The instrumented single leg stance test detects early balance impairment in people with multiple sclerosis.

Balance impairment is frequent in people with multiple sclerosis (pwMS) and affects risk of falls and quality of life. By using inertial measurement units (IMUs) on the Single Leg Stance Test (SLS) we aimed to discriminate healthy controls (HC) from pwMS and detect differences in balance endurance and quality. Thirdly, we wanted to test the correlation between instrumented SLS parameters and self-reported measures of gait and balance. Fifty-five pwMS with mild (EDSS<4) and moderate disability (EDSS≥4) and 20 HC performed the SLS with 3 IMUs placed on the feet and sacrum and filled the Twelve Item Multiple Sclerosis Walking Scale (MSWS-12) questionnaire. A linear mixed model was used to compare differences in the automated balance measures. Balance duration was significantly longer in HC compared to pwMS (p < 0.001) and between the two disability groups (p < 0.001). Instrumented measures identified that trunk stability (normalized mediolateral and antero-posterior center of mass stability) had the strongest association with disability (R2 marginal 0.30, p < 0.001) and correlated well with MSWS-12 (R = 0.650, p < 0.001). PwMS tended to overestimate own balance compared to measured balance duration. The use of both self-reported and objective assessments from IMUs can secure the follow-up of balance in pwMS.

Worst-case analysis of array beampatterns using interval arithmetic.

Over the past decade, interval arithmetic (IA) has been used to determine tolerance bounds of phased-array beampatterns. IA only requires that the errors of the array elements are bounded and can provide reliable beampattern bounds even when a statistical model is missing. However, previous research has not explored the use of IA to find the error realizations responsible for achieving specific bounds. In this study, the capabilities of IA are extended by introducing the concept of "backtracking," which provides a direct way of addressing how specific bounds can be attained. Backtracking allows for the recovery of the specific error realization and corresponding beampattern, enabling the study and verification of which errors result in the worst-case array performance in terms of the peak sidelobe level (PSLL). Moreover, IA is made applicable to a wider range of arrays by adding support for arbitrary array geometries with directive elements and mutual coupling in addition to element amplitude, phase, and positioning errors. Last, a simple formula for approximate bounds of uniformly bounded errors is derived and numerically verified. This formula gives insights into how array size and apodization cannot reduce the worst-case PSLL beyond a certain limit.

Inertial Sensor-Based Estimation of Temporal Events in Skating Sub-Techniques While In-Field Roller Skiing.

The aim of this study was to test and adapt a treadmill-developed method for determination of inner-cycle parameters and sub-technique in cross-country roller ski skating for a field application. The method is based on detecting initial and final ground contact of poles and skis during cyclic movements. Eleven athletes skied 4 laps of 2.5 km at low- and high-endurance intensities, using 2 types of skis with different rolling coefficients. Participants were equipped with inertial measurement units attached to their wrists and skis, and insoles with pressure sensors and poles with force measurements were used as reference systems. The method based on inertial measurement units was able to detect >97% of the temporal events detected with the reference system. The inner-cycle temporal parameters had a precision ranging from 49 to 59 milliseconds, corresponding to 3.9% to 13.7% of the corresponding inner-cycle duration. Overall, this study showed good reliability of using inertial measurement units on athletes' wrists and skis to determine temporal events, inner-cycle parameters, and the performed sub-techniques in cross-country roller ski skating in field conditions.

Point detection in textured ultrasound images.

Detection of point scatterers in textured ultrasound images can be challenging. This paper investigates how four multilook methods can improve the detection. We analyze many images with known point scatterer locations and randomly textured backgrounds. The normalized matched filter (NMF) and multilook coherence factor (MLCF) methods are normalized methods that do not require any texture correction prior to detection analysis. They are especially propitious when optimal texture correction of the ultrasound images is difficult to obtain. The results show significant improvement in detection performance when the MLCF method is weighted with the prewhitened and texture corrected image. The method can be applied even when we do not have prior knowledge about the optimal prewhitening limits. The multilook methods NMF and NMF weighted (NMFW) are very favorable methods to apply on images where acoustic noise dominates the speckle background.

Inner-Cycle Phases Can Be Estimated from a Single Inertial Sensor by Long Short-Term Memory Neural Network in Roller-Ski Skating.

OBJECTIVE: The aim of this study was to provide a new machine learning method to determine temporal events and inner-cycle parameters (e.g., cycle, pole and ski contact and swing time) in cross-country roller-ski skating on the field, using a single inertial measurement unit (IMU). METHODS: The developed method is based on long short-term memory neural networks to detect the initial and final contact of the poles and skis with the ground during the cyclic movements. Eleven athletes skied four laps of 2.5 km at a low and high intensity using skis with two different rolling coefficients. They were equipped with IMUs attached to the upper back, lower back and to the sternum. Data from force insoles and force poles were used as the reference system. RESULTS: The IMU placed on the upper back provided the best results, as the LSTM network was able to determine the temporal events with a mean error ranging from -1 to 11 ms and had a standard deviation (SD) of the error between 64 and 70 ms. The corresponding inner-cycle parameters were calculated with a mean error ranging from -11 to 12 ms and an SD between 66 and 74 ms. The method detected 95% of the events for the poles and 87% of the events for the skis. CONCLUSION: The proposed LSTM method provides a promising tool for assessing temporal events and inner-cycle phases in roller-ski skating, showing the potential of using a single IMU to estimate different spatiotemporal parameters of human locomotion.

Validation of temporal parameters within the skating sub-techniques when roller skiing on a treadmill, using inertial measurement units.

The aim of this study was to develop and validate a method using inertial measurements units (IMUs) to determine inner-cycle parameters (e.g., cycle, poles and skis contact, and swing time) and the main sub-techniques (i.e., G2, G3 and G4) in cross-country roller ski skating on a treadmill. The developed method is based on the detection of poles and skis initial and final contacts with the ground during the cyclic movements. Thirteen well-trained athletes skied at different combinations of speed (6-24 km∙h-1) and incline (2-14%) on a treadmill using the three different sub-techniques. They were equipped with IMUs attached to their wrists and skis. Their movements were tracked using reflective markers and a multiple camera infrared system. The IMU-based method was able to detect more than 99% of the temporal events. It calculated the inner-cycle temporal parameters with a precision ranging from 19 to 66 ms, corresponding to 3.0% to 7.8% of the corresponding inner-cycle duration. The obtained precision would likely allow differentiation of skiers on different performance levels and detection of technique changes due to fatigue. Overall, this laboratory validation provides interesting possibilities also for outdoor applications.

Accurate prediction of transmission through a lensed row-column addressed array.

Using a diverging lens on a row-column array (RCA) can increase the size of its volumetric image and thus significantly improve its clinical value. Here, a ray tracing method is presented to predict the position of the transmitted wave so that it can be used to make beamformed images. The usable transmitted field-of-view (FOV) is evaluated for a lensed 128 + 128 element RCA by comparing the theoretic prediction of the emitted wavefront position with three-dimensional (3D) finite element simulation of the emitted field. The FOV of the array is found to be 122° ± 2° in the direction orthogonal to the emitting elements and 28.5°-51.2°, depending on depth and element position, for the direction lying along the element. Moreover, the proposed ray tracing method is compared with a simpler thin lens model, and it is shown that the improved accuracy of the proposed method can increase the usable transmitted FOV up to 25.1°.

Point Detection in Ultrasound Using Prewhitening and Multilook Optimization.

We investigate methods to improve the detection of point scatterers in ultrasound imaging using the standard delay-and-sum (DAS) image as our starting point. An optimized whitening transform can increase the spatial resolution of the image. By splitting an image's frequency spectrum into many subsets using the multilook technique, we can exploit the coherent properties of a point scatterer. We present three new multilook methods and evaluate their effect on point detection. The performances are compared to DAS using synthetic aperture Field II simulations of a point scatterer in uniform speckle background. The results show that optimized prewhitening of the images can significantly improve the point detection. The multilook methods have the potential to improve the detection performance further when a sufficient number of looks are used. If prior knowledge about the optimal spectrum limits is unavailable and a nonoptimal prewhitening is applied, applying that the new multilook methods can considerably improve the point detection.

Sensor-based gait analyses of the six-minute walk test identify qualitative improvement in gait parameters of people with multiple sclerosis after rehabilitation.

The aim of this work was to determine whether wearable inertial measurement units (IMUs) could detect gait improvements across different disability groups of people with Multiple Sclerosis (pwMS) by the six-minute walk test (6MWT) during a rehabilitation stay in a specialized rehabilitation center. Forty-six pwMS and 20 healthy controls (HC) were included in the study. They performed the 6MWT with two inertial measurement units (IMUs) placed on the feet. Thirty-two of the pwMS were retested at the end of the stay. PwMS were divided in a mild-disability and a moderate-disability group. The 6MWT was divided in six sections of 1 min each for technical analysis, and linear mixed models were used for statistical analyses. The comparison between the two disability groups and HC highlighted significant differences for each gait parameter (all p < 0.001). The crossing effect between the test-retest and the two disability groups showed greater improvement for the moderate-disability group. Finally, the gait parameter with the higher effect size, allowing the best differentiation between the disability groups, was the foot flat ratio (R2 = 0.53). Gait analyses from wearable sensors identified different evolutions of gait patterns during the 6MWT in pwMS with different physical disability. The measured effect of a short-time rehabilitation on gait with 6MWT was higher for pwMS with higher degree of disability. Using IMUs in a clinical setting allowed to identify significant changes in inter-stride gait patterns. Wearable sensors and key parameters have the potential as useful clinical tools for focusing on gait in pwMS.

Detection of Point Scatterers in Medical Ultrasound.

We present an overview of the detection of point scatterers in ultrasound images and suggest strategies for evaluating and measuring the detection performance. We use synthetic aperture Field II simulations of a point scatterer in speckle background and evaluate how common imaging techniques affect point target detectability. We discuss how to compare different methods and calculate confidence intervals. In general, applying speckle reduction methods reduces the point detection performance. However, the results show that it is possible to smooth the speckle background and preserve relatively high performance with a suitable and optimized method. The different detection performances of the advanced beamforming methods coherence factor (CF), phase coherence factor (PCF), and Capon's minimum variance (MV) are presented and benchmarked with standard delay-and-sum (DAS). The results show that CF achieves slightly better detection performance than DAS for weak point scatterers, whereas PCF and MV perform worse than DAS. Choice of apodization window and adaptive aperture size affects the probability of detection. Results show that methods that preserve spatial resolution have better detection performance of point scatterers.

Speckle Reduction Using Adaptive Receive-Side Compounding.

A typical approach to reduce speckle in coherent imaging systems is to average same-target images with different speckle realizations. We study settings where such realizations come from applying different transducer-array element weights at reception, referred to here as receive compounding. An effect of such compounding is reduced spatial resolution, causing smearing of point-like image structures, filling of cysts, and expansion of hyperechoic regions. In this article, we study how these unwanted effects can be mitigated by combining the compounding with a small, phase-based, adaptive steering of the array at reception. The adaptivity is based on a criterion akin to that of the Capon beamformer; a minimum-output distortionless response. Here, the distortionless part ensures that however we steer, we have a uniform at-focus response. We have applied this adaptive steering in combination with several receive compounding techniques on simulated Field II, phantom, and in vivo data. The results show that all the studied compounding techniques respond to this positively in light of the mentioned unwanted effects. The technique based on Thomson's multitaper method even surpassed the noncompounded equivalent in reproducing the geometry of structures. The speckle reduction, as measured by the change in the pixel mean to standard deviation ratio, is indeed lower, and there are subtle changes in the spatial speckle patterns when applying steering; however, we believe that in most cases, the negative effects are tolerable in light of the benefits gained. The suggested approach is intuitive and easily implemented.

The Generalized Contrast-to-Noise Ratio: A Formal Definition for Lesion Detectability.

In the last 30 years, the contrast-to-noise ratio (CNR) has been used to estimate the contrast and lesion detectability in ultrasound images. Recent studies have shown that the CNR cannot be used with modern beamformers, as dynamic range alterations can produce arbitrarily high CNR values with no real effect on the probability of lesion detection. We generalize the definition of CNR based on the overlap area between two probability density functions. This generalized CNR (gCNR) is robust against dynamic range alterations; it can be applied to all kind of images, units, or scales; it provides a quantitative measure for contrast; and it has a simple statistical interpretation, i.e., the success rate that can be expected from an ideal observer at the task of separating pixels. We test gCNR on several state-of-the-art imaging algorithms and, in addition, on a trivial compression of the dynamic range. We observe that CNR varies greatly between the state-of-the-art methods, with improvements larger than 100%. We observe that trivial compression leads to a CNR improvement of over 200%. The proposed index, however, yields the same value for compressed and uncompressed images. The tested methods showed mismatched performance in terms of lesion detectability, with variations in gCNR ranging from -0.08 to +0.29. This new metric fixes a methodological flaw in the way we study contrast and allows us to assess the relevance of new imaging algorithms.

The Effect of Dynamic Range Alterations in the Estimation of Contrast.

Many adaptive beamformers claim to produce images with increased contrast, a feature that could enable a better detection of lesions and anatomical structures. Contrast is often quantified using the contrast ratio (CR) and the contrast-to-noise ratio (CNR). The estimation of CR and CNR can be affected by dynamic range alterations (DRAs), such as those produced by a trivial gray-level transformation. Thus, we can form the hypothesis that contrast improvements from adaptive beamformers can, partly, be due to DRA. In this paper, we confirm this hypothesis. We show evidence on the influence of DRA on the estimation of CR and CNR and on the fact that several methods in the state of the art do alter the DR. To study this phenomenon, we propose a DR test (DRT) to estimate the degree of DRA and we apply it to seven beamforming methods. We show that CR improvements correlate with DRT with [Formula: see text] in simulated data and [Formula: see text] in experiments. We also show that DRA may lead to increased CNR values, under some circumstances. These results suggest that claims on lesion detectability, based on CR and CNR values, should be revised.

Signal Coherence and Image Amplitude With the Filtered Delay Multiply and Sum Beamformer.

The filtered delay multiply and sum (F-DMAS) beamformer has recently been presented in the context of medical ultrasound image formation. This nonlinear beamformer produces images with improved contrast resolution and noise rejection when compared with the delay and sum (DAS) beamformer. In an attempt to better understand the origin of the improved image quality, this paper shows a theoretical study of the image amplitude statistics backed up by numerical simulations. The results show that the difference in image amplitude using the DAS or F-DMAS beamformers can be partly explained by the way signal coherence influences both beamformers. When using the F-DMAS compared with the DAS beamformer, the image amplitude is shown to be more dependent on the signal coherence. Experimental ultrasound images of a phantom confirm our findings.

Improved Visualization of Hydroacoustic Plumes Using the Split-Beam Aperture Coherence.

Natural seepage of methane into the oceans is considerable, and plays a role in the global carbon cycle. Estimating the amount of this greenhouse gas entering the water column is important in order to understand their environmental impact. In addition, leakage from man-made structures such as gas pipelines may have environmental and economical consequences and should be promptly detected. Split beam echo sounders (SBES) detect hydroacoustic plumes due to the significant contrast in acoustic impedance between water and free gas. SBES are also powerful tools for plume characterization, with the ability to provide absolute acoustic measurements, estimate bubble trajectories, and capture the frequency dependent response of bubbles. However, under challenging conditions such as deep water and considerable background noise, it can be difficult to detect the presence of gas seepage from the acoustic imagery alone. The spatial coherence of the wavefield measured across the split beam sectors, quantified by the coherence factor (CF), is a computationally simple, easily available quantity which complements the acoustic imagery and may ease the ability to automatically or visually detect bubbles in the water column. We demonstrate the benefits of CF processing using SBES data from the Hudson Canyon, acquired using the Simrad EK80 SBES. We observe that hydroacoustic plumes appear more clearly defined and are easier to detect in the CF imagery than in the acoustic backscatter images.

Hypothesis of Improved Visualization of Microstructures in the Interventricular Septum with Ultrasound and Adaptive Beamforming.

In this work, in vivo ultrasound cardiac images created with Capon's minimum variance adaptive beamformer are compared with images acquired with the conventional delay-and-sum beamformer. Specifically, we provide three views of a human heart imaged through the parasternal short-axis, the parasternal long-axis and the apical four-chamber views. The minimum variance beamformer produced images with improved lateral resolution, resulting in better resolved speckle structure and improved edges, especially on close investigation of the interventricular septum. These improvements in image quality might possibly improve the visualization of microstructures in the human heart.

The iterative adaptive approach in medical ultrasound imaging.

Many medical ultrasound imaging systems are based on sweeping the image plane with a set of narrow beams. Usually, the returning echo from each of these beams is used to form one or a few azimuthal image samples. We model, for each radial distance, jointly the full azimuthal scanline. The model consists of the amplitudes of a set of densely placed potential reflectors (or scatterers), cf. sparse signal representation. To fit the model, we apply the iterative adaptive approach (IAA) on data formed by a sequenced time delay and phase shift. The performance of the IAA in combination with our time-delayed and phase-shifted data are studied on both simulated data of scenes consisting of point targets and hollow cyst-like structures, and recorded ultrasound phantom data from a specially adapted commercially available scanner. The results show that the proposed IAA is more capable of resolving point targets and gives better defined and more geometrically correct cyst-like structures in speckle images compared with the conventional delay-and-sum (DAS) approach. Compared with a Capon beamformer, the IAA showed an improved rendering of cyst-like structures and a similar point-target resolvability. Unlike the Capon beamformer, the IAA has no user parameters and seems unaffected by signal cancellation. The disadvantage of the IAA is a high computational load.

Capon beamforming and moving objects--an analysis of lateral shift-invariance.

If an ultrasound imaging system provides a presentation of a moving object which is sensitive to small spatial shifts, the system is said to be locally spatially shift-variant. This can happen, for instance, if the axial or lateral sampling is insufficient. The Capon beamformer has been shown to provide increased lateral resolution in ultrasound images. Increased lateral resolution should demand denser lateral sampling. However, in previous literature on Capon beamforming for medical ultrasound imaging, only single-frame scenarios have been simulated. Temporal behavior and effects caused by the increased resolution and lack of oversampling have therefore been neglected. In this paper, we analyze the local lateral shift-invariance of the Capon beamformer when imaging moving objects. We show that insufficient lateral sampling makes an imaging system based on the Capon beamformer laterally shift-variant. Different methods for oversampling on transmit and receive are then discussed and investigated to improve on the Capon beamformer. It is shown that lateral shift-invariance can be improved by oversampling based on phase rotation on receive without affecting the acquisition frame rate and with a minor change in processing complexity.

Implementing capon beamforming on a GPU for real-time cardiac ultrasound imaging.

Capon beamforming is associated with a high computational complexity, which limits its use as a real-time method in many applications. In this paper, we present an implementation of the Capon beamformer that exhibits realtime performance when applied in a typical cardiac ultrasound imaging setting. To achieve this performance, we make use of the parallel processing power found in modern graphics processing units (GPUs), combined with beamspace processing to reduce the computational complexity as the number of array elements increases. For a three-dimensional beamspace, we show that processing rates supporting real-time cardiac ultrasound imaging are possible, meaning that images can be processed faster than the image acquisition rate for a wide range of parameters. Image quality is investigated in an in vivo cardiac data set. These results show that Capon beamforming is feasible for cardiac ultrasound imaging, providing images with improved lateral resolution both in element-space and beamspace.

Multi-line transmission in medical imaging using the second-harmonic signal.

The emergence of three-dimensional imaging in the field of medical ultrasound imaging has greatly increased the number of transmissions needed to insonify a whole volume. With a large number of transmissions comes a low image frame rate. When using classical transmission techniques, as in two-dimensional imaging, the frame rate becomes unacceptably low, prompting the use of alternative transmission patterns that require less time. One alternative is to use a multi-line transmission (MLT) technique which consists of transmitting several pulses simultaneously in different directions. Perturbations appear when acquiring and beamforming the signal in the direction of one pulse because of the pulses sent in other directions. The edge waves from the pulses transmitted in a different direction add to the signal transmitted in the direction of interest, resulting in artifacts in the final image. Taking advantage of the nonlinear propagation of sound in tissue, the second-harmonic signal can be used with the MLT technique. The image obtained using the second-harmonic signal, compared with an image obtained using the fundamental signal, should have reduced artifacts coming from other pulses transmitted simultaneously. Simulations, backed up by experiments imaging a wire target and an in vivo left ventricle, confirm that the hypothesis is valid. In the studied case, the perturbations appear as an increase in the signal level around the main echo of a point scatterer. When using the fundamental signal, the measured amplitude level of the perturbations was approximately -40 dB compared with the maximum signal amplitude (-27 dB in vivo), whereas it was around -60 dB (-45 dB in vivo) for the second-harmonic signal. The MLT technique encounters limitations in the very near field where the pulses overlap and the perturbation level also increases for images with strong speckle and low contrast.