Identification and analysis of stable breathing periods in electrical impedance tomography recordings.

Objective. In this paper, an automated stable tidal breathing period (STBP) identification method based on processing electrical impedance tomography (EIT) waveforms is proposed and the possibility of detecting and identifying such periods using EIT waveforms is analyzed. In wearable chest EIT, patients breathe spontaneously, and therefore, their breathing pattern might not be stable. Since most of the EIT feature extraction methods are applied to STBPs, this renders their automatic identification of central importance.Approach. The EIT frame sequence is reconstructed from the raw EIT recordings and the raw global impedance waveform (GIW) is computed. Next, the respiratory component of the raw GIW is extracted and processed for the automatic respiratory cycle (breath) extraction and their subsequent grouping into STBPs.Main results. We suggest three criteria for the identification of STBPs, namely, the coefficient of variation of (i) breath tidal volume, (ii) breath duration and (iii) end-expiratory impedance. The total number of true STBPs identified by the proposed method was 294 out of 318 identified by the expert corresponding to accuracy over 90%. Specific activities such as speaking, eating and arm elevation are identified as sources of false positives and their discrimination is discussed.Significance. Simple and computationally efficient STBP detection and identification is a highly desirable component in the EIT processing pipeline. Our study implies that it is feasible, however, the determination of its limits is necessary in order to consider the implementation of more advanced and computationally demanding approaches such as deep learning and fusion with data from other wearable sensors such as accelerometers and microphones.

An Ultrasonographic Multiparametric Carotid Plaque Risk Index Associated with Cerebrovascular Symptomatology: A Study Comparing Color Doppler Imaging and Contrast-Enhanced Ultrasonography.

BACKGROUND AND PURPOSE: Various ultrasonographic features of carortid plaques have been associated with the occurence of stroke, highlighting the need for multi-parametric assessment of plaque's vulnerability. Our aim was to compare ultrasonographic multiparametric indices using color Doppler imaging and contrast-enhanced sonography between symptomatic and asymptomatic carotid plaques. MATERIALS AND METHODS: This was a cross-sectional observational study recruiting 54 patients (72.2% male; median age, 61 years) undergoing sonography and contrast-enhanced sonography. Patients were included if a moderately or severely stenotic internal carotid artery plaque was detected, with the plaque being considered symptomatic if it was ipsilateral to a stroke occuring within the last 6 months. A vulnerability index, previously described by Kanber et al, combined the degree of stenosis, gray-scale median, and a quantitative measure of surface irregularities (surface irregularity index) derived from color Doppler imaging and contrast-enhanced ultrasonography, resulting in 2 vulnerability indices, depending on the surface irregularity index used. Mann-Whitney U and t tests were used to compare variables between groups, and receiver operating characteristic curves were used to compare diagnostic accuracy. RESULTS: Sixty-two plaques were analyzed (50% symptomatic), with a mean degree of stenosis of 68.9%. Symptomatic plaques had a significantly higher degree of stenosis (mean, 74.7% versus 63.1%; P < .001), a lower gray-scale median (13 versus 38; P = .001), and a higher Kanber vulnerability index based both on color Doppler imaging (median, 61.4 versus 16.5; P < .001) and contrast-enhanced ultrasonography (median, 88.6 versus 25.2; P < .001). The area under the curve for the detection of symptomatic plaques was 0.772 for the degree of stenosis alone, 0.783 for the vulnerability index-color Doppler imaging, and 0.802 for the vulnerability index-contrast-enhanced ultrasonography, though no statistical significance was achieved. CONCLUSIONS: Symptomatic plaques had a higher degree of stenosis, lower gray-scale median values, and higher values of the Kanber vulnerability index using both color Doppler imaging and contrast-enhanced ultrasonography for plaque surface delineation.