Blood Pressure Response and Pulse Arrival Time During Exercise Testing in Well-Trained Individuals

Introduction: There is a lack of data describing the blood pressure response (BPR) in well-trained individuals. In addition, continuous bio-signal measurements are increasingly investigated to overcome the limitations of intermittent cuff-based BP measurements during exercise testing. Thus, the present study aimed to assess the BPR in well-trained individuals during a cycle ergometer test with a particular focus on the systolic BP (SBP) and to investigate pulse arrival time (PAT) as a continuous surrogate for SBP during exercise testing. Materials and Methods: Eighteen well-trained male cyclists were included (32.4 ± 9.4 years; maximal oxygen uptake 63 ± 10 ml/min/kg) and performed a stepwise lactate threshold test with 5-minute stages, followed by a continuous test to voluntary exhaustion with 1-min increments when cycling on an ergometer. BP was measured with a standard automated exercise BP cuff. PAT was measured continuously with a non-invasive physiological measurements device (IsenseU) and metabolic consumption was measured continuously during both tests. Results: At lactate threshold (281 ± 56 W) and maximal intensity test (403 ± 61 W), SBP increased from resting values of 136 ± 9 mmHg to maximal values of 219 ± 21 mmHg and 231 ± 18 mmHg, respectively. Linear within-participant regression lines between PAT and SBP showed a mean r2 of 0.81 ± 17. Conclusion: In the present study focusing on the BPR in well-trained individuals, we observed a more exaggerated systolic BPR than in comparable recent studies. Future research should follow up on these findings to clarify the clinical implications of the high BPR in well-trained individuals. In addition, PAT showed strong intra-individual associations, indicating potential use as a surrogate SBP measurement during exercise testing.publishedVersio

Blood Pressure Response and Pulse Arrival Time During Exercise Testing in Well-Trained Individuals

Introduction: There is a lack of data describing the blood pressure response (BPR) in well-trained individuals. In addition, continuous bio-signal measurements are increasingly investigated to overcome the limitations of intermittent cuff-based BP measurements during exercise testing. Thus, the present study aimed to assess the BPR in well-trained individuals during a cycle ergometer test with a particular focus on the systolic BP (SBP) and to investigate pulse arrival time (PAT) as a continuous surrogate for SBP during exercise testing. Materials and Methods: Eighteen well-trained male cyclists were included (32.4 ± 9.4 years; maximal oxygen uptake 63 ± 10 ml/min/kg) and performed a stepwise lactate threshold test with 5-minute stages, followed by a continuous test to voluntary exhaustion with 1-min increments when cycling on an ergometer. BP was measured with a standard automated exercise BP cuff. PAT was measured continuously with a noninvasive physiological measurements device (IsenseU) and metabolic consumption was measured continuously during both tests. Results: At lactate threshold (281 ± 56 W) and maximal intensity test (403 ± 61 W), SBP increased from resting values of 136 ± 9 mmHg to maximal values of 219 ± 21 mmHg and 231 ± 18 mmHg, respectively. Linear within-participant regression lines between PAT and SBP showed a mean r 2 of 0.81 ± 17. Conclusion: In the present study focusing on the BPR in well-trained individuals, we observed a more exaggerated systolic BPR than in comparable recent studies. Future research should follow up on these findings to clarify the clinical implications of the high BPR in well-trained individuals. In addition, PAT showed strong intra-individual associations, indicating potential use as a surrogate SBP measurement during exercise testing.publishedVersio

Static Elastography With Ultrasound Using Adaptive Beamforming

Background and motivation The health of human tissue can be indicated by the stiffness of the tissue. It is known that the risk of a nodule being malignant is increased with the stiffness of the nodule. Elastography is an imaging mode capable of displaying the stiffness of the tissue. Static elastography with ultrasound consists of creating a pre- and post-compression ultrasound image where the tissue being imaged has been compressed between the images. The displacement of tissue is calculated along the axial dimension based on the assumption that speckle pattern follows tissue movement. Tissue strain, indicating the stiffness of tissue, can then be found from the displacement of the tissue. Speckle statistics and the speckle pattern are different for images created with conventional and adaptive (Capon) beamforming. The speckle pattern created with adaptive beamforming has a smaller and more distinct pattern because of the improved resolution by adaptive beamforming. Hypothetically a more distinct pattern should result in better correlation and thus better displacement estimation. Recently it has been shown that lateral oversampling is needed to achieve lateral shift-invariance between image frames when using adaptive beamforming. Shift-invariance between frames is especially important for elastography since the displacement estimate is based on correlation between two nearly identical frames. Approach To simulate static elastography two speckle images are created with Field II simulations based on the same scatter phantom, where the scatterers have been displaced axially to create pre- and post-compression ultrasound images. The images are created with the conventional beamformer and the adaptive beamformer with different parameters. In the middle of the phantom a circular object has constant displacement to mimic a hard malignant nodule in the tissue. Results and conclusions We show that lateral oversampling is necessary for single frame scenarios when doing adaptive beamforming and to achieve shift- invariant imaging of speckle. The speckle pattern from adaptive beamforming is more distinct, but our research shows that adaptive beamforming with certain parameters gave similar performance for axial correlation for displacement estimation as conventional beamforming and thus similar accuracy when doing static elastography

Software Beamforming in Medical Ultrasound Imaging - a blessing and a curse

Medical ultrasound (US) imaging is a non-invasive imaging modality. Smaller and cheaper US systems make US imaging available to more people, leading to a democratization of medical US imaging. The improvements of general processing hardware allow the reconstruction of US images to be done in software. These implementations are known as software beamforming and provide access to the US data earlier in the processing chain. Adaptive beamforming exploits the early access to the full US data with algorithms adapting the processing to the data. Adaptive beamforming claims improved image quality. The improved image will potentially result in an improved diagnosis. Adaptive beamformers have seen enormous popularity in the research community with exponential growth in the number of papers published. However, the complexity of the algorithms makes them hard to re-implement, making a thorough comparison of the algorithms difficult. The UltraSound ToolBox (USTB https://www.USTB.no) is an open source processing framework facilitating the comparison of imaging techniques and the dissemination of research results. The USTB, including the implementation of several state-of-the-art adaptive beamformers, has partly been developed in this thesis and used to produce most of the results presented. The results show that some of the contrast improvements reported in the literature turn out to be from secondary effects of adaptive processing. More specifically, we show that many state-of-the-art algorithms alter the dynamic range. These dynamic range alterations are invalidating the conventional contrast metrics. Said differently; many adaptive algorithms are so flexible that they instead of improving the image quality are merely optimizing the metrics used to evaluate the image quality. We suggest a dynamic range test, compromising data, and code, to assess whether an algorithm alters the dynamic range. A thorough review of the contrast metrics used in US imaging shows there is no consensus on the metrics used in the research literature. Therefore, our introduction of the generalized contrast to noise ratio (GCNR) is essential since this is a contrast metric immune to dynamic range alterations. The GCNR is a remedy for the curse of the metric breaking abilities of software beamforming. Software beamforming also has its blessings. The flexible implementations made possible by software beamforming does lead to improved image quality. The improved resolution of the minimum variance adaptive beamformer does lead to enhanced visualization of the interventricular septum in the human heart. The ability to do beamforming in software allows the implementation of the full reconstruction chain from raw data to the final rendered images on an iPhone. As well as the results presented in the published papers, this thesis does a thorough review of the software beamforming processing chain as implemented in the USTB

Resolution Measured as Separability Compared to Full Width Half Maximum for Adaptive Beamformers

Spatial resolution is defined as a system's ability to separate targets using some kind of criterion, such as the Rayleigh criterion. However, in practice, lateral resolution is often evaluated by measuring the Full Width Half Maximum (FWHM at -6dB) of the point spread function (PSF). We hypothesize that FWHM overestimates the system resolution for some adaptive beamformers, compared to using the Rayleigh criterion. Simulation results seem to confirm this hypothesis

The dark region artifact in adaptive ultrasound beamforming

An undesired effect, the dark region artifact (DRA), has been under-communicated in our research community. The DRA appear next to acoustically strong targets for some of the many adaptive beamformers introduced in the literature. This study investigates the DRA for a collection of adaptive beamformers and shows that this effect originates because some of the methods fail to estimate which signals arise in the mainlobe and which originates from sidelobes. The DRA results in darker regions in the ultrasound images, indicating the wrong acoustical amplitude. Therefore, the measured contrast can falsely appear higher for adaptive beamformers affected by the DRA

Assessment of Basic Motions and Technique Identification in Classical Cross-Country Skiing

Cross-country skiing is a popular Olympic winter sport, which is also used extensively as a recreational activity. While cross-country skiing primarily is regarded as a demanding endurance activity it is also technically challenging, as it contains two main styles (classical and skating) and many sub-techniques within these styles. To further understand the physiological demands and technical challenges of cross-country skiing it is imperative to identify sub-techniques and basic motion features during training and competitions. Therefore, this paper presents features for identification and assessment of the basic motion patterns used during classical-style cross-country skiing. The main motivation for this work is to contribute to the development of a more detailed platform for comparing and communicating results from technique analysis methods, to prevent unambiguous definitions and to allow more precise discussions and quality assessments of an athlete's technical ability. To achieve this, our paper proposes formal motion components and classical style technique definitions as well as sub-technique classifiers. This structure is general and can be used directly for other cyclic activities with clearly defined and distinguishable sub-techniques, such as the skating style in cross country skiing. The motion component features suggested in our approach are arm synchronization, leg kick, leg kick direction, leg kick rotation, foot/ski orientation and energy like measures of the arm, and leg motion. By direct measurement, estimation, and the combination of these components, the traditional sub-techniques of diagonal stride, double poling, double poling kick, herringbone, as well as turning techniques can be identified. By assuming that the proposed definitions of the classical XC skiing sub-techniques are accepted, the presented classifier is proven to map measures from the motion component definitions to a unique representation of the sub-techniques. This formalization and structure may be used on new motion components, measurement principles, and classifiers, and therefore provides a framework for comparing different methodologies. Pilot data from a group of high-level cross-country skiers employing inertial measurement sensors placed on the athlete's arms and skis are used to demonstrate the approach. The results show how detailed sub-technique information can be coupled with physical, track, and environmental data to analyze the effects of specific motion patterns, to develop useful debriefing tools for coaches and athletes in training and competition settings, and to explore new research hypotheses.publishedVersio

Automatic Classification of Sub-Techniques in Classical Cross-Country Skiing Using a Machine Learning Algorithm on Micro-Sensor Data

The automatic classification of sub-techniques in classical cross-country skiing provides unique possibilities for analyzing the biomechanical aspects of outdoor skiing. This is currently possible due to the miniaturization and flexibility of wearable inertial measurement units (IMUs) that allow researchers to bring the laboratory to the field. In this study, we aimed to optimize the accuracy of the automatic classification of classical cross-country skiing sub-techniques by using two IMUs attached to the skier’s arm and chest together with a machine learning algorithm. The novelty of our approach is the reliable detection of individual cycles using a gyroscope on the skier’s arm, while a neural network machine learning algorithm robustly classifies each cycle to a sub-technique using sensor data from an accelerometer on the chest. In this study, 24 datasets from 10 different participants were separated into the categories training-, validation- and test-data. Overall, we achieved a classification accuracy of 93.9% on the test-data. Furthermore, we illustrate how an accurate classification of sub-techniques can be combined with data from standard sports equipment including position, altitude, speed and heart rate measuring systems. Combining this information has the potential to provide novel insight into physiological and biomechanical aspects valuable to coaches, athletes and researcherspublishedVersio

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. Index Terms—Delay and sum (DAS) beamformer, filtered delay multiply and sum (F-DMAS) beamformer, signal coherence, statistics. Published Open Access with IEEE. © 2018 IEEE