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.
Corresponding customized software tool is usually unavailable, which increases the time and workload for evaluating the results of a clinical trial. In the present paper, we demonstrate the development process of a customized software for one clinical trial on patients with obstructive lung disease. Over hundred patients and volunteers as controlled were included in the clinical trial. They were examined by spirometry and EIT in a seated position during spontaneous tidal breathing. Subsequently, standard vital capacity maneuver and forced full expiration maneuver were performed. In order to evaluate the offline data, a customized software was developed. The requirements of the software were defined by investigators. The software was then tested on patients’ data and refined based on feedbacks of the investigators. We finalized the customized software with analysis of various disease-specific parameters and indices. Compared to the data process with device specific programs and other commercial software, the customized software is more flexible, user-friendly and extendable. As conclusion, customized software simplifies the evaluation process distinctly and helps physicians to focus on study design and result interpretation.
Successful embolectomy of the superior mesenteric artery in a 75-year-old man is reported. The decisive points in early diagnosis are discussed and the specific diagnostic methods for the correct decision are presented. The fulminant evolution of the disease leaves little time in which to decide. Early embolectomy brings about complete cure. It is a life-saving operation and there are no contraindications.
Dispersion of refractoriness may contribute to the propensity for reentrant arrhythmias. This study was performed to assess the effect of sotalol on the dispersion of refractoriness in experimental myocardial infarction. In 9 mongrel dogs, 14 days after induction of myocardial infarction by an occlusion reperfusion technique, programmed ventricular stimulation and epicardial mapping were performed before and during (3 mg/kg + 0.5 mg/kg per hour) sotalol administration. To assess the spatial distribution of refractoriness, ventricular fibrillation (VF) intervals were analyzed. The rationale for this method is that, during VF, when multiple reentrant wavelets are present, cells are excited as soon as they recover from previous activation. The coefficient of variation (standard deviation × 100) served as an index of spatial distribution of refractoriness. Results : VF was induced before sotalol in 7 dogs and in 5 of 7 during sotalol administration. The mean value of the index VF intervals decreased from 19.8 ± 2.3 at baseline to 15.8 ± 2.6 during sotalol (P = 0.011), indicating a more homogeneous distribution of refractoriness. Thus, the antiarrhythmic effects of sotalol may be mediated by its action on the dispersion of refractoriness.
This paper presents a wearable sensor architecture for frequency-multiplexed electrical impedance tomography (EIT) and synchronous multilead electrocardiogram (ECG) data acquisition. The system is based on a novel electronic sensing architecture, called cooperative sensors, that significantly reduces the cabling complexity and enables flexible EIT stimulation and measurement patterns. The cooperative-sensor architecture was initially designed for ECG and has been extended for multichannel bioimpedance measurement. This approach allows for an adjustable EIT stimulation pattern via frequency-division multiplexing. This paper also shows a calibration procedure as well as EIT system noise performance assessment. Preliminary measurements on a healthy volunteer showed the ability of the wearable system to measure EIT data synchronously with multilead ECG. Ventilation-related and heartbeat-related EIT images were reconstructed, demonstrating the feasibility of the proposed architecture for noninvasive cardiovascular monitoring.
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