Signals Of Different Durations Research Articles

Prediction of paroxysmal atrial fibrillation using a convolutional neural network and electrocardiogram signals

Atrial fibrillation (AF) is the most clinically diagnosed arrhythmia in cardiac pathology. The incidence of AF begins at a very early age and its initial state is paroxysmal atrial fibrillation (PAF). This type of heart disease can be detected and predicted by analyzing the spectrogram of a surface electrocardiogram (ECG) signal. In many studies, different ECG signal formats and convolutional neural network (CNN) architectures have been used. However, the lack of good signal preprocessing or signal adequacy may have affected the accuracy, especially on short-term ECG signals. In this study, we analyzed a preprocessed ECG signal, determined the optimal set to predict PAF, and evaluated the accuracy using ECG signals of different durations. The PAF Prediction Challenge–PhysioNet database was used to extract spectrograms in 30-sec and 5-sec windows for two classes (Normal, PAF) and 3 classes (Normal, Close-AF, Distant-AF). Then, the AlexNet architecture was used. The proposed method achieved a two-class accuracy of 99.92% with a 30-sec window and 99.42% with a 5-sec window, improving the PAF prediction performance compared with similar works. In addition, the three-class accuracies were 96.92% and 97.43% with windows of 30-sec, and 5-sec, respectively. These results prove the efficacy of the method for the early diagnosis of PAF, even based on short-term ECG signals.

Optimal Identification of Muscle Synergies From Typical Sit-to-Stand Clinical Tests.

Goal: The goal of this manuscript is to investigate the optimal methods for extracting muscle synergies from a sit-to-stand test; in particular, the performance in identifying the modular structures from signals of different length is characterized. Methods: Surface electromyography signals have been recorded from instrumented sit-to-stand trials. Muscle synergies have then been extracted from signals of different duration (i.e. 5 times sit to stand and 30 seconds sit to stand) from different portions of a complete sit-to-stand-to-sit cycle. Performance have then been characterized using cross-validation procedures. Moreover, an optimal method based on a modified Akaike Information Criterion measure is applied on the signal for selecting the correct number of synergies from each trial. Results: Results show that it is possible to identify correctly muscle synergies from relatively short signals in a sit-to-stand experiment. Moreover, the information about motor control structures is identified with a higher consistency when only the sit-to-stand phase of the complete cycle is considered. Conclusions: Defining a set of optimal methods for the extraction of muscle synergies from a clnical test such as the sit-to-stand is of key relevance to ensure the applicability of any synergy-related analysis in the clinical practice, without requiring knowledge of the technical signal processing methods and the underlying features of the signal.

Stochastic Sequestration Promotes Specificity in Decision Making in Single Cells.

Cellular functions are mediated by specific molecular interactions; however, often competing nonspecific interactions can occur instead, for example, in noncoding regions of genes during transcription or in the response of cell receptors to external signals. Various functional roles have been proposed for such interactions. Motivated by these considerations, we study the time-dependent behavior of a class of discrete, stochastic models in which decoy molecules mediate nonspecific reactions that sequester activated molecules. It is shown that such nonspecific interactions can lead to a time delay in the completion of the specific reaction by the activated molecule, thus permitting discrimination between signals of different duration. We study the effect of stochastic fluctuations in a simple model of gene transcription by numerical solution of the Master Equation and find that the distribution of first passage times for the specific reaction shows surprising nonexponential (non-Debye) behavior over a range of time scales. The mathematical mechanism underlying this behavior is explained in terms of the behavior of the eigensystem of the linear operator associated with the time evolution. Our results demonstrate that stochastic sequestration can be used to enhance the specificity achieved by the well-known kinetic proofreading mechanism.

Stochastic Modeling of Temporal Enhanced Ultrasound: Impact of Temporal Properties on Prostate Cancer Characterization.

Temporal enhanced ultrasound (TeUS) is a new ultrasound-based imaging technique that provides tissue-specific information. Recent studies have shown the potential of TeUS for improving tissue characterization in prostate cancer diagnosis. We study the temporal properties of TeUS-temporal order and length-and present a new framework to assess their impact on tissue information. We utilize a probabilistic modeling approach using hidden Markov models (HMMs) to capture the temporal signatures of malignant and benign tissues from TeUS signals of nine patients. We model signals of benign and malignant tissues (284 and 286 signals, respectively) in their original temporal order as well as under order permutations. We then compare the resulting models using the Kullback-Liebler divergence and assess their performance differences in characterization. Moreover, we train HMMs using TeUS signals of different durations and compare their model performance when differentiating tissue types. Our findings demonstrate that models of order-preserved signals perform statistically significantly better (85% accuracy) in tissue characterization compared to models of order-altered signals (62% accuracy). The performance degrades as more changes in signal order are introduced. Additionally, models trained on shorter sequences perform as accurately as models of longer sequences. The work presented here strongly indicates that temporal order has substantial impact on TeUS performance; thus, it plays a significant role in conveying tissue-specific information. Furthermore, shorter TeUS signals can relay sufficient information to accurately distinguish between tissue types. Understanding the impact of TeUS properties facilitates the process of its adopting in diagnostic procedures and provides insights on improving its acquisition.

Beat-ID: Towards a computationally low-cost single heartbeat biometric identity check system based on electrocardiogram wave morphology.

In recent years, safer and more reliable biometric methods have been developed. Apart from the need for enhanced security, the media and entertainment sectors have also been applying biometrics in the emerging market of user-adaptable objects/systems to make these systems more user-friendly. However, the complexity of some state-of-the-art biometric systems (e.g., iris recognition) or their high false rejection rate (e.g., fingerprint recognition) is neither compatible with the simple hardware architecture required by reduced-size devices nor the new trend of implementing smart objects within the dynamic market of the Internet of Things (IoT). It was recently shown that an individual can be recognized by extracting features from their electrocardiogram (ECG). However, most current ECG-based biometric algorithms are computationally demanding and/or rely on relatively large (several seconds) ECG samples, which are incompatible with the aforementioned application fields. Here, we present a computationally low-cost method (patent pending), including simple mathematical operations, for identifying a person using only three ECG morphology-based characteristics from a single heartbeat. The algorithm was trained/tested using ECG signals of different duration from the Physionet database on more than 60 different training/test datasets. The proposed method achieved maximal averaged accuracy of 97.450% in distinguishing each subject from a ten-subject set and false acceptance and rejection rates (FAR and FRR) of 5.710±1.900% and 3.440±1.980%, respectively, placing Beat-ID in a very competitive position in terms of the FRR/FAR among state-of-the-art methods. Furthermore, the proposed method can identify a person using an average of 1.020 heartbeats. It therefore has FRR/FAR behavior similar to obtaining a fingerprint, yet it is simpler and requires less expensive hardware. This method targets low-computational/energy-cost scenarios, such as tiny wearable devices (e.g., a smart object that automatically adapts its configuration to the user). A hardware proof-of-concept implementation is presented as an annex to this paper.

Neuronal activation times to simple, complex, and natural sounds in cat primary and nonprimary auditory cortex

Interactions between living organisms and the environment are commonly regulated by accurate and timely processing of sensory signals. Hence, behavioral response engagement by an organism is typically constrained by the arrival time of sensory information to the brain. While psychophysical response latencies to acoustic information have been investigated, little is known about how variations in neuronal response time relate to sensory signal characteristics. Consequently, the primary objective of the present investigation was to determine the pattern of neuronal activation induced by simple (pure tones), complex (noise bursts and frequency modulated sweeps), and natural (conspecific vocalizations) acoustic signals of different durations in cat auditory cortex. Our analysis revealed three major cortical response characteristics. First, latency measures systematically increase in an antero-dorsal to postero-ventral direction among regions of auditory cortex. Second, complex acoustic stimuli reliably provoke faster neuronal response engagement than simple stimuli. Third, variations in neuronal response time induced by changes in stimulus duration are dependent on acoustic spectral features. Collectively, these results demonstrate that acoustic signals, regardless of complexity, induce a directional pattern of activation in auditory cortex.

Brevity is not always a virtue in primate communication.

Semple et al. (Semple et al. in press, Biol. Lett. (doi:10.1098/rsbl.2009.1062)) argued that the 'law of brevity' (an inverse relationship between word length and frequency of use) applies not only to human language but also to vocal signalling in non-human primates, because coding efficiency is paramount in both situations. We analysed the frequency of use of signals of different duration in the vocal repertoires of two Neotropical primate species studied in the wild-the common marmoset (Callithrix jacchus) and the golden-backed uakari (Cacajao melanocephalus). The key prediction of the law of brevity was not supported in either species: although the most frequently emitted calls were relatively brief, they were not the shortest signals in the repertoire. The costs and benefits associated with signals of different duration must be appreciated to understand properly their frequency of use. Although relatively brief vocal signals may be favoured by natural selection in order to minimize energetic costs, the very briefest signals may be ambiguous, contain reduced information or be difficult to detect or locate, and may therefore be selected against. Analogies between human language and vocal communication in animals can be misleading as a basis for understanding frequency of use, because coding efficiency is not the only factor of importance in animal communication, and the costs and benefits associated with different signal durations will vary in a species-specific manner.

Pre-clinical evaluation of respiratory-gated delivery of volumetric modulated arc therapy with RapidArc

A study was carried out to evaluate the possibility of delivering volumetric modulated arc therapy with the RapidArc technology under respiratory-gated conditions. The experiments were performed in the framework of a non-clinically released environment. Plans of six patients, all realized for a single arc, were used for the experiments. The Real-time Position Management™ (RPM) respiratory gating system from Varian was used to generate gate-open signals of different durations. Arcs were delivered applying the different gates creating sequences of beam-hold/beam-on during the dose delivery: the average number of interruptions for a single arc ranged from 0 to 45. Dose prescription was set to 2 Gy and different gate-open periods of 30, 15 and 5 s to keep gantry speed constant at maximum. 5 Gy and 15 Gy doses were then applied to gate-open signals of 5 and 8 s, respectively, to mimic the most challenging conditions of slow gantry rotation and high-frequency interruptions. The 5 and 15 Gy experiments represent dose conditions of clinical interest for stereotactic treatments. For each patient and gating condition, pre-treatment 2D verification measurements were performed using the PTW-729 array in conjunction with the Octavius phantom (PTW, Freiburg); measurements were performed on different days (one per patient, with the complete setup of phantom and detectors every time), while each gating experiment was repeated seven consecutive times for reproducibility (without a new setup of the measurement equipment). Measurements were compared with dose calculations in the treatment planning system (performed without any gating) to appraise the dosimetric impact of the presence of gating and the eventual dependence from the number of interruptions during a single arc. Analysis of machine-registered log files in terms of average deviations between actual and expected positions (from automatic measurements every 50 ms) resulted in mean ΔMU (monitor units) <0.02% for all gating conditions. Δ(Gantry angle) = 0.38 ± 0.01° for 2 Gy (all gate periods), 0.24 ± 0.01° for 5 Gy, and 0.10 ± 0.01° for 15 Gy deliveries. Average deviations for multileaf collimator (MLC) positions (root mean square over all 120 leaves) were 0.45 ± 0.01 mm for 2 Gy (all gate periods), 0.32 ± 0.01 mm for 5 Gy and 0.14 ± 0.01 mm for 15 Gy. Results in terms of dose measurements confirmed that the application of gating to RapidArc delivery does not affect the quality of the dose delivery. With criteria of ΔD = 3%, DTA = 3 mm, the gamma test was passing in a range of 99 to 100% of the measured points for most of the cases (with maximum number of interruptions of about 20 per arc) and from 97 to 98% for the extreme case of 15 Gy and 8 s gate-open signal (corresponding to almost 50 interruptions per arc). In conclusion, RapidArc delivery proved, in a pre-clinical phase and non-clinically released framework, to be reliable and dosimetrically accurate also when applied in conjunction with gating procedures.

Spectral loudness summation as a function of duration.

Loudness was measured as a function of signal bandwidth for 10-, 100-, and 1000-ms-long signals. The test and reference signals were bandpass-filtered noise spectrally centered at 2 kHz. The bandwidth of the test signal was varied from 200 to 6400 Hz. The reference signal had a bandwidth of 3200 Hz. The reference levels were 45, 55, and 65 dB SPL. The level to produce equal loudness was measured with an adaptive, two-interval, two-alternative forced-choice procedure. A loudness matching procedure was used, where the tracks for all signal pairs to be compared were interleaved. Mean results for nine normal-hearing subjects showed that the magnitude of spectral loudness summation depends on signal duration. For all reference levels, a 6- to 8-dB larger level difference between equally loud signals with the smallest (delta f = 200 Hz) and largest (delta f = 6400 Hz) bandwidth is found for 10-ms-long signals than for the 1000-ms-long signals. The duration effect slightly decreases with increasing reference loudness. As a consequence, loudness models should include a duration-dependent compression stage. Alternatively, if a fixed loudness ratio between signals of different duration is assumed, this loudness ratio should depend on the signal spectrum.

Intracellular Calcium Signals Regulating Cytosolic Phospholipase A2 Translocation to Internal Membranes

Increased intracellular Ca(2+) concentrations ([Ca(2+)](i)) promote cytosolic phospholipase A(2) (cPLA(2)) translocation to intracellular membranes. The specific membranes to which cPLA(2) translocates and the [Ca(2+)](i) signals required were investigated. Plasmids of EGFP fused to full-length cPLA(2) (EGFP-FL) or to the cPLA(2) C2 domain (EGFP-C2) were used in Ca(2+)/EGFP imaging experiments of cells treated with [Ca(2+)](i)-mobilizing agonists. EGFP-FL and -C2 translocated to Golgi in response to sustained [Ca(2+)](i) greater than approximately 100-125 nm and to Golgi, ER, and perinuclear membranes (PNM) at [Ca(2+)](i) greater than approximately 210-280 nm. In response to short duration [Ca(2+)](i) transients, EGFP-C2 translocated to Golgi, ER, and PNM, but EGFP-FL translocation was restricted to Golgi. However, EGFP-FL translocated to Golgi, ER, and PNM in response to long duration transients. In response to declining [Ca(2+)](i), EGFP-C2 readily dissociated from Golgi, but EGFP-FL dissociation was delayed. Agonist-induced arachidonic acid release was proportional to the [Ca(2+)](i) and to the extent of cPLA(2) translocation. In summary, we find that the differential translocation of cPLA(2) to Golgi or to ER and PNM is a function of [Ca(2+)](i) amplitude and duration. These results suggest that the cPLA(2) C2 domain regulates differential, Ca(2+)-dependent membrane targeting and that the catalytic domain regulates both the rate of translocation and enzyme residence.

The monolithic double-threshold discriminator

A double-threshold discriminator capable of processing input signals of different duration is described. Simplicity of the discriminator circuitry makes it possible to embody the discriminator in multichannel ICs using microwave bipolar-JFET technology. Time walk is calculated to be less than 0.35 ns for the input ramp signals with rise times 25–100 ns and amplitudes 50 mV–1 V.

Habituation based neural networks for spatio-temporal classification

A new class of neural networks is proposed for the dynamic classification of spatio-temporal signals. These networks are designed to classify signals of different durations, taking into account correlations among different signal segments. Such networks are applicable to SONAR and speech signal classification problems, among others. Network parameters are adapted based on the biologically observed habituation mechanism. This allows the storage of contextual information, without a substantial increase in network complexity. We introduce the concept of a complete memory. We then prove mathematically that a network with a complete memory temporal encoding stage followed by a sufficiently powerful feedforward network is capable of approximating arbitrarily well any continuous, causal, time-invariant discrete-time system with a uniformly bounded input domain. The memory mechanisms of the habituation based networks are complete memories, and involve nonlinear transformations of the input signal. In networks such as the time delay neural network (TDNN) [35] and focused gamma networks [8], nonlinearities are present in the feedforward stage only. This distinction is made important by recent theoretical results concerning the limitations of structures with linear temporal encoding stages. Results are reported on classification of high dimensional feature vectors obtained from Banzhaf sonograms.

Interfacing cultured neurons to planar substrate microelectrodes: characterization of the neuron-to-microelectrode junction

This paper focuses on the characterization of the bioelectrochemical interface that develops whenever neurons are cultured directly on top of planar arrays of noble metal microelectrodes. The characterization is based on the equivalent circuit analysis of a neuron membrane coupled to a metallic planar microelectrode. The membrane is described according to the Hodgkin-Huxley model, using a set of equations specialized for the description of action potentials generated by chick embryo dorsal root ganglia (DRG) neurons. An ad-hoc modified version of the circuit analysis program spice allows one to simulate the signal corresponding to an action potential as it should result from the microelectrode transduction. By varying the membrane-to-electrode coupling and other biophysical parameters, simulation signals of different durations, intensities and shapes are generated. The appropriateness of the model is verified by adapting simulation signals to experimental ones, obtained by preliminary experiments with DRG neurons cultured on a microelectrode array. The potentialities and limitations of the equivalent circuit approach as a tool for the characterization of a long-term (i.e. days) coupling of neurons to planar microelectrodes are discussed.

Sound intensity processing by the goldfish.

Capacities of the goldfish for intensity discrimination were studied using classical respiratory conditioning and a staircase psychophysical procedure. Physiological studies on single saccular (auditory) nerve fibers under similar stimulus conditions helped characterize the dimensions of neural activity used in intensity discrimination. Incremental intensity difference limens (IDLs in dB) for 160-ms increments in continuous noise, 500-ms noise bursts, and 500-ms, 800-Hz tone bursts are 2 to 3 dB, are independent of overall level, and vary with signal duration according to a power function with a slope averaging - 0.33. Noise decrements are relatively poorly detected and the silent gap detection threshold is about 35 ms. The IDLs for increments and decrements in an 800-Hz continuous tone are about 0.13 dB, are independent of duration, and are level dependent. Unlike mammalian auditory nerve fibers, some goldfish saccular fibers show variation in recovery time to tonal increments and decrements, and adaptation to a zero rate. Unit responses to tone increments and decrements show rate effects generally in accord with previous observations on intracellular epsp's in goldfish saccular fibers. Neurophysiological correlates of psychophysical intensity discrimination data suggest the following: (1) noise gap detection may be based on spike rate increments which follow gap offset; (2) detection of increments and decrements in continuous tones may be determined by steep low-pass filtering in peripheral neural channels which enhance the effects of spectral "splatter" toward the lower frequencies; (3) IDLs for pulsed signals of different duration can be predicted from the slopes of rate-intensity functions and spike rate variability in individual auditory nerve fibers; and (4) at different sound pressure levels, different populations of peripheral fibers provide the information used in intensity discrimination.

Auditory hallucinations and left temporal lobe pathology

Thresholds of tone signals of different duration were studied in 30 right-handed patients with paranoid schizophrenia and different forms of verbal hallucination. In hallucinating patients, as compared to a control gruop (non-hallucinating schizophrenics with a paranoiac syndrome), there was an asymmetry of detection thresholds for short-tone signals (from 10 msec or less) at the expense of an increase of thresholds in the right ear. In 2 patients with apparent left-handedness there was an asymmetry in the left ear. This asymmetry was marked in patients with genuine verbal hallucination. The authors discuss the relationship between verbal hallucination and mechanisms of inner speech, and the pathology of the audio-verbal zone in the temporal area of the dominant hemisphere.

On the capacity of a discrete, constant channel

This paper is concerned with an iterative method for calculation of the capacity of a discrete, constant channel. Unlike the standard reference (Muroga 1953), in which Lagrange multipliers are used in the conventional form, the method described is based on techniques of mathematical programming. In addition, input signals of different duration are admitted. The algorithm proposed is very simple and has the advantage that it yields converging lower and uppper bounds for the capacity.

Interaural Phase Effects in the Masking of Signals of Different Durations

The detectability of a pulsed, 250-cps sinusoid in noise was measured under three interaural phase conditions and at three durations. The conditions were (1) signal and noise in one ear only, SmNm, (2) signal in one ear and the same in-phase noise in both ears, SmN0, (3) signal in both ears, but with a 180° phase difference, and the same in-phase noise in both ears, SπN0. The detectability of the signal was about 9 dB better in Condition 2 than in Condition 1, and about 7 dB better in Condition 3 than in Condition 2. The difference in detectability is slightly dependent on signal duration, the largest difference appearing at the shortest duration. The psychometric functions were essentially the same in all conditions, except for an attenuation constant. The results are contrasted with two theories used to account for the binaural effects; some discrepancy between both theories and the results are noted.