A Numerical Study of Optimization Methods for Phase-Only Optical Pulse-Shaping

The field of optical pulse-shaping and its applications is introduced, with a focus on time-domain approaches. A numerical investigation of all-fiber, time-domain, phase-only filtering is conducted for arbitrary temporal pulse synthesis. The theoretical phase modulation function required for generating use- specific target-intensity profiles is calculated using different optimization methods including a Brute Force Monte Carlo search, the Simulated Annealing method and the Genetic Algorithm method. The convergence speed, computational complexity and accuracy of these methods is compared under binary phase-only modulation, where the Genetic algorithm was found to outperform other methods.

Hue-Preserving Saturation Improvement in RGB Color Cube

This paper proposes a method for improving saturation in the context of hue-preserving color image enhancement. The proposed method handles colors in an RGB color space, which has the form of a cube, and enhances the contrast of a given image by histogram manipulation, such as histogram equalization and histogram specification, of the intensity image. Then, the color corresponding to a target intensity is determined in a hue-preserving manner, where a gamut problem should be taken into account. We first project any color onto a surface in the RGB color space, which bisects the RGB color cube, to increase the saturation without a gamut problem. Then, we adjust the intensity of the saturation-enhanced color to the target intensity given by the histogram manipulation. The experimental results demonstrate that the proposed method achieves higher saturation than that given by related methods for hue-preserving color image enhancement.

Transcranial focused ultrasound phase correction using the hybrid angular spectrum method

The InSightec Exablate system is the standard of care used for transcranial focused ultrasound ablation treatments in the United States. The system calculates phase corrections that account for aberrations caused by the human skull. This work investigates whether skull aberration correction can be improved by comparing the standard of care InSightec ray tracing method with the hybrid angular spectrum (HAS) method and the gold standard hydrophone method. Three degassed ex vivo human skulls were sonicated with a 670 kHz hemispherical phased array transducer (InSightec Exablate 4000). Phase corrections were calculated using four different methods (straight ray tracing, InSightec ray tracing, HAS, and hydrophone) and were used to drive the transducer. 3D raster scans of the beam profiles were acquired using a hydrophone mounted on a 3-axis positioner system. Focal spots were evaluated using six metrics: pressure at the target, peak pressure, intensity at the target, peak intensity, positioning error, and focal spot volume. For three skulls, the InSightec ray tracing method achieved 52 ± 21% normalized target intensity (normalized to hydrophone), 76 ± 17% normalized peak intensity, and 0.72 ± 0.47 mm positioning error. The HAS method achieved 74 ± 9% normalized target intensity, 81 ± 9% normalized peak intensity, and 0.35 ± 0.09 mm positioning error. The InSightec-to-HAS improvement in focal spot targeting provides promise in improving treatment outcomes. These improvements to skull aberration correction are also highly relevant for the applications of focused ultrasound neuromodulation and blood brain barrier opening, which are currently being translated for human use.

Abstract 12955: A Novel Algorithm for Automated Titration of Autonomic Regulation Therapy for Heart Failure

Background: Autonomic Regulation Therapy (ART) using chronic vagus nerve stimulation (VNS) is a promising new therapy for patients with heart failure who remain symptomatic despite standard care. In the ANTHEM-HF Pilot Study, a therapeutic VNS intensity was successfully achieved in patients with HFrEF using manually programmed VNS up-titration. An algorithm has been developed for automatically intensifying VNS in small increments to a programmable target and capable of adjustments during up-titration process using a hand-held programmer or magnet. Methods: 6 healthy canines were implanted with an implantable pulse generator (IPG) and electrical lead for right cervical VNS. IPG programming at implant activated the TA algorithm with (1) a 1-week start delay; (2) initial stimulation intensity of 0.125 mA, 130 μsec pulse width, and 5 Hz frequency; (3) target stimulation intensity of 2.5 mA, 250 μsec pulse width, and 5 Hz frequency; and (4) trajectory to achieve the target intensity in approximately 10 weeks. Magnet placement over the IPG at scheduled intervals tested algorithm design intention to decrement VNS intensity, prolong the time to reach the target intensity, and/or temporarily inhibit VNS. Results: All animals underwent successful VNS system implantation and completed all scheduled activities. There was one transient implant-related adverse event (Horner’s Syndrome). The TA algorithm performed as designed. The targeted VNS intensity was achieved as scheduled, and automated titration was well tolerated in all animals. There were no stimulation-related adverse events. ECG monitoring demonstrated no clinically significant cardiac findings. Detailed gross necropsy and macroscopic examinations revealed vagus nerves and all major organs to be normal in all animals. Conclusion: An IPG for VNS having a programmable TA algorithm for automatically intensifying VNS to a target intensity and capable of adjustment in response to magnet applications to the IPG, was successfully tested in a preclinical study of healthy canines. The TA algorithm performed as designed, appears to be safe and could dramatically reduce burden of titration in a clinical setting.

An Improved UAV-PHD Filter-Based Trajectory Tracking Algorithm for Multi-UAVs in Future 5G IoT Scenarios

The 5G cellular network is expected to provide core service platform for the expanded Internet of Things (IoT) by supporting enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable low latency communications (URLLC). Unmanned aerial vehicles (UAVs), also known as drones, provide civil, commercial, and government services in various fields. Particularly in a 5G IoT scenario, UAV-aided network communications will fulfill an increasingly important role and will require the tracking of multiple UAV targets. As UAVs move quickly, maintaining the stability of the communication connection in 5G will be a challenge. Therefore, it is necessary to track the trajectory of UAVs. At present, the GM-PHD filter has a problem that the new target intensity must be known, and it cannot obtain the moving target trajectory and the influence of the clutter is likely to cause false alarm. A UAV-PHD filter is proposed in this work to improve the traditional GM-PHD filter by applying machine learning to the emergency detection and trajectory tracking of UAV targets. An out-of-sight detection algorithm for multiple UAVs is then presented to improve tracking performance. The method is assessed by simulation using MATLAB, and OSPA distance is utilized as an evaluation indicator. The simulation results illustrate that the proposed method can be applied to the tracking of multiple UAV targets in future 5G-IoT scenarios, and the performance is superior to the traditional GM-PHD filter.

Evaluation of the Scaling Factor Bias Influence on the Probability of Collapse Using Sa(T1) as the Intensity Measure

Amplitude scaling is a common approach to modify recorded ground motions to achieve a desired intensity level. The possible bias introduced by scaling the amplitude of ground motions when using the first-mode spectral ordinate as the intensity measure is evaluated using intensity-based analyses. This study evaluates whether upward scaling introduces bias in lateral displacement demands, but more importantly, in the probability of collapse. The latter, which is of utmost importance, has received little attention in previous studies. Analyses were conducted using degrading single-degree-of-freedom and multiple-degree-offreedom systems with different fundamental periods of vibration and normalized strengths subjected to different sets of recorded accelerograms requiring different scale factors to reach a target intensity. The results demonstrate that this type of amplitude scaling introduces a bias in which lateral displacement demands and collapse estimates are increasingly overestimated with an increasing scale factor and that the bias is strongly dependent on the period and lateral strength of the system. Furthermore, the bias is considerably larger in collapse risk estimates.

Ratings of Perceived Exertion and Physiological Responses in Children During Exercise

OMNI ratings of perceived exertion (RPE) and physiological responses in children (n=7 boys, 8 girls, 11.1±1.0 years) were examined during estimation (graded exercise test [GXT] and steady-state) and production (steady-state) trials on a cycle ergometer. Peak oxygen consumption (VO2peak) was determined via a GXT with RPE estimated every 30 s. Later, two 6-min trials were completed: Participants 1) estimated RPE at ~75% of VO2peak, 2) produced a level of exertion corresponding to their RPE at ~75% of VO2peak during the GXT. Data analysis included a one-way MANOVA and a paired t-test. The target intensity during the GXT corresponded to 74.2±2.5% of VO2peak; the steady-state estimation and production trials were performed at 76.5±2.7% and 68.5±14.1% of VO2peak, respectively (p>0.05). Mean RPE at ~75% of VO2peak during the GXT and production trial was 6.7±1.5; during the steady-state estimation trial RPE was 5.8±2.0 (p>0.05). There were no differences (p>0.05) in the physiological responses. Participants estimated RPE similarly at ~75% of VO2peak during both graded and steady-state exercise, but when asked to produce a given RPE, marked variability was observed in physiological responses. These findings may have implications in optimizing exercise prescriptions for children.