Automated edge-detection technique for measurement of brachial artery reactivity: A comparison of concordance with manual measurements

Concerns have been raised about the reproducibility of brachial artery reactivity (BAR), because subjective decisions regarding the location of interfaces may influence the measurement of very small changes in lumen diameter. We studied 120 consecutive patients with BAR to address if an automated technique could be applied, and if experience influenced reproducibility between two observers, one experienced and one inexperienced. Digital cineloops were measured automatically, using software that measures the leading edge of the endothelium and tracks this in sequential frames and also manually, where a set of three point-to-point measurements were averaged. There was a high correlation between automated and manual techniques for both observers, although less variability was present with expert readers. The limits of agreement overall for interobserver concordance were 0.13 +/-0.65 mm for the manual and 0.03 +/-0.74 mm for the automated measurement. For intraobserver concordance, the limits of agreement were -0.07 +/-0.38 mm for observer 1 and -0.16 +/-0.55 mm for observer 2. We concluded that BAR measurements were highly concordant between observers, although more concordant using the automated method, and that experience does affect concordance. Care must be taken to ensure that the same segments are measured between observers and serially.

Seizure detection algorithm for neonates based on wave-sequence analysis

Objective: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. Methods: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. Results: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30 s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. Conclusions: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. Significance: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring. Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

Time-Frequency Distribution Moments of Heart Rate Variability for Neonatal Seizure Detection

In this paper, we propose features extracted from the heart rate variability (HRV) based on the first and second conditional moments of time-frequency distribution (TFD) as an additional guide for seizure detection in newborn. The features of HRV in the low frequency band (LF: 0-0.07 Hz), mid frequency band (MF: 0.07-0.15 Hz), and high frequency band (HF: 0.15-0.6 Hz) have been obtained by means of the time-frequency analysis using the modified-B distribution (MBD). Results of ongoing time-frequency research are presented. Based on our preliminary results, the first conditional moment of HRV which is also known as the mean/central frequency in the LF band and the second conditional moment of HRV which is also known as the variance/instantaneous bandwidth (IB) in the HF band can be used as a good feature to discriminate the newborn seizure from the non-seizure

A Nonstationary Model of Newborn EEG

The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).

Development of a fully quantitative approach to the interpretation of stress echocardiography using radial and longitudinal myocardial velocities

Background: Tissue Doppler may be used to quantify regional left ventricular function but is limited by segmental variation of longitudinal velocity from base to apex and free to septal walls. We sought to overcome this by developing a composite of longitudinal and radial velocities. Methods and Results. We examined 82 unselected patients undergoing a standard dobutamine echocardiogram. Longitudinal velocity was obtained in the basal and mid segments of each wall using tissue Doppler in the apical views. Radial velocities were derived in the same segments using an automated border detection system and centerline method with regional chords grouped according to segment location and temporally averaged. In 25 patients at low probability of coronary disease, the pattern of regional variation in longitudinal velocity (higher in the septum) was the opposite of radial velocity (higher in the free wall) and the combination was homogenous. In 57 patients undergoing angiography, velocity in abnormal segments was less than normal segments using longitudinal (6.0 +/- 3.6 vs 9.0 +/- 2.2 cm/s, P = .01) and radial velocity (6.0 +/- 4.0 vs 8.0 +/- 3.9 cm/s, P = .02). However, the composite velocity permitted better separation of abnormal and normal segments (13.3 +/- 5.6 vs 17.5 +/- 4.2 cm/s, P = .001). There was no significant difference between the accuracy of this quantitative approach and expert visual wall motion analysis (81% vs 84%, P = .56). Conclusion: Regional variation of uni-dimensional myocardial velocities necessitates site-specific normal ranges, probably because of different fiber directions. Combined analysis of longitudinal and radial velocities allows the derivation of a composite velocity, which is homogenous in all segments and may allow better separation of normal and abnormal myocardium.

Comparison between real-time three-dimensional echocardiography, T1-201 single photon emission computed tomography and cardiac magnetic resonance imaging in the quantitative assessment of left ventricular volumes

Left ventricular (LV) volumes have important prognostic implications in patients with chronic ischemic heart disease. We sought to examine the accuracy and reproducibility of real-time 3D echo (RT-3DE) compared to TI-201 single photon emission computed tomography (SPECT) and cardiac magnetic resonance imaging (MRI). Thirty (n = 30) patients (age 62±9 years, 23 men) with chronic ischemic heart disease underwent LV volume assessment with RT-3DE, SPECT, and MRI. Ano vel semi-automated border detection algorithmwas used by RT-3DE. End diastolic volumes (EDV) and end systolic volumes (ESV) measured by RT3DE and SPECT were compared to MRI as the standard of reference. RT-3DE and SPECT volumes showed excellent correlation with MRI (Table). Both RT- 3DE and SPECT underestimated LV volumes compared to MRI (ESV, SPECT 74±58 ml versus RT-3DE 95±48 ml versus MRI 96±54 ml); (EDV, SPECT 121±61 ml versus RT-3DE 169±61 ml versus MRI 179±56 ml). The degree of ESV underestimation with RT-3DE was not significant.

Automated regional myocardial displacement for facilitating the interpretation of dobutamine echocardiography

Quantification of stress echocardiography may overcome the training requirements and subjective nature of visual wall motion score (WMS) assessment, but quantitative approaches may be difficult to apply and require significant time for image processing. The integral of long-axis myocardial velocity is displacement, which may be represented as a color map over the left ventricular myocardium. This study was designed to explore the feasibility and accuracy of measuring long-axis myocardial displacement, derived from tissue Doppler, for the detection of coronary artery disease (CAD) during dobutamine stress echocardiography (DBE). One hundred thirty patients underwent standard DBE, including 30 patients at low risk of CAD, 30 patients with normal coronary angiography (both groups studied to define normal ranges of displacement), and 70 patients who underwent coronary angiography in whom the accuracy of normal ranges was tested. Regional myocardial displacement was obtained by analysis of color tissue Doppler apical images acquired at peak stress. Displacement was compared with WMS, and with the presence of CAD by angiography. The analysis time was 3.2 +/- 1.5 minutes per patient. Segmental displacement was correlated with wall motion (normal 7.4 +/- 3.2 mm, ischemia 5.8 +/- 4.2 mm, viability 4.6 +/- 3.0 mm, scar 4.5 +/- 3.5 mm, p <0.001). Reversal of normal base-apex displacement was an insensitive (19%) but specific (90%) marker of CAD. The sum of displacements within each vascular territory had a sensitivity and specificity of 89% and 79%, respectively, for prediction of significant CAD, compared with 86% and 78%, respectively, for WMS (p = NS). The displacements in the basal segments had a sensitivity and specificity of 83% and 78%, respectively (p = NS). Regional myocardial displacement during DBE is feasible and offers a fast and accurate method for the diagnosis of CAD. (C),2002 by Excerpta Medica, Inc.

Automated Analysis of the Auditory Brainstem Response Using Derivative Estimation Wavelets

In this paper, we describe an algorithm that automatically detects and labels peaks I - VII of the normal, suprathreshold auditory brainstem response (ABR). The algorithm proceeds in three stages, with the option of a fourth: ( 1) all candidate peaks and troughs in the ABR waveform are identified using zero crossings of the first derivative, ( 2) peaks I - VII are identified from these candidate peaks based on their latency and morphology, ( 3) if required, peaks II and IV are identified as points of inflection using zero crossings of the second derivative and ( 4) interpeak troughs are identified before peak latencies and amplitudes are measured. The performance of the algorithm was estimated on a set of 240 normal ABR waveforms recorded using a stimulus intensity of 90 dBnHL. When compared to an expert audiologist, the algorithm correctly identified the major ABR peaks ( I, III and V) in 96 - 98% of the waveforms and the minor ABR peaks ( II, IV, VI and VII) in 45 - 83% of waveforms. Whilst peak II was correctly identified in only 83% and peak IV in 77% of waveforms, it was shown that 5% of the peak II identifications and 31% of the peak IV identifications came as a direct result of allowing these peaks to be found as points of inflection. Copyright (C) 2005 S. Karger AG, Basel.

Foetal malformations and seizure control: 52 months data of the Australian Pregnancy Registry

The Australian Pregnancy Registry, affiliated European Register of Antiepileptic drugs in Pregnancy (EURAP), recruits informed consenting women with epilepsy on treatment with antiepileptic drugs (AEDs), those untreated, and women on AEDs for other indications. Enrolment is considered prospective if it has occurred before presence or absence of major foetal malformations (FMs) are known, or retrospective, if they had occurred after the birth of infant or detection of major FM. Telephone Interviews are conducted to ascertain pregnancy outcome and collect data about seizures. To date 630 women have been enrolled, with 565 known pregnancy outcomes. Valproate (VPA) above 1100 mg/day was associated with a significantly higher incidence of FMs than other AEDs (P < 0.05). This was independent of other AED use or potentially confounding factors on multivariate analysis (OR = 7.3, P < 0.0001). Lamotrigine (LTG) monotherapy (n = 65), has so far been free of malformations. Although seizure control was not a primary outcome, we noted that more patients on LTG than on VPA required dose adjustments to control seizures. Data indicate an increased risk of FM in women taking VPA in doses > 1100 mg/day compared with other AEDs. The choice of AED for pregnant women with epilepsy requires assessment of balance of risks between teratogenicity and seizure control.

Computational methods for the detection of facial palsy

We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P

DR-NEGOTIATE - A system for automated agent negotiation with defeasible logic-based strategies

This paper reports on a system for automated agent negotiation, based on a formal and executable approach to capture the behavior of parties involved in a negotiation. It uses the JADE agent framework, and its major distinctive feature is the use of declarative negotiation strategies. The negotiation strategies are expressed in a declarative rules language, defeasible logic, and are applied using the implemented system DR-DEVICE. The key ideas and the overall system architecture are described, and a particular negotiation case is presented in detail.