The Quadrature Method: A Novel Dipole Localisation Algorithm for Artificial Lateral Lines Compared to State of the Art.

The lateral line organ of fish has inspired engineers to develop flow sensor arrays-dubbed artificial lateral lines (ALLs)-capable of detecting near-field hydrodynamic events for obstacle avoidance and object detection. In this paper, we present a comprehensive review and comparison of ten localisation algorithms for ALLs. Differences in the studied domain, sensor sensitivity axes, and available data prevent a fair comparison between these algorithms from their original works. We compare them with our novel quadrature method (QM), which is based on a geometric property specific to 2D-sensitive ALLs. We show how the area in which each algorithm can accurately determine the position and orientation of a simulated dipole source is affected by (1) the amount of training and optimisation data, and (2) the sensitivity axes of the sensors. Overall, we find that each algorithm benefits from 2D-sensitive sensors, with alternating sensitivity axes as the second-best configuration. From the machine learning approaches, an MLP required an impractically large training set to approach the optimisation-based algorithms' performance. Regardless of the data set size, QM performs best with both a large area for accurate predictions and a small tail of large errors.

Three-dimensional multi-source localization of underwater objects using convolutional neural networks for artificial lateral lines.

This research focuses on the signal processing required for a sensory system that can simultaneously localize multiple moving underwater objects in a three-dimensional (3D) volume by simulating the hydrodynamic flow caused by these objects. We propose a method for localization in a simulated setting based on an established hydrodynamic theory founded in fish lateral line organ research. Fish neurally concatenate the information of multiple sensors to localize sources. Similarly, we use the sampled fluid velocity via two parallel lateral lines to perform source localization in three dimensions in two steps. Using a convolutional neural network, we first estimate a two-dimensional image of the probability of a present source. Then we determine the position of each source, via an automated iterative 3D-aware algorithm. We study various neural network architectural designs and different ways of presenting the input to the neural network; multi-level amplified inputs and merged convolutional streams are shown to improve the imaging performance. Results show that the combined system can exhibit adequate 3D localization of multiple sources.

Recurrent neural networks for hydrodynamic imaging using a 2D-sensitive artificial lateral line.

The lateral line is a mechanosensory organ found in fish and amphibians that allows them to sense and act on their near-field hydrodynamic environment. We present a 2D-sensitive artificial lateral line (ALL) comprising eight all-optical flow sensors, which we use to measure hydrodynamic velocity profiles along the sensor array in response to a moving object in its vicinity. We then use the measured velocity profiles to reconstruct the object's location, via two types of neural networks: feed-forward and recurrent. Several implementations of feed-forward neural networks for ALL source localisation exist, while recurrent neural networks may be more appropriate for this task. The performance of a recurrent neural network (the long short-term memory, LSTM) is compared to that of a feed-forward neural network (the online-sequential extreme learning machine, OS-ELM) via localizing a 6 cm sphere moving at 13 cm s-1. Results show that, in a 62 cm [Formula: see text] 9.5 cm area of interest, the LSTM outperforms the OS-ELM with an average localisation error of 0.72 cm compared to 4.27 cm, respectively. Furthermore, the recurrent network is relatively less affected by noise, indicating that recurrent connections can be beneficial for hydrodynamic object localisation.

Bio-inspired all-optical artificial neuromast for 2D flow sensing.

We present the design, fabrication and testing of a novel all-optical 2D flow velocity sensor, inspired by a fish lateral line neuromast. This artificial neuromast consists of optical fibres inscribed with Bragg gratings supporting a fluid force recipient sphere. Its dynamic response is modelled based on the Stokes solution for unsteady flow around a sphere and found to agree with experimental results. Tuneable mechanical resonance is predicted, allowing a deconvolution scheme to accurately retrieve fluid flow speed and direction from sensor readings. The optical artificial neuromast achieves a low frequency threshold flow sensing of 5 mm s-1 and 5 µm s-1 at resonance, with a typical linear dynamic range of 38 dB at 100 Hz sampling. Furthermore, the optical artificial neuromast is shown to determine flow direction within a few degrees.

Performance of neural networks for localizing moving objects with an artificial lateral line.

Fish are able to sense water flow velocities relative to their body with their mechanoreceptive lateral line organ. This organ consists of an array of flow detectors distributed along the fish body. Using the excitation of these individual detectors, fish can determine the location of nearby moving objects. Inspired by this sensory modality, it is shown here how neural networks can be used to extract an object's location from simulated excitation patterns, as can be measured along arrays of stationary artificial flow velocity sensors. The applicability, performance and robustness with respect to input noise of different neural network architectures are compared. When trained and tested under high signal to noise conditions (46 dB), the Extreme Learning Machine architecture performs best with a mean Euclidean error of 0.4% of the maximum depth of the field D, which is taken half the length of the sensor array. Under lower signal to noise conditions Echo State Networks, having recurrent connections, enhance the performance while the Multilayer Perceptron is shown to be the most noise robust architecture. Neural network performance decreased when the source moves close to the sensor array or to the sides of the array. For all considered architectures, increasing the number of detectors per array increased localization performance and robustness.

Manufacturer evaluations of endograft modifications.

The motivation to modify the design of a vascular device can arise from a number of sources. Clinical experience with the unmodified device could suggest new design modifications to improve device performance or clinical outcomes. Similarly, clinical success with a device often suggests modifications that could broaden the applicability of the device to enable treatment of different or more advanced disease states. As a specific example, both of these scenarios have arisen during the last decade in the evolution of endovascular grafts for the treatment of abdominal aortic aneurysms, with modifications enabling the treatment of patients with shorter infrarenal necks, more angulated anatomy, and smaller access vessels. These modifications have been made by manufacturers and additionally by physicians who create branched and fenestrated devices. The experience to date with the use of fenestrated devices and the development of chimney, snorkel, and periscope techniques suggests that modifications to off-the-shelf devices may provide some clinical benefit. This experience provides additional motivation for manufacturers to develop devices to address the clinical needs not met with their current product lines. For manufacturers, the device development process includes an assessment of the new device design to determine the appropriate evaluation strategy to support the safety and effectiveness of the modified device. This report provides a high-level overview of the process generally followed by device manufacturers to evaluate a proposed device modification before market release, in accordance with local country regulations and recognized international standards such as the International Organization of Standardization (ISO) standards for endovascular grafts (ISO 25539 Part 1).

Anatomical and functional changes in the lower urinary tract following spontaneous vaginal delivery.

OBJECTIVE: To assess the incidence of urinary incontinence in pregnancy and after spontaneous vaginal delivery and its relation with changes in the static and dynamic function of the pelvic floor. DESIGN: The second part of a prospective longitudinal study. SETTING: University Hospital Groningen and Martini Hospital Groningen, the Netherlands. POPULATION: A cohort of 62 women before and after spontaneous vaginal delivery at term and 27 nulliparous non-pregnant controls. METHODS: Urinary incontinence was measured by a questionnaire and by a 24 hour pad test. The position and mobility of the urethrovesical junction were measured by perineal ultrasound and related to simultaneously measured abdominal pressure changes. Serial investigations were done at 38 weeks of gestation and at 6 weeks and 6 months after delivery. MAIN OUTCOME MEASURES: Urinary incontinence and its relation with the position of the urethrovesical junction at rest and with the mobility of the urethrovesical junction during Valsalva and during coughing, indicated by the displacement/pressure coefficient and with obstetric variables. RESULTS: After delivery, reported urinary incontinence was reduced from 26% at 38 weeks of gestation to 16% and 15% at 6 weeks and 6 months after delivery, respectively. Even lower rates were measured by the 24 hour pad test, which revealed a decrease from 14% at 38 weeks to 10% and 5% at 6 weeks and 6 months postpartum, respectively. Six weeks and six months after delivery, the angle of the urethrovesical junction at rest was significantly increased compared with the non-pregnant control women. Compared with the antenatal measurements, the displacement/pressure coefficients during coughing and during the Valsalva manoeuvre were significantly increased six weeks after delivery. Six months after delivery, only the coefficient for coughing was still significantly greater than the antenatal value and the value in the non-pregnant control group. No relations were found between urethrovesical junction measurements and obstetric variables and subjective or objective urinary incontinence parameters. CONCLUSION: Although pregnancy and spontaneous vaginal delivery significantly increased the degree of bladder neck descent during coughing, urinary incontinence, quite common during pregnancy, occurs less frequently postpartum.