Fernando S. Schlindwein

Application of wavelets in Doppler ultrasound

Provides an introduction into wavelets and illustrates their application with two examples. The wavelet transform provides the analyst with a scaleable time‐frequency representation of the signal, which may uncover details not evidenced by conventional signal processing techniques. The signals used in this paper are Doppler ultrasound recordings of blood flow velocity taken from the internal carotid artery and the femoral artery. Shows how wavelets can be used as an alternative signal processing tool to the short time Fourier transform for the extraction of the time‐frequency distribution of Doppler ultrasound signals. Implements wavelet‐based adaptive filtering for the extraction of maximum blood velocity envelopes in the post processing of Doppler signals.

A real-time autoregressive spectrum analyzer for Doppler ultrasound signals

A system based on a digital signal processor and a microcomputer has been programmed to estimate the maximum entropy autoregressive (AR) power spectrum of ultrasonic Doppler shift signals and display the results in the form of a sonogram in real-time on a computer screen. The system, which is based on a TMS 320C25 digital signal processor chip, calculates spectra with 128 frequency components from 64 samples of the Doppler signal. The samples are collected at a programmable rate of up to 40.96 kHz, and the computation of each spectrum takes typically 3.2 ms. The feasibility of on-line AR spectral estimation makes this type of analysis an attractive alternative to the more conventional fast Fourier transform approach to the analysis of Doppler ultrasound signals.

The relationship between time averaged intensity weighted mean velocity, and time averaged maximum velocity in neonatal cerebral arteries

It is usual practice to calculate the mean velocity of blood flow in neonatal cerebral vessels from the intensity weighted mean (IWM) Doppler shift signal. Theoretically however the maximum frequency envelope could be used for similar purposes, and indeed may have certain advantages. The purpose of this study was to confirm the suitability of the maximum frequency method. Good quality Doppler recordings from the anterior cerebral and middle cerebral arteries of both term and very low birth weight babies were analyzed by both methods and compared. A small number of recordings were then deliberately degraded, either by the addition of noise or by the use of inappropriate filters, and reanalyzed. The results of these comparisons suggest that the maximum frequency follower should be the follower of choice for neonatal cerebral blood flow studies.

Spectral broadening of clinical Doppler signals using FFT and autoregressive modelling.

OBJECTIVE This paper investigates the behaviour of the spectral broadening index (SBI) derived from spectra obtained using autoregressive (AR) modelling compared to that of SBI based on fast Fourier transform (FFT) analysis of clinical Doppler ultrasound scans. METHODS Doppler signals from internal carotid arteries of patients with normal and diseased vessels with up to 80% stenosis were analysed. A threshold at -6 dB of the maximum magnitude component of each individual spectrum was implemented to reject low-level noise. The SBI was obtained using the maximum and the mean frequency envelopes extracted from the sonogram. RESULTS A qualitative improvement in both the appearance of the AR sonograms and the shape of the individual AR spectra was noticeable. The AR approach consistently produced narrower spectra than the FFT and the shapes of the frequency envelopes derived from the AR sonogram and the FFT sonogram were also rather different. Despite these differences a strong correlation was observed between the value of the FFT-based SBI and the AR-based SBI. The mean value of the FFT-SBI is larger than that of the AR-SBI and the variance of the FFT-SBI is smaller than that of the AR-SBI based on a set of at least 20 sequentially recorded heartbeats. CONCLUSIONS It was established that, for all cases where significant stenosis was present, a statistically significant value for SBI could be obtained using four or more heartbeats if five spectra around the peak systole were used to estimate the SBI of each individual heartbeat. No quantitative advantage in using the AR approach over the FFT for the determination of SBI was obtained due to the poorer variance of the AR-SBI and the additional computational complexity of the AR approach.

A study of the spectral broadening of simulated Doppler signals using FFT and AR modelling

Doppler ultrasound is used clinically to detect stenosis in the carotid artery. The presence of stenosis may be identified by disturbed flow patterns distal to the stenosis that cause spectral broadening in the spectrum of the Doppler signal around peak systole. This paper investigates the behaviour of the spectral broadening index (SBI) derived from wide-band spectra obtained using autoregressive modelling (AR), compared with the SBI based on the fast-Fourier transform (FFT) spectra. Simulated Doppler signals were created using white noise and shaped filters to analyse spectra typically found around the systolic peak and to assess the magnitude and variance of AR and FFT-SBI for a range of signal-to-noise ratios. The results of the analysis show a strong correlation between the indices calculated using the FFT and AR algorithms. Despite the qualitative improvement of the AR spectra over the FFT, the estimation of SBI for short data frames is not significantly improved using AR.

Direct inversion of the apparent complex-resistivity spectrum

Cole‐Cole model parameters are widely used to interpret electrical geophysical methods and are obtained by inverting the induced polarization (IP) spectrum. This paper presents a direct inversion method for parameter estimation based on multifold least-squares estimation. Two algorithms are described that provide optimal parameter estimation in the least-squares sense. Simulations demonstrate that both algorithms can provide direct apparent spectral parameter inversion for complex resistivity data. Moreover, the second algorithm is robust under reasonably high noise.

Comparison of integrated micro-electrical-mechanical system and piezoelectric accelerometers for machine condition monitoring

Abstract The design and implementation of instrumentation to collect real-time vibrational data from a quasi-steady state machine (a dry vacuum pump) for fault prediction diagnostics is presented. When simultaneous multiple data collection points are required on the same machinery, the use of conventional transducers such as piezoelectric accelerometers becomes impractical due to their price, as each needs an expensive associated charge amplifier. The use of inexpensive micromachined integrated micro-electrical-mechanical system accelerometers such as ADXL105 has been explored here as an alternative to piezoelectric accelerometers for obtaining reliable and predictable data for diagnostics. Surface micromachined accelerometers are a new technology and their usage for vibrational analysis has been conservative due to concerns over increased noise levels and tolerance to high temperatures. In this article, it is shown that such concerns can be allayed. The time and frequency domain vibration signatures obtained using both types of accelerometers are compared. The study shows that ADXL105 accelerometers can be an effective alternative low-cost high-quality solution for machine condition monitoring.

Detection of asphyxia using heart rate variability

The long-term aims of this study are to find a parameter derived from the ECG that has a high sensitivity and specificity to asphyxia and, once we know or suspect that asphyxia occurred, to estimate how severe it was. We carried out a pilot study in which 24 adult Wistar rats were anaesthetised and subjected to controlled asphyxia for specified durations. We measured the pH, ‘neurological score’ and the ECG, extracting from this heart rate and heart rate variability (HRV). We have developed a technique capable of detecting asphyxia in less than 1 min, based on monitoring the ECG and estimating HRV by measuring the standard deviation of normal RR intervals (the RR interval is the time interval between two consecutive R-points of the QRS complex). In all cases the heart rate decreased and HRV increased, by an average of 46±33ms in relation to the baseline, at the onset of asphyxia. The comparison of the base level of HRV after and before asphyxia shows promise for the estimation of the severity of the episode; however, the limitations of this study should be noted as they include the small size of the cohort and the methods of analysis.

Distinctive Patterns of Dominant Frequency Trajectory Behavior in Drug-Refractory Persistent Atrial Fibrillation: Preliminary Characterization of Spatiotemporal Instability

The role of substrates in the maintenance of persistent atrial fibrillation (persAF) remains poorly understood. The use of dominant frequency (DF) mapping to guide catheter ablation has been proposed as a potential strategy, but the characteristics of high DF sites have not been extensively studied. This study aimed to assess the DF spatiotemporal stability using high density noncontact mapping (NCM) in persAF.

Prospective evaluation of two novel ECG-based restitution biomarkers for prediction of sudden cardiac death risk in ischaemic cardiomyopathy

Objective To improve prediction of sudden cardiac death (SCD) in patients with ischaemic cardiomyopathy (ICM). Electrical heterogeneity is known to contribute to risk of SCD. We have previously developed Regional Restitution Instability Index (R2I2), an ECG-based biomarker, which quantifies cardiac electrical instability by measuring heterogeneity in electrical restitution, and demonstrated its potential utility for risk stratification in a retrospective analysis of patients with ICM. Here, we examined R2I2 in a prospective ICM cohort and also tested the predictive value of another ECG-based biomarker, Peak ECG Restitution Slope (PERS). Methods Prospective, blinded, observational study of 60 patients with ICM undergoing implantable cardioverter defibrillator risk stratification. R2I2 was calculated from an electrophysiological study (EPS) using ECG surrogates for action potential duration and diastolic interval. R2I2 quantifies inter-lead electrical restitution heterogeneity. PERS was the peak restitution curve slope taken as a mean across the 12 ECG leads. Endpoints were ventricular arrhythmia (VA)/SCD. Results Over median follow-up of 22 months, 16 (26.6%) patients achieved endpoint. R2I2 was significantly higher in these patients compared with those without an event (mean±SEM: 1.11±0.09 vs 0.84±0.04, p=0.003) as was PERS (median(IQR): 1.35(0.60) vs 1.08(0.52), p=0.014). R2I2≥1.03, the cut-off used in our previous study, identified patients with a significantly higher risk of VA/SCD independent of EPS result, LVEF or QRS duration with a relative risk of 6.5 (p=0.008). Patients positive for R2I2 and PERS had a relative risk of VA/SCD 21.6 times that of those negative for R2I2 and PERS (p<0.0001). Conclusions R2I2 and PERS each independently and in combination, identify patients with ICM that are at high risk of developing ventricular arrhythmias (VA). R2I2/PERS represent promising risk markers for SCD discrimination. Trial registration number ClinicalTrials.gov Identifier: NCT01944514.