Automatic Max-Likelihood Envelope Detection Algorithm for Quantitative High-Frame-Rate Ultrasound for Neonatal Brain Monitoring.

OBJECTIVE: Post-operative brain injury in neonates may result from disturbed cerebral perfusion, but accurate peri-operative monitoring is lacking. High-frame-rate (HFR) cerebral ultrasound could visualize and quantify flow in all detectable vessels using spectral Doppler; however, automated quantification in small vessels is challenging because of low signal amplitude. We have developed an automatic envelope detection algorithm for HFR pulsed wave spectral Doppler signals, enabling neonatal brain quantitative parameter maps during and after surgery. METHODS: HFR ultrasound data from high-risk neonatal surgeries were recorded with a custom HFR mode (frame rate = 1000 Hz) on a Zonare ZS3 system. A pulsed wave Doppler spectrogram was calculated for each pixel containing blood flow in the image, and spectral peak velocity was tracked using a max-likelihood estimation algorithm of signal and noise regions in the spectrogram, where the most likely cross-over point marks the blood flow velocity. The resulting peak systolic velocity (PSV), end-diastolic velocity (EDV) and resistivity index (RI) were compared with other detection schemes, manual tracking and RIs from regular pulsed wave Doppler measurements in 10 neonates. RESULTS: Envelope detection was successful in both high- and low-quality arterial and venous flow spectrograms. Our technique had the lowest root mean square error for EDV, PSV and RI (0.46 cm/s, 0.53 cm/s and 0.15, respectively) when compared with manual tracking. There was good agreement between the clinical pulsed wave Doppler RI and HFR measurement with a mean difference of 0.07. CONCLUSION: The max-likelihood algorithm is a promising approach to accurate, automated cerebral blood flow monitoring with HFR imaging in neonates.

Heart rate estimation and validation algorithm for fetal phonocardiography.

Objective.Fetal heart rate (FHR) is an important parameter for assessing fetal well-being and is usually measured by doppler ultrasound. Fetal phonocardiography can provide non-invasive, easy-to-use and passive alternative for fetal monitoring method if reliable FHR measurements can be made even in noisy clinical environments. Therefore, this work presents an automatic algorithm to determine FHR from the fetal heart sound recordings in a noisy clinical environment.Approach.Using an electronic stethoscope fetal heart sounds were recorded from the expecting mother's abdomen, during weeks 30-40 of their pregnancy. Of these, 60 recordings were analyzed manually by two observers to obtain reference heart rate measurement. An algorithm was developed to determine FHR using envelope detection and autocorrelation of the signals. Algorithm performance was improved by implementing peak validation algorithm utilizing knowledge of valid FHR from prior windows and power spectral density function. The improvements in accuracy and reliability of algorithm were measured by mean absolute error (MAE) and positive percent agreement.Main results.By including the validation step, the MAE reduced from 11.50 to 7.54 beats per minute and positive percent agreement improved from 81% to 87%.Significance.We classified the recordings into good, moderate and poor quality to understand how the algorithm works in each of the case. The proposed algorithms provide good accuracy overall but are sensitive to the noises in recording environment that influence the quality of the signals.

Digital drugs (binaural beats): how can it affect the brain/their impact on the brain.

To understand the principal functioning of binaural beats signals and the way it can affect the brain, eight drugs were used. This study was carried out on three groups: the first one contains four binaural beats signals, each one refers to a specific tone: alpha, beta, theta, and delta waves. The second group holds three records, representing three separate meditation binaural beats; however, the third one contains only one record that stands for the Marijuana e-drugs. Two types of analyses were performed on these groups, the temporal and the frequency analyses. In the first one, Hilbert transform was used to detect the envelope of the signal; we then determined the cross correlation function to understand the relationship between the two signals of the left and the right ears. However, in the frequency analysis, Fast Fourier Transform (FFT) was applied to extract binaural and carrier frequencies. The obtained results are very satisfactory and show that there is a delay between the two signals of the left and the right ears. Nevertheless, the frequency analysis shows that in the second group, Solfeggio frequencies lambda, theta and delta waves are used to obtain the meditation state, were gamma, lambda, alpha, and delta waves are applied to get the Marijuana effect in the third group.

Performance Analysis of Surface Reconstruction Algorithms in Vertical Scanning Interferometry Based on Coherence Envelope Detection.

Optical interferometry plays an important role in the topographical surface measurement and characterization in precision/ultra-precision manufacturing. An appropriate surface reconstruction algorithm is essential in obtaining accurate topography information from the digitized interferograms. However, the performance of a surface reconstruction algorithm in interferometric measurements is influenced by environmental disturbances and system noise. This paper presents a comparative analysis of three algorithms commonly used for coherence envelope detection in vertical scanning interferometry, including the centroid method, fast Fourier transform (FFT), and Hilbert transform (HT). Numerical analysis and experimental studies were carried out to evaluate the performance of different envelope detection algorithms in terms of measurement accuracy, speed, and noise resistance. Step height standards were measured using a developed interferometer and the step profiles were reconstructed by different algorithms. The results show that the centroid method has a higher measurement speed than the FFT and HT methods, but it can only provide acceptable measurement accuracy at a low noise level. The FFT and HT methods outperform the centroid method in terms of noise immunity and measurement accuracy. Even if the FFT and HT methods provide similar measurement accuracy, the HT method has a superior measurement speed compared to the FFT method.

Vital-Signs Detector Based on Frequency-Shift Keying Radar.

A frequency-shift keying (FSK) radar in the 2.45-GHz band is proposed for highly accurate vital-signs detection. The measurement accuracy of the proposed detector for the heartbeat is increased by using the cross-correlation between the phase differences of signals at two frequencies used by the FSK radar, which alternately transmits and receives the signals with different frequencies. Two frequencies-2.45 and 2.5 GHz-are effectively discriminated by using the envelope detection with the frequency control signal of the signal generator in the output waveform of the FSK radar. The phase difference between transmitted and received signals at each frequency is determined after calibrating the I / Q imbalance and direct-current offset using a data-based imbalance compensation algorithm, the Gram-Schmidt procedure, and the Pratt method. The absolute-distance measurement results for a human being show that the vital signs obtained at each frequency using the proposed FSK radar have a cross-correlation. The heartbeat detection results for the proposed FSK radar at a distance of < 2.4 m indicate a reduction in the error rate and an increase in the signal-to-noise ratio compared with those obtained using a single operating frequency.

Model-based beamforming with plane wave synthesis in medical ultrasound.

We are interested in examining how our model-based beamforming algorithm, referred to as aperture-domain model image reconstruction (ADMIRE), performs on plane wave sequences in conjunction with synthetic aperture beamforming. We also aim to identify the impact of ADMIRE applied before and after synthetic focusing. We employed simulated phantoms using Field II and tissue-mimicking phantoms to evaluate ADMIRE as applied to synthetic sequencing. We generated plane wave images with and without synthetic aperture focusing (SAF) and measured contrast and contrast-to-noise ratio (CNR). For simulated cyst images formed from single plane waves, the contrast for delay-and-sum (DAS) and ADMIRE are 15.64 and 28.34 dB, respectively, whereas the CNR are 1.76 and 3.90 dB, respectively. We also applied ADMIRE to simulated resolution phantoms having a point target at 3 cm depth on-axis. We simulated the point spread functions from data obtained from 1 plane wave and 75 steered plane waves, along with linear scans with 3 and 4 cm- focal depths. We then compared the outcome of applying ADMIRE before and after SAF using 3 and 11 steered plane waves. Finally, we applied this to an in vivo carotid artery. Based on the findings in this study, ADMIRE can be adapted to full field insonification sequences to improve image quality in plane wave imaging. Additionally, we investigated how robustly ADMIRE performs in the presence of random noise. We then address identified limitations using a conventional envelope detection method with decluttered signals.

Modeling and FPGA-based implementation of an efficient and simple envelope detector using a Hilbert Transform FIR filter for ultrasound imaging applications

Abstract Introduction Although the envelope detection is a widely used method in medical ultrasound (US) imaging to demodulate the amplitude of the received echo signal before any back-end processing, novel hardware-based approaches have been proposed for reducing its computational cost and complexity. In this paper, we present the modeling and FPGA implementation of an efficient envelope detector based on a Hilbert Transform (HT) approximation for US imaging applications. Method The proposed model exploits both the symmetry and the alternating zero-valued coefficients of a HT finite impulse response (FIR) filter to generate the in-phase and quadrature components that are necessary for the envelope computation. The hardware design was synthesized for a Stratix IV FPGA, by using the Simulink and the integrated DSP Builder toolbox, and implemented on a Terasic DE4-230 board. The accuracy of our algorithm was evaluated by the normalized root mean square error (NRMSE) cost function in comparison with the conventional method based on the absolute value of the discrete-time analytic signal via FFT. Results An excellent agreement was achieved between the theoretical simulations with the experimental result. The NRMSE was 0.42% and the overall FPGA utilization was less than 1.5%. Additionally, the proposed envelope detector is capable of generating envelope data at every FPGA clock cycle after 19 (0.48 µs) cycles of latency. Conclusion The presented results corroborate the simplicity, flexibility and efficiency of our model for generating US envelope data in real-time, while reducing the hardware cost by up to 75%.