Changes In Waveform Shape Research Articles

Ultrasonic guided wave phased array based on reconstructed pulse-echo signals from phase information

Abstract Aiming at the inherent dispersion characteristics of ultrasonic guided waves and the problems of gratings and side lobes in classical total focusing method (TFM) imaging algorithms, this paper proposes a full focus imaging algorithm based on reconstruct signals from phase information. Utilizing the numerical solution of the dispersion curve in the wavenumber domain, the time domain signal of Lamb wave is propagated backward to revise the changes in waveform shape caused by dispersion, and the flight time of the pulse-echo is eliminated simultaneously. The phase of pulse-echo after dispersion compensation should be consistent with the excitation signal. And the pulse-echo should have a large waveform correlation coefficient with the excitation signal. For each imaging point, dispersion compensation for all collected signals is respectively implemented so that the sign coherence factor (SCF) and the waveform correlation factor (WCF) between pulse-echo and excitation waveform can be extracted to reconstruct scattering signals. The reconstructed signals only contain information about the pulse-echo from defect. TFM imaging of the reconstructed signal can effectively suppress the grating side lobes of classical TFM imaging and improve the signal-to-noise ratio (SNR).

Algorithmic assessment of shoulder function using smartphone video capture and machine learning

Tears within the stabilizing muscles of the shoulder, known as the rotator cuff (RC), are the most common cause of shoulder pain—often presenting in older patients and requiring expensive advanced imaging for diagnosis. Despite the high prevalence of RC tears within the elderly population, there is no previously published work examining shoulder kinematics using markerless motion capture in the context of shoulder injury. Here we show that a simple string pulling behavior task, where subjects pull a string using hand-over-hand motions, provides a reliable readout of shoulder mobility across animals and humans. We find that both mice and humans with RC tears exhibit decreased movement amplitude, prolonged movement time, and quantitative changes in waveform shape during string pulling task performance. In rodents, we further note the degradation of low dimensional, temporally coordinated movements after injury. Furthermore, a logistic regression model built on our biomarker ensemble succeeds in classifying human patients as having a RC tear with > 90% accuracy. Our results demonstrate how a combined framework bridging animal models, motion capture, convolutional neural networks, and algorithmic assessment of movement quality enables future research into the development of smartphone-based, at-home diagnostic tests for shoulder injury.

Waveform correlation factor (WCF) weighted TFM imaging for Lamb wave phased array

Aimed at improving the imaging performance of the classical total focusing method (TFM), which is an effective post-processing technique for Lamb wave phased array based damage imaging, a waveform correlation factor (WCF) weighted TFM imaging algorithm is proposed. In the proposed algorithm, besides the signal amplitude used in the classical TFM, the waveform correlation coefficients between any two waveforms after dispersion compensation are also utilized for damage imaging. Waveform correlation coefficients will be large if the wave packets are caused by the same imaging point, or they will be small due to the change in waveform shape arising from dispersion. For each imaging point, dispersion compensation for all collected signals is respectively implemented so that the scattering waveforms can be extracted. Then the waveform correlation coefficients between any two scattering waveforms are calculated and weighted on the corresponding amplitude used in the TFM. By comparing the imaging results of the proposed algorithm with that of the classical TFM algorithm, it is found that the proposed algorithm can significantly reduce the background noise and thus improve the imaging performance.

Synchrony Drives Motor Cortex Beta Bursting, Waveform Dynamics, and Phase-Amplitude Coupling in Parkinson's Disease.

Several lines of inquiry have separately identified beta oscillations, synchrony, waveform shape, and phase-amplitude coupling as important but sometimes inconsistent factors in the pathophysiology of Parkinson's disease. What has so far been lacking is a means by which these neurophysiological parameters are interrelated and how they relate to clinical symptomatology. To clarify the relationship among oscillatory power, bursting, synchrony, and phase-amplitude coupling, we recorded local field potentials/electrocorticography from hand motor and premotor cortical area in human subjects with c (N = 10) and Parkinson's disease (N = 22) during deep brain stimulator implantation surgery (14 females, 18 males). We show that motor cortical high beta oscillations in Parkinson's disease demonstrate increased burst durations relative to essential tremor patients. Notably, increased corticocortical synchrony between primary motor and premotor cortices precedes motor high beta bursts, suggesting a possible causal relationship between corticocortical synchrony and localized increases in beta power. We further show that high beta bursts are associated with significant changes in waveform shape and that beta-encoded phase-amplitude coupling is more evident during periods of high beta bursting. These findings reveal a deeper structure to the pathologic changes identified in the neurophysiology of Parkinson's disease, suggesting mechanisms by which the treatment may be enhanced using targeted network synchrony disruption approaches.SIGNIFICANCE STATEMENT Understanding Parkinson's disease pathophysiology is crucial for optimizing symptom management. Present inconsistencies in the literature may be explained by temporal transients in neural signals driven by transient fluctuations in network synchrony. Synchrony may also act as a unifying phenomenon for the pathophysiological observations reported in Parkinson's disease. Here, simultaneous recordings from motor cortices show that increases in network beta synchrony anticipate episodes of beta bursting. We furthermore identify beta bursting as being associated with changes in waveform shape and increases in phase-amplitude coupling. Our results identify network synchrony as a driver of various pathophysiological observations reported in the literature and account for inconsistencies in the literature by virtue of the temporally variable nature of the phenomenon.

Effects of waveform shape of pulsatile blood flow on hemodynamics in an artery bifurcation model

Pulsatile non-Newtonian fluid flow was simulated in an artery bifurcation model, with three different inlet flow waveform shapes and an identical inlet mean velocity steady-state condition, to quantify the impact of three different waveform shapes on hemodynamics such as flow patterns, wall shear stress, and oscillatory shear index during a cardiac cycle. It was found that the degree of flow separation is insensitive to changes in flow waveform shape. There is remarkable similarity in the position and magnitude of the maximum wall shear stress at peak systole and the maximum time-averaged wall shear stress for all examined cases. The oscillatory shear index distributions are broadly similar except that the local maximum oscillatory shear index increases proportionally with the pulsatility index of the waveform shape. The maximum oscillatory shear index values on the planar branch are within 8.7% in all examined cases, while these oscillatory shear index values on the nonplanar branch are identical due to the effects of its curvature. The negligible hemodynamic differences between simplified and characteristic waveform cases suggest that changes in waveform shape play a minimal role in the progression and development of atherosclerosis. Although the computed hemodynamics is almost consistent for the three different waveform shapes, several slight differences were observed.

Long-term stability of neural signals from microwire arrays implanted in common marmoset motor cortex and striatum

Current neuroprosthetics rely on stable, high quality recordings from chronically implanted microelectrode arrays (MEAs) in neural tissue. While chronic electrophysiological recordings and electrode failure modes have been reported from rodent and larger non-human primate (NHP) models, chronic recordings from the marmoset model have not been previously described. The common marmoset is a New World primate that is easier to breed and handle compared to larger NHPs and has a similarly organized brain, making it a potentially useful smaller NHP model for neuroscience studies. This study reports recording stability and signal quality of MEAs chronically implanted in behaving marmosets. Six adult male marmosets, trained for reaching tasks, were implanted with either a 16-channel tungsten microwire array (five animals) or a Pt-Ir floating MEA (one animal) in the hand-arm region of the primary motor cortex (M1) and another MEA in the striatum targeting the nucleus accumbens (NAcc). Signal stability and quality was quantified as a function of array yield (active electrodes that recorded action potentials), neuronal yield (isolated single units during a recording session), and signal-to-noise ratio (SNR). Out of 11 implanted MEAs, nine provided functional recordings for at least three months, with two arrays functional for 10 months. In general, implants had high yield, which remained stable for up to several months. However, mechanical failure attributed to MEA connector was the most common failure mode. In the longest implants, signal degradation occurred, which was characterized by gradual decline in array yield, reduced number of isolated single units, and changes in waveform shape of action potentials. This work demonstrates the feasibility of long-term recordings from MEAs implanted in cortical and deep brain structures in the marmoset model. The ability to chronically record cortical signals for neural prosthetics applications in the common marmoset extends the potential of this model in neural interface research.

Changes in the harmonic components of the flicker electroretinogram during light adaptation.

To evaluate the nature and extent of changes in the fundamental and harmonic components of the 31-Hz flicker electroretinogram (ERG) during light adaptation. Full-field ERGs were recorded from five visually normal subjects (ages 21-60 years). Following 30 min of dark adaptation, the subjects were exposed to a uniform adapting field of 50 cd/m(2). The field, which was presented for approximately 15 min, was intermittently modulated sinusoidally at 31.25 Hz. The ERG was recorded during the sinusoidal modulation, and Fourier analysis was used to obtain the amplitude and phase of the fundamental (F), second (2F), and third (3F) harmonic response components. F amplitude increased by almost a factor of two over approximately 6 min (time constant, τ, of 3.0 min). The 2F amplitude increased by a smaller amount, a factor of 1.4, and the time-course was approximately eight times faster than that of F (τ = 0.4 min). The 3F amplitude increased by a factor of 4.6, an increase that was larger than F or 2F, with a time-course that was between that of F and 2F (τ = 1.4 min). F phase was unaffected by light adaptation, whereas the 2F and 3F phases both increased by approximately 45° over similar time-courses (τ = 2.0 min). Light adaptation had different effects on the fundamental, second, and third harmonic components of the 31-Hz flicker ERG, which resulted in a change in waveform shape during light adaptation. The previously reported flicker ERG amplitude growth is driven primarily, but not entirely, by changes in the fundamental.

Analysis of multifocal electroretinograms from a population with type 1 diabetes using partial least squares reveals spatial and temporal distribution of changes to retinal function

Spatial-temporal partial least squares (ST-PLS) is a multivariate statistical analysis that has improved the analysis of modern imaging techniques. Multifocal electroretinograms (mfERGs) contain a large amount of data, and averaging and grouping have been used to reduce the amount of data to levels that can be handled using traditional statistical methods. In contrast, using all acquired data points, ST-PLS enables statistically rigorous testing of changes in waveform shape and in the distributed signal related to retinal function. We hypothesise that ST-PLS will improve analysis of the mfERG. Two mfERG protocols, a 103 hexagon clinical protocol and a slow-flash mfERG (sf-mfERG) protocol, were recorded from an adolescent population with type 1 diabetes and an age similar control population. The standard mfERGs were analysed using a template-fitting algorithm and the sf-mfERG using a signal-to-noise measure. The results of these traditional analysis techniques are compared with those of the ST-PLS analysis. Traditional analysis of the mfERG recordings revealed changes between groups for implicit time but not amplitude; however, the spatial location of these changes could not be identified. In contrast, ST-PLS detected significant changes between groups and displayed the spatial location of these changes on the retinal map and the temporal location within the mfERG waveforms. ST-PLS confirmed that changes to diabetic retinal function occur before the onset of clinical pathology. In addition, it revealed two distinct patterns of change depending on whether the multifocal paradigm was optimised to target outer retinal function (photoreceptors) or middle/inner retinal function (collector cells).

The influence of shallow atmospheric structure on tropospheric ducted infrasound from the Buncefield oil depot explosion

The vapour cloud explosion which destroyed the Buncefield oil depot, UK, on 11th December 2005, has proven to be a benchmark ground truth event for infrasonic studies. The regional infrasonic returns, those that propagated in the stratosphere and thermosphere, have been analysed in detail elsewhere. Here, we present the results of a study into infrasound ducted in the troposphere, recorded within 250 km of the source as air-to-ground coupled waves by a dense seismometer network. These tropospheric arrivals exhibit large waveform differences across the UK, both in amplitude and waveform shape. We numerically model these infrasound arrivals using a wave number integration method, incorporating a velocity profile derived from the UK Met Office numerical weather prediction model. Although some of the waveform variability is due to ground conditions at the recording site, we show that consistent changes in waveform shape across a 200 km swath of stations are correlated with a change in the wind vector in the lowermost 2 km of the atmosphere. Also, small amplitude, high-frequency precursors to the dominant acoustic signal, which might be misinterpreted as evidence of a small initial explosion, are shown to be consistent with the dispersion expected from a thin, shallow wind jet.

Stratigraphically significant attributes

Seismic attributes are derivatives of seismic data that are commonly used for two purposes, feature detection and to predict (usually quantitatively) physical properties of interest. Although there is a well-developed interest in using “physically significant” attributes (i.e., attributes thought to respond to or directly image changes in acoustic or elastic properties) to predict subsurface physical properties, in this article I make a case for identifying and using “stratigraphically significant” attributes. Stratigraphically significant attributes are seismic attributes that capture changes in waveform shape that are caused by changes in stratigraphy. As used here, the term “stratigraphy” refers to vertical and lateral changes in bed thickness and physical properties that are generally caused by changes in depositional processes. It should be recognized, however, that changes in physical properties caused by diagenesis can be important, especially in carbonates, and are here included in the definition ...

Some observations on fibrillations and positive sharp waves.

Electromyographic recordings of fibrillation potentials (FPs) and positive sharp waves (PSWs) demonstrate transformation of FP to PSW and vice versa, atypical firing patterns, changes in waveform shape and amplitude, and time-locked potentials. The etiology of the waveform characteristics of FP and PSW is discussed based on abnormal propagation in a small section of muscle fiber that is "damaged" by the needle. The results of simple computer simulations are described.

Interaction between spike waveform classification and temporal sequence detection

In vivo extracellular recordings have allowed researchers to study the response properties of neurons to behaviorally relevant stimuli. In this paper we use multiple tetrode recordings from the hippocampus of the freely behaving rat to show that the action potential amplitude of a given cell can vary in a systematic and activity dependent manner over behaviorally relevant time scales. Since the discrimination algorithms used by experimenters to isolate cells from extracellular recordings are based on differences in waveforms, we show how these systematic changes in waveform shape can lead to non-random errors in single cell isolation. We further demonstrate that these non-random errors can lead to apparent temporal ordering effects between neurons in the absence of any specific temporal relationship. A firm understanding of these naturally occurring physiological changes is therefore critical for the evaluation of higher order phenomena such as the temporally correlated firing of ensembles of neurons.

Classification of non-stationary neural signals

Although a number of methods have been proposed for classification of individual action potentials embedded in multi-unit activity, they have been challenged by non-stationarity. The waveform shapes of action potentials can change rapidly over time as a result of shifts in membrane conductances during extended burst firing sequences and more slowly over time due to electrode drift. These changes are typically non-Gaussian. We present an algorithm for waveform identification that makes no assumptions on the distribution of these shapes other than the change in waveform shape for a particular neuron should not be discontinuous. We apply this algorithm to the resolution of multi-unit neural signals recorded in the cat visual cortex and we compare this approach to a spike sorting method that is based on the Bayesian likelihood of a spike fitting a particular model (Lewicki, M. Bayesian modeling and classification of neural signals. Neural Comput 1994;6(5):1005–1030).

Visually evoked cortical potentials in awake cats during saccadic eye movements.

Visually evoked potentials (VEPs) measured under conditions of retinal image stabilization that minimized the influences of visual masking and smearing were averaged from electroencephalographic records measured from striate cortex of three cats. The amplitudes of the VEPs increased around saccade initiation. The grating-evoked potentials obtained at different times relative to the saccade exhibited changes in waveform shape that could be attributed to a saccade-evoked potential. The changes in the shape of the waveform were reasonably accounted for by the summation of the grating-evoked potential (produced when the cat did not make a saccade) and an appropriately timed saccade-evoked potential. The fundamental amplitudes of the residual potentials were computed and found to vary across the time course of the saccade. These observations suggest that there are other influences besides visual masking that are exerted early in the visual pathway to modulate visual processing during saccadic eye movements. A corollary discharge process is the most likely candidate to exert these influences.

Measurements of ultrasonic pulse distortion produced by human chest wall.

Ultrasonic wavefront distortion produced by transmission through human chest wall specimens was measured over a two-dimensional aperture. Measured pulse wavefronts were sometimes disrupted by secondary wavefronts produced by interaction between the transmitted pulses and the bone and cartilage structures of the rib cage. The secondary wavefronts produced large distortions in the received waveforms and interfered with the determination of the wavefront distortion caused by soft-tissue inhomogeneities. The effects of secondary wavefronts were minimized by reducing the region of analysis. Differences in arrival time and energy level between these restricted regions and references that account for geometric delay and spreading were computed. Spectral changes were assessed by calculating a waveform similarity factor that is decreased from 1.0 by changes in waveform shape. For 16 different intercostal spaces, the arrival time fluctuations of the measured waveforms had an average (+/-s.d.) rms value of 21.3 (+/-8.4) ns and an average correlation length of 2.50 (+/-0.62) mm. The energy level fluctuations had an average rms value of 1.57 (+/-0.45) dB and an average correlation length of 1.98 (+/-0.33) mm, and the average waveform similarity factor was 0.964 (+/-0.012). For soft-tissue inhomogeneities in chest wall specimens, the average rms arrival time and energy level fluctuations were less than half those measured for the abdominal wall. However, although the average correlation length of the arrival time fluctuations was less than half that found for the abdominal wall, the average correlation length of the energy level fluctuations was similar to that of the abdominal wall.

Measurement and correction of ultrasonic pulse distortion produced by the human breast

Ultrasonic wavefront distortion produced by transmission through breast tissue specimens was measured in a two-dimensional aperture. Differences in arrival time and energy level between the measured waveforms and references that account for geometric delay and spreading were calculated. Also calculated was a waveform similarity factor that is decreased from 1.0 by changes in waveform shape. For nine different breast specimens, the arrival time fluctuations had an average (+/- s.d.) rms value of 66.8 (+/- 12.6) ns and an associated correlation length of 4.3 (+/- 1.1) mm, while the energy level fluctuations had an average rms value of 5.0 (+/- 0.5) dB and a correlation length of 3.4 (+/- 0.8) mm. The corresponding waveform similarity factor was 0.910 (+/- 0.023). The effect of the wavefront distortion on focusing and the ability of time-shift compensation to remove the distortion were evaluated by comparing parameters such as the -30-dB effective radius, the -10-dB peripheral energy ratio, and the level at which the effective radius departs from an ideal by 10% for the focus obtained without compensation, with time-shift estimation and compensation in the aperture, and with time-shift estimation and compensation performed after backpropagation. For the nine specimens, the average -10-dB peripheral energy ratio of the focused beams fell from 3.82 (+/- 1.83) for the uncompensated data to 0.96 (+/- 0.18) with time-shift compensation in the aperture and to 0.63 (+/- 0.07) with time-shift compensation after backpropagation. The average -30-dB effective radius and average 10% deviation level were 4.5 (+/- 0.8) mm and -19.2 (+/- 3.5) dB, respectively, for compensation in the aperture and 3.2 (+/- 0.7) mm and -22.8 (+/- 2.8) dB, respectively, for compensation after backpropagation. The corresponding radius for the uncompensated data was not meaningful because the dynamic range of the focus was generally less than 30 dB in the elevation direction, while the average 10% deviation level for the uncompensated data was -4.9 (+/- 4.1) dB. The results indicate that wavefront distortion produced by breast significantly degrades ultrasonic focus in the low MHz frequency range and that much of this degradation can be eliminated using wavefront backpropagation and time-shift compensation.

SYSTEMS ANALYSIS APPLIED TO INTRACRANIAL PRESSURE WAVEFORMS AND CORRELATION WITH CLINICAL STATUS IN HEAD INJURED PATIENTS

Intracranial pressure waveforms (ICPWF) in head injured patients vary with the nature and severity of injury. Clinical interpretation of ICPWF shape is not defined. Spectral analysis provides an objective method of measuring changes in waveform shape, but the indices most suitable for clinical use remain unknown. Spectral analysis has been applied to ICPWF recorded from 30 patients with head injury, classified on clinical grounds into good, poor and intermediate groups. Normalized indices derived from ratios of certain characteristics of the ICP waveform to those of the arterial pressure (AP) waveform, were different (P less than 0.05) in all groups. A simple index examined was the harmonic count ratio (Nc:Na) which decreased with increasing severity of injury. ICP/AP harmonic transfer functions were derived, and demonstrated a peaked response in the range 10-12 Hz. Increasing attenuation of this peaked response occurred with increasing severity of injury. These results suggest that transfer functions may be a clinically useful index of intracranial conditions.

Differential diagnosis of ischaemic ulceration of the leg using ultrasound.

SUMMARY Whilst most ulcers on the leg can be confidently and easily separated into those due to venous insufficiency and those due to arterial obstruction, some may present problems of differential diagnosis. Further investigation then becomes necessary. In order to avoid arteriography a new, quick, transcutaneous method has been evolved, which is painless, repeatable and can be carried out in an outpatient clinic. This technique uses two ultrasonic fiowmeters. The propagation time of the pulse wave between two measuring sites along the arterial system of the leg and the change in waveform shape between these two sites are measured.