement and segmentation of ultrasonic images of the eye. Of particular interest is the extension or these technique to segmentation of three-dimensional data sets, where simple thresholding and gradient operations are not entirely successful.

The design of a MEMS ultrasonic sensor has been presented that exploits the Single Bubble Sonoluminescence (SBSL) phenomenon to realize an energy transduction mechanism from acoustical to electrical domain. In the developed scheme, highly stable laser like short duration light pulses are emitted when ultrasound waves strike a thermally generated microbubble stabilized in a confined volume of 1% xenon-enriched water. The emitted light pulses are detected by an integrated profiled silicon type photodetector to generate ultrastable 100 picoseconds duration current pulses per acoustical cycle. The sensor exhibits energy amplification during the transduction process itself that is not achievable by conventional types of MEMS or non-MEMS acoustical sensors. The cylindrical sensor geometry is 650 μm in diameter and 300 μm in height and is designed to have a sensitivity of 5.56 mA/atm/cycle. The sensor can be used in applications where detection of high pressure ultrasound waves is necessary or as an ultrastable very short duration current pulse generator for use in tissue and nerve repair or microsurgery.

Ultrasound (US) imaging is the initial phase in the preliminary diagnosis for the treatment of kidney diseases, particularly to estimate kidney size, shape and position, to give information about kidney function, and to help in diagnosis of abnormalities like cysts, stones, junctional parenchyma and tumors which is shown in Figs. 7–9. This study proposes Grey Level Co-occurrence Matrix (GLCM)-based Probabilistic Principal Component Analysis (PPCA) and Artificial Neural Network (ANN) method for the classification of kidney images. Grey Wolf Optimization (GWO) is used to update the current positions of abnormal kidney images in the discrete searching space, thus getting the optimal feature subset for better classification purposes based on Feed Forward Neural Network (FFNN). The scanned image is pre-processed and the required features are extracted by GLCM, among those, some features are selected by PPCA. Feed Forward Back propagation Neural Network (FFBN) is used to classify the normalities and abnormalities in the part of kidney images. The proposed methodology is implemented in MATLAB platform and the analyzed result produces 98% accuracy using GWO-FFBN technique.

Ultrasound imaging is commonly used to diagnose internal anomalies. Imaging for abnormality detection is a challenging process in today’s world. Even though there is an advancement in technology, tele-radiographers face difficulty in the accurate diagnosis of abnormalities. In order to resolve this issue, tele-radiology has paved a new way for doctors around the world to access the Internet to share the radiological images from one location to another. But frequent online access is one of the bottleneck issues. In order to overcome this drawback, Computer Assisted Diagnosis (CAD) is preferred in this proposed study and it uses VIRTEX-6 FPGA to clearly identify abnormality in the platform and also manual control is minimized in this condition. The proposed algorithm includes five steps: pre-processing, segmentation, feature extraction, selection and classification. The classification is performed using the Iterative K-Nearest Neighbor (IKNN) classifier based on the selected features. Unlike popular KNN, the proposed IKNN algorithm performs the similarity measurement on selective neighbors for a number of times where the number of neighbors has been dynamically selected at each iteration. Also, at each iteration, the method would select a subset of features in a random way. For the features selected and with the neighbors selected, the method computes the similarity value of Hist-sim which is being measured according to the features selected from the histogram features where the method computes the Haralick similarity with the features selected from the Haralick features. Using the features selected, the method computes the value of cumulative class drive similarity (CCDS). At each iteration the class with maximum similarity is selected and finally, the class being selected for the most number of times is selected as a result of classification. This improves the performance of classification. While comparing with the existing algorithms such as Support Vector Machine (SVM) with the linear, Radial Basis Function (RBF) and polynomial kernels, greater accuracy is achieved via IKNN classification. The specificity is found to be 95, 80 and 75 for normal, cystic and stone kidneys.

Piezoelectric ultrasonic transducers typically employ composite structures to improve their transmission and reception sensitivities. The geometry of the composite is regular with one dominant length scale and, since these are resonant devices, this dictates the central operating frequency of the device. In order to construct a wide bandwidth device it would seem natural therefore to utilize resonators that span a range of length scales. In this article we consider such a device and build a theoretical model to predict its performance. A fractal medium is used as this contains a wide range of length scales and yields to a renormalization approach. The propagation of an ultrasonic wave in this heterogeneous medium is then analyzed and used to construct expressions for the electrical impedance, and the transmission and reception sensitivities of this device as a function of the driving frequency. The results presented show a marked increase in the reception sensitivity of the device.

To ensure the safe operation of many safety critical structures such as nuclear plants, aircraft and oil pipelines, non-destructive imaging is employed using piezoelectric ultrasonic transducers. These sensors typically operate at a single frequency due to the restrictions imposed on their resonant behavior by the use of a single length scale in the design. To allow these transducers to transmit and receive more complex signals it would seem logical to use a range of length scales in the design so that a wide range of resonating frequencies will result. In this paper, we derive a mathematical model to predict the dynamics of an ultrasound transducer that achieves this range of length scales by adopting a fractal architecture. In fact, the device is modeled as a graph where the nodes represent segments of the piezoelectric and polymer materials. The electrical and mechanical fields that are contained within this graph are then expressed in terms of a finite element basis. The structure of the resulting discretized equations yields to a renormalization methodology which is used to derive expressions for the non-dimensionalized electrical impedance and the transmission and reception sensitivities. A comparison with a standard design shows some benefits of these fractal designs.

Piezoelectric ultrasonic transducers have the ability to act both as a receiver and a transmitter of ultrasound. Standard designs have a regular structure and therefore operate effectively over narrow bandwidths due to their single length scale. Naturally occurring transducers benefit from a wide range of length scales giving rise to increased bandwidths. It is therefore of interest to investigate structures which incorporate a range of length scales, such as fractals. This paper applies an adaptation of the Green function renormalization method to analyze the propagation of an ultrasonic wave in a series of pre-fractal structures. The structure being investigated here is the Sierpinski carpet. Novel expressions for the non-dimensionalized electrical impedance and the transmission and reception sensitivities as a function of the operating frequency are presented. Comparisons of metrics between three new designs alongside the standard design (Euclidean structure) and the previously investigated Sierpinski gasket device are performed. The results indicate a significant improvement in the reception sensitivity of the device, and improved bandwidth in both the receiving and transmitting responses.

In this paper, FD formulations in cylindrical coordinates are used to model the field radiated, by a circular source, in fluid and solid media.

The stability of the used schemes is controlled by a proper choice of time and space steps. Absorbing boundary conditions are introduced to satisfy the assumption of a propagation in a half space medium. In order to minimize the CPU time, calculations are limited for regions disturbed by the propagating ultrasonic pulse then the calculus zone is incremented.

Some numerical results are presented to illustrate the effect of the medium nature, source vibration profiles and eventually the presence of targets in the acoustic field. A spatio-temporal description of the diffraction phenomena is given. The radiated field is interpreted in terms of plane and edge waves. For solid media, this interpretation allows the determination of the arrival times which are compared with those numerically predicted. Numerical results corresponding to fluid media are compared to those obtained by the Impulse Response Method. The good agreement obtained justifies the choice of the FDM for the modeling of the wave propagation problems.

This paper describes the relationship between the eigenfrequencies of CT scanned realistic human head model and the subjective detecting pitch, which is given by providing the bone-conducted ultrasound. Our goal is to develop the optimal bone-conducted ultrasonic hearing aid for profoundly hearing-impaired persons. An ascent of a speech intelligibility is the requirement of hearing aid. To improve it, the perception mechanism of the bone-conducted ultrasound must be clarified, but the conclusive agreement of it has not been reached yet, although many hypotheses were reported.

The authors feel an interest in the detecting pitch of bone-conducted ultrasound with no frequency-dependence and predict that the cochleae are related to the perception mechanism for bone-conducted ultrasound, since it has been verified that the auditory cortex responds to bone-conducted ultrasound by MEG study.

In this paper, waves propagating from the mastoid to both cochleae are numerically analyzed and the characteristics of transfer functions are estimated as a first step to clarifying the perception mechanism for detecting pitch of bone-conducted ultrasonic stimuli.

Whilst most people in developed societies would celebrate the route from innovation to impact, particularly in the context of engineering and biomedicine, it is not often acknowledged that the definitions of the start, mid-points and even end-points of that route vary between groups in society. Since that route requires funding, this variety of opinion leaves regions of the route vulnerable to underfunding, particularly in times of recession. This paper explores how this can lead to failure to foresee problems and underpin solutions on the 10–50 year timescale. Furthermore, policies designed to support the route from innovation to impact can have the opposite effect. The route is illustrated with examples from the author's research.

In this paper we treat the cancellous bone as is done in mixture theory, i.e. each point in the material has both a fluid and a solid phase co-existing there. Each phase is weighted by the volume fraction of material in the composite structure. It is seen that in such a material attenuation of amplitude as frequency increases occurs as is observed in laboratory experiments^33,34 and as was observed in the finite element homogenization approach used by Hackl, Ilic and Gilbert.

An acoustic wave equation for pressure accounting for viscoelastic attenuation is derived from viscoelastic equations of motion. It is assumed that the relaxation moduli are completely monotonic (CM). The acoustic equation differs significantly from the equations proposed by Szabo (1994) and in several other papers. Integral representations of dispersion and attenuation are derived. General properties and asymptotic behavior of attenuation and dispersion in the low and high-frequency range are studied. The results are compatible with experiments. The relation between the asymptotic properties of attenuation and wavefront singularities is examined. The theory is applied to some classes of viscoelastic models and to the quasi-linear attenuation reported in seismology.

Anomalous variations of abductor digiti minimi are commonly found at Guyon's canal but rarely cause ulnar nerve compression. We report such a case with particular emphasis on the effectiveness of ultrasound to detect and delineate anatomical structures in this region.

The ability to improve the technique for an accurate clinical diagnosis of the injury of interosseous membrane of the forearm (IOM) associated with forearm fractures and dislocations is important for its treatment and prognosis. Ultrasound examination of the IOM in 46 forearms from 18 normal volunteers, five patients with restricted forearm pronation and supination, and two preoperative cases was performed to determine the usefulness and reproductivity of this examination. The intact IOM was observed as a continuous, slightly convex anteriorly and hyperechoic structure between the radius and ulna with both transverse and longitudinal views. IOMs with histories of forearm injuries were distinguished by the findings, which demonstrated a loss of continuity and were seen as hypoechoic traces from the others. This study confirmed that it is possible to trace the entire IOM and to detect differences between intact and disrupted IOMs with transverse and longitudinal views.