Explore the vast range of titles available.

Background Phase-rectified signal averaging (PRSA) was often applied to assess the cardiac vagal modulation. Despite its broad use, this method suffers from the confounding effects of anomalous variants of sinus rhythm. This study aimed to improve the original PRSA method in deceleration capacity (DC) quantification. Methods The refined deceleration capacity ( DC ref ) was calculated by excluding from non-vagally mediated abnormal variants of sinus rhythms. Holter recordings from 202 healthy subjects and 51 patients with end-stage renal disease (ESRD) have been used for validity. The DC ref was compared to original DC ( DC org ) by the area under receiver operating characteristic curve. Results Experimental results demonstrate that the original and refined DC s calculated from 24-h, 2-h, and 30-min Holter recordings are significantly lower in patients with ESRD than those in the healthy group. In receiver operating characteristic curve analysis, the DC ref provides better performance than the DC org in distinguishing between the patients with ESRD and healthy control subjects. Furthermore, the refined PRSA technique enhances the low frequency and attenuates high frequency components for spectral analysis in ESRD patients. Conclusions The DC ref appears to reduce the influence of non-vagally mediated abnormal variants of sinus rhythm and highlighting the pathological influence. DC ref , especially assessed from short-term electrocardiography recordings, may be complementary to existing autonomic function assessment, risk stratification, and efficacy prediction strategies.

In this paper, we continue a topic of modeling measuring processes by perceiving them as a kind of signal sampling. And, in this respect, note that an ideal model was developed in a previous work. Whereas here, we present its nonideal version. This extended model takes into account an effect, which is called averaging of a measured signal. And, we show here that it is similar to smearing of signal samples arising in nonideal signal sampling. Furthermore, we demonstrate in this paper that signal averaging and signal smearing mean principally the same, under the conditions given. So, they can be modeled in the same way. A thorough analysis of errors related to the signal averaging in a measuring process is given and illustrated with equivalent schemes of the relationships derived. Furthermore, the results obtained are compared with the corresponding ones that were achieved analyzing amplitude quantization effects of sampled signals used in digital techniques. Also, we show here that modeling of errors related to signal averaging through the so-called quantization noise, assumed to be a uniform distributed random signal, is rather a bad choice. In this paper, an upper bound for the above error is derived. Moreover, conditions for occurrence of hidden aliasing effects in a measured signal are given.

Theoretical expressions describing the signal of an intermodal fiber interferometer are presented. Two methods of signal averaging are investigated theoretically: the ensemble averaging and the averaging over a \"long realization\". The methods are examined by conducting numerical experiments. The averaging efficiency is analyzed depending on number of realizations and the fiber length increment.

Nuclear magnetic resonance (NMR) is a fundamental spectroscopic technique for the study of biological systems and materials, molecular imaging and the analysis of small molecules. It detects interactions at very low energies and is thus non-invasive and applicable to a variety of targets, including animals and humans. However, one of its most severe limitations is its low sensitivity, which stems from the small interaction energies involved. Here, we report that dynamic nuclear polarization in liquid solution and at room temperature can enhance the NMR signal of 13 C nuclei by up to three orders of magnitude at magnetic fields of ∼3 T. The experiment can be repeated within seconds for signal averaging, without interfering with the sample magnetic homogeneity. The method is therefore compatible with the conditions required for high-resolution NMR. Enhancement of 13 C signals on various organic compounds opens up new perspectives for dynamic nuclear polarization as a general tool to increase the sensitivity of liquid NMR. The analysis of complex (bio)molecules by NMR spectroscopy is often complicated by limitations in sensitivity. Now, it has been shown that 13 C NMR signals are strongly enhanced in solution by resonant microwave irradiation of a nitroxide polarizer. This method exhibits up to one-thousand-fold improvements in sensitivity, which stands to greatly improve the detail with which small molecules and metabolites can be studied.

The aim of this paper is to propose and evaluate the novel method of template generation, matching, comparing and visualization applied to motion capture (kinematic) analysis. To evaluate our approach, we have used motion capture recordings (MoCap) of two highly-skilled black belt karate athletes consisting of 560 recordings of various karate techniques acquired with wearable sensors. We have evaluated the quality of generated templates; we have validated the matching algorithm that calculates similarities and differences between various MoCap data; and we have examined visualizations of important differences and similarities between MoCap data. We have concluded that our algorithms works the best when we are dealing with relatively short (2–4 s) actions that might be averaged and aligned with the dynamic time warping framework. In practice, the methodology is designed to optimize the performance of some full body techniques performed in various sport disciplines, for example combat sports and martial arts. We can also use this approach to generate templates or to compare the correct performance of techniques between various top sportsmen in order to generate a knowledge base of reference MoCap videos. The motion template generated by our method can be used for action recognition purposes. We have used the DTW classifier with angle-based features to classify various karate kicks. We have performed leave-one-out action recognition for the Shorin-ryu and Oyama karate master separately. In this case, 100 % actions were correctly classified. In another experiment, we used templates generated from Oyama master recordings to classify Shorin-ryu master recordings and vice versa. In this experiment, the overall recognition rate was 94.2 % , which is a very good result for this type of complex action.

The human central nervous system is the integrative basis for the functioning of the organism. The basis of such integration is provided by the fact that the same neurons are involved in various sets of sensory, cognitive, and motor functions. Therefore, the analysis of one set of integrative system components makes it possible to draw conclusions about the state and efficiency of the other components. Thus, to evaluate a person’s cognitive properties, we can assess their involuntary motor acts, i.e., a person’s subsensory reactions. To measure the parameters of involuntary motor acts, we have developed a strain gauge measuring system. This system provides measurement and estimation of the parameters of involuntary movements against the background of voluntary isometric efforts. The article presents the architecture of the system and shows the organization of the primary signal processing in analog form, in particular the separation of the signal taken from the strain-gauge sensor into frequency and smoothly varying components by averaging and subtracting the analog signals. This transfer to analog form simplifies the implementation of the digital part of the measuring system and allowed for minimizing the response time of the system while displaying the isometric forces in the visual feedback channel. The article describes the realization of the system elements and shows the results of its experimental research.

Impedance cardiography (ICG) is a low-cost, non-invasive technique that enables the clinical assessment of haemodynamic parameters, such as cardiac output and stroke volume (SV). Conventional ICG recordings are taken from the patient’s thorax. However, access to ICG vital signs from the upper-arm brachial artery (as an associated surrogate) can enable user-convenient wearable armband sensor devices to provide an attractive option for gathering ICG trend-based indicators of general health, which offers particular advantages in ambulatory long-term monitoring settings. This study considered the upper arm ICG and control Thorax-ICG recordings data from 15 healthy subject cases. A prefiltering stage included a third-order Savitzky–Golay finite impulse response (FIR) filter, which was applied to the raw ICG signals. Then, a multi-stage wavelet-based denoising strategy on a beat-by-beat (BbyB) basis, which was supported by a recursive signal-averaging optimal thresholding adaptation algorithm for Arm-ICG signals, was investigated for robust signal quality enhancement. The performance of the BbyB ICG denoising was evaluated for each case using a 700 ms frame centred on the heartbeat ICG pulse. This frame was extracted from a 600-beat ensemble signal-averaged ICG and was used as the noiseless signal reference vector (gold standard frame). Furthermore, in each subject case, enhanced Arm-ICG and Thorax-ICG above a threshold of correlation of 0.95 with the noiseless vector enabled the analysis of beat inclusion rate (BIR%), yielding an average of 80.9% for Arm-ICG and 100% for Thorax-ICG, and BbyB values of the ICG waveform feature metrics A, B, C and VET accuracy and precision, yielding respective error rates (ER%) of 0.83%, 11.1%, 3.99% and 5.2% for Arm-IG, and 0.41%, 3.82%, 1.66% and 1.25% for Thorax-ICG, respectively. Hence, the functional relationship between ICG metrics within and between the arm and thorax recording modes could be characterised and the linear regression (Arm-ICG vs. Thorax-ICG) trends could be analysed. Overall, it was found in this study that recursive averaging, set with a 36 ICG beats buffer size, was the best Arm-ICG BbyB denoising process, with an average of less than 3.3% in the Arm-ICG time metrics error rate. It was also found that the arm SV versus thorax SV had a linear regression coefficient of determination (R2) of 0.84.

The ECG signal contain vital information for cardiac disease which is one of main cause of catastrophic mortality. In conventional technique, the signals are extracted through different points located on the limbs and surface of the chest. The biological impedance of human body eliminates any practical means of making fake copies of the relevant physiological traits. Moreover, this method needs the complex data acquisition system and apparatus as well as inconvenience way of acquisition of signal at the chest. Hence, there is a demand to find out the promising alternative technique to extract the ECG signals in more convenient way with high accuracy. In this paper, the real-time ECG monitor has been developed to extract the signals from the multipoint on the hands and fingers. Placement of the electrodes are done based on the acupressure point on palms and fingers. A total of 120 volunteers were investigated to develop the ECG database as the development dataset. This work uses the template matching algorithm and distance classification method to analyze and to find the best similarities between the developed dataset of ECG biometric signals to improve the identification rate. In order to lessen the noise that was recorded with the ECG signals, signal averaging was used to create ECG databases and templates. The recognition rate rose to 98% accuracy on the development dataset when the prescreening procedure was introduced to create a combined system model. ECG biometric model was created by combining the two models and using the development dataset's results. The algorithm was applied on the entire developed ECG dataset and 96% of accuracy rate was achieved in identification.

Researchers have long suspected a mutual interaction between maternal and fetal heart rhythms, referred to as maternal-fetal cardiac coupling (MFCC). While several studies have been published on this phenomenon, they vary in terms of methodologies, populations assessed, and definitions of coupling. Moreover, a clear discussion of the potential clinical implications is often lacking. Subsequently, we perform a scoping review to map the current state of the research in this field and, by doing so, form a foundation for future clinically oriented research on this topic. A literature search was performed in PubMed, Embase, and Cochrane. Filters were only set for language (English, Dutch, and German literature were included) and not for year of publication. After screening for the title and the abstract, a full-text evaluation of eligibility followed. All studies on MFCC were included which described coupling between heart rate measurements in both the mother and fetus, regardless of the coupling method used, gestational age, or the maternal or fetal health condition. 23 studies remained after a systematic evaluation of 6,672 studies. Of these, 21 studies found at least occasional instances of MFCC. Methods used to capture MFCC are synchrograms and corresponding phase coherence indices, cross-correlation, joint symbolic dynamics, transfer entropy, bivariate phase rectified signal averaging, and deep coherence. Physiological pathways regulating MFCC are suggested to exist either via the autonomic nervous system or due to the vibroacoustic effect, though neither of these suggested pathways has been verified. The strength and direction of MFCC are found to change with gestational age and with the rate of maternal breathing, while also being further altered in fetuses with cardiac abnormalities and during labor. From the synthesis of the available literature on MFCC presented in this scoping review, it seems evident that MFCC does indeed exist and may have clinical relevance in tracking fetal well-being and development during pregnancy.

Objectives To prospectively evaluate the feasibility and biventricular assessment accuracy of a free-breathing cardiac cine imaging technique (RTCSCineMoCo) combined with highly accelerated real-time (RT) acquisition, compressed sensing (CS) reconstruction, and fully automated non-rigid respiratory motion correction. Methods We evaluated 80 patients scheduled for clinical cardiac MRI. Cardiac cine images of the same long-axis and short-axis stacks were acquired using three techniques: (1) SegBH: standard segmented cine with breath-hold; (2) RTCSCineMoCo; (3) RTCSCine: single-shot RT CS cine at 3.0 T. Image quality (IQ) was evaluated using a qualitative 5-point Likert scale and the European CMR registry standardized criteria. Quantitative parameters including left (LV) and right ventricular (RV) ejection fractions (EF), end-diastolic volumes (EDV), end-systolic volumes (ESV), stroke volumes (SV), and LV mass (LVM) were measured and compared. Results RTCSCineMoCo and SegBH had equivalent IQ scores (4.4 ± 0.7 vs. 4.2 ± 0.8, p = 0.066), while RTCSCine had a significantly lower IQ score than SegBH (4.0 ± 0.8 vs. 4.2 ± 0.8, p = 0.031). In a quantitative analysis, RTCSCineMoCo and SegBH yielded similar measurements for all parameters, while the majority of RTCSCine parameters were significantly different compared with SegBH, except for LVEDV. Conclusion RTCSCineMoCo is a promising method for robust free-breathing cardiac cine imaging, achieving better IQ and more precise quantitative analysis results for both ventricles compared with RTCSCine. Key Points • RTCSCineMoCo is a promising method for free-breathing cardiac MR cine imaging in daily practice. • RTCSCineMoCo provided better IQ and more precise quantitative measurements compared with RTCSCine, by extending RT data acquisition to multiple heartbeats, performing non-rigid respiratory motion correction, and signal averaging. • RTCSCineMoCo may be suitable for routine clinical use for vulnerable patients who may otherwise pose a challenge to image successfully with the conventional segmented cine technique.