EMG recurrence quantifications in dynamic exercise

This study was designed to evaluate the suitability of nonlinear recurrence quantification analysis (RQA) in assessing electromyograph (EMG) signals during dynamic exercise. RQA has been proven to be effective in analyzing nonstationary signals. The subject group consisted of 19 male patients diagnosed with low back pain. EMG signals were recorded from left and right paraspinal muscles during isoinertial exercise both before and after 12 weeks of regimented physical therapy. Autorecurrence analysis was performed between the left and right EMG signals individually, and cross-recurrence analysis was performed on the left-right EMG pairs. Spectral analysis of the EMG signals was employed as an independent, objective measure of fatigue. Increase in the RQA variable % determinism during the 90-s dynamic tests was found to be a good marker for fatigue. Before physical therapy, this nonlinear marker revealed simultaneous increases in motor unit recruitment within each pool and between left and right pools. After physical therapy, the motor unit recruitment was less within and between pools, indicative of increased fatigue resistance. Finally, fatigue resistance (less increase in % determinism) correlated well with subjective scores of pain relief. Taken together, these latter results indicate that recurrence analysis may be useful in charting the efficacy of a specific exercise therapy program in reducing low back pain by elevating the fatigue threshold.     

Nonlinear surface EMG analysis to detect changes of motor unit conduction velocity and synchronization.

Amplitude and frequency content of the surface electromyographic (EMG) signal reflect central and peripheral modifications of the neuromuscular system. Classic surface EMG spectral variables applied to assess muscle functions are the centroid and median power spectral frequencies. More recently, nonlinear tools have been introduced to analyze the surface EMG; among them, the recurrence quantification analysis (RQA) was shown to be particularly promising for the detection of muscle status changes. The purpose of this work was to analyze the effect of motor unit short-term synchronization and conduction velocity (CV) on EMG spectral variables and two variables extracted by RQA, the percentage of recurrence (%Rec) and determinism (%Det). The study was performed on the basis of a simulation model, which allowed changing the degree of synchronization and mean CV of a number of motor units, and of an experimental investigation of the surface EMG signal properties detected during high-force-level isometric fatiguing contractions of the biceps brachii muscle. Simulations and experimental results were largely in agreement and show that 1) spectral variables, %Rec, and %Det are influenced by CV and degree of synchronization; 2) spectral variables are highly correlated with %Det (R = -0.95 in the simulations and -0.78 and -0.75 for the initial values and normalized slopes, respectively, in the experimental signals), and thus the information they provide on muscle properties is basically the same; and 3) variations of %Det and %Rec in response to changes in muscle properties are significantly larger than the variations of spectral variables. This study validates RQA as a means for fatigue assessment with potential advantages (such as the higher sensitivity to changes of muscle status) with respect to the classic spectral analysis.     

Detection and sources of nonlinearity in the variability of cardiac R-R intervals and blood pressure in rats

Beat-to-beat R-R interval (RRV) and systolic blood pressure (SPV) variability signals were obtained from unrestrained rats in baseline and under different pharmacological treatments. The origin and extent of the nonlinearity in both signals, as well as their degree of mutual coupling, was estimated using measurements from the correlation integral (CI) and recurrence quantification analysis (RQA). After the respiratory component of baseline signals was removed, the nonlinearity was lower in the RRV and disappeared in the SPV. This also decreased the RRV-SPV coupling. The nonlinearity of RRV was also reduced after atropine, and the nonlinearity of SPV was strengthened after prazosin and N(omega)-monomethyl-L-arginine (L-NMMA). Atropine and prazosin decreased CI measures of both signals, whereas propranolol, phenylephrine, and L-NMMA decreased only those of SPV. RQA indexes of RRV increased after atropine and decreased after propranolol, whereas the reverse occurred for the RRV-SPV coupling. These results suggest that: 1) the nonlinearity of RRV appears to be very dependent on the parasympathetic activity, whereas that of SPV seems to come from its respiratory component through a nonneural pathway; 2) respiratory component appears to be involved, through the parasympathetic system, in the RRV-SPV coupling; and 3) CI and RQA measures seems to be useful in assessing autonomic mediation of RRV and RRV-SPV coupling.     

RQA在肌电分析中的应用

介绍了递归图的生成方法和定量递归分析（RQA）中递归点的百发数,确定性线段的百分数,线段分布香农熵等分析量的意义。应用RQA分析肱二头肌及肱桡肌在不同负重下的肌电信号,发现肽二头肌肌电信号的递归点百分数的比肱肌高,有较强的周期性嵌入。与同一信号所作的FFT谱分析相比较,RQA法有较同的区分灵敏性,是肌电分析的一种新方法,它在其他复杂的生理信号处理中也有十分广阔的应用前景。     

Comparing the HRV Time-Series Signals Acquired from Cannabis Consuming and Non-Consuming Indian Paddy-Field Workers by Recurrence Quantification Analysis

ObjectiveIn the last few decades, the consumption of cannabis-based products for recreational purposes has dramatically increased. Unfortunately, cannabis consumption has been associated with the incidences of cardiovascular diseases. Hence, there is a necessity for understanding the plausible mechanics of cardiophysiological changes due to cannabis consumption. Accordingly, the current study was designed to understand the suitability of the recurrence quantification analysis (RQA) method in detecting the changes in the heart rate variability (HRV) time-series signals due to the consumption of cannabis (bhang). Further, a machine learning model has been proposed for the automated detection of the cannabis takers.Materials and MethodsThe RQA of the HRV time-series signals from 200 healthy Indian male paddy-field workers were carried out. The obtained parameters were statistically analyzed using the Mann-Whitney U test. Further, the decision trees, weight-based feature ranking, and dimensionality reduction methods were employed for identifying the relevant features for the development of a suitable machine learning model.ResultsObservable changes in the patterns of the recurrence plots among the bhang consuming and non-consuming groups were noticed. However, there were no significant differences in the RQA parameters. Among the developed machine learning models, the SVM model obtained from the “Information gain ratio” feature selection method exhibited the highest accuracy (%) of 69.09 ± 9.33.ConclusionOur study suggests that the RQA method is not as effective as the time and frequency domain methods for detecting the alterations in the HRV time-series signals due to cannabis consumption. The SVM model was found to be the best model for the automated detection of cannabis takers. The selection of the features by the information gain ratio method played an important role in the development of the optimized SVM model.     

Otoacoustic emissions at different click intensities: invariant and subject-dependent features.

A study of click-evoked otoacoustic emissions (CEOAEs) elicited at stimulation intensities from 35 to >80 dB was carried out by recurrence quantification analysis on signals from both normal and hearing-impaired subjects. In normal subjects, a clear scaling of determinism with increasing stimulation intensity was observed in the click intensity range from 41 to 59 dB. Outside that range and, in particular, above its upper end, subject-dependent features appeared in the form of different maximal levels of determinism. A comparative analysis of responses from hearing-impaired subjects with conductive hearing losses and sensorineural hearing losses suggested that the principal contributor to this behavior is the middle ear and allowed us to discriminate the two pathologies solely on the basis of CEOAEs. These observations are consistent with a simple phenomenological model of the auditory periphery in which different functional modules are sequentially recruited at increasing stimulus intensities, with a consequent rise in CEOAE coherence.     

Application of recurrence quantification analysis for the automated identification of epileptic EEG signals

Epilepsy is a common neurological disorder that is characterized by the recurrence of seizures. Electroencephalogram (EEG) signals are widely used to diagnose seizures. Because of the non-linear and dynamic nature of the EEG signals, it is difficult to effectively decipher the subtle changes in these signals by visual inspection and by using linear techniques. Therefore, non-linear methods are being researched to analyze the EEG signals. In this work, we use the recorded EEG signals in Recurrence Plots (RP), and extract Recurrence Quantification Analysis (RQA) parameters from the RP in order to classify the EEG signals into normal, ictal, and interictal classes. Recurrence Plot (RP) is a graph that shows all the times at which a state of the dynamical system recurs. Studies have reported significantly different RQA parameters for the three classes. However, more studies are needed to develop classifiers that use these promising features and present good classification accuracy in differentiating the three types of EEG segments. Therefore, in this work, we have used ten RQA parameters to quantify the important features in the EEG signals.These features were fed to seven different classifiers: Support vector machine (SVM), Gaussian Mixture Model (GMM), Fuzzy Sugeno Classifier, K-Nearest Neighbor (KNN), Naive Bayes Classifier (NBC), Decision Tree (DT), and Radial Basis Probabilistic Neural Network (RBPNN). Our results show that the SVM classifier was able to identify the EEG class with an average efficiency of 95.6%, sensitivity and specificity of 98.9% and 97.8%, respectively.     

基于定量分析方法的动作表面肌电信号分析

介绍了非线性数据处理方法递归图法(recurrence plots,RP)及其定量分析方法(recurrence quantifi-cation analysis,RQA),并利用RP和RQA研究了动作表面肌电信号。研究发现,表面肌电信号在不同动作模式下其所对应的RP图在结构上差异明显,通过计算两通道肌电信号的RQA指标递归率,发现不同动作信号的RQA指标递归率值具有不同的聚类分布。该方法为肌电信号的动作模式分类提供了一种新的思路。     

Sex differences in otoacoustic emissions measured in rhesus monkeys (Macaca mulatta)

Click-evoked otoacoustic emissions (CEOAEs) and distortion-product OAEs (DPOAEs) were measured in about 60 rhesus monkeys. CEOAE strength was substantially greater in females than in males, just as in humans. DPOAE strength was generally slightly stronger in females, just as in humans. In males, CEOAEs were weaker (more masculine) in the fall breeding season and in winter than in the summer. In females, CEOAEs were slightly stronger (more feminine) in the fall, when sex steroids are elevated in females (and males), than in the summer when rhesus monkeys are reproductively quiescent. Thus, the sex differences in CEOAEs were greater in the fall than in the summer. We presume that the seasonal fluctuations in OAEs reflect activational hormonal effects, while the basic sex differences in OAEs likely reflect organizational effects of prenatal androgen exposure. Some monkeys of both sexes had been treated with additional testosterone or the anti-androgen flutamide during prenatal development. In accord with expectations, prenatal androgen treatment weakened CEOAEs in females, and prenatal flutamide treatment strengthened CEOAEs in males. For DPOAEs, the differences between treated and untreated groups were mostly small and often inconsistent. Taken as a whole, the data from both rhesus monkeys and humans suggest that the linear, reflection-based mechanism of OAE production that underlies CEOAEs is more sensitive to prenatal androgenic processes than is the nonlinear distortion mechanism that underlies DPOAEs.     

Chaotic and stochastic dynamics of epileptiform-like activities in sclerotic hippocampus resected from patients with pharmacoresistant epilepsy

The types of epileptiform activity occurring in the sclerotic hippocampus with highest incidence are interictal-like events (II) and periodic ictal spiking (PIS). These activities are classified according to their event rates, but it is still unclear if these rate differences are consequences of underlying physiological mechanisms. Identifying new and more specific information related to these two activities may bring insights to a better understanding about the epileptogenic process and new diagnosis. We applied Poincaré map analysis and Recurrence Quantification Analysis (RQA) onto 35 in vitro electrophysiological signals recorded from slices of 12 hippocampal tissues surgically resected from patients with pharmacoresistant temporal lobe epilepsy. These analyzes showed that the II activity is related to chaotic dynamics, whereas the PIS activity is related to deterministic periodic dynamics. Additionally, it indicates that their different rates are consequence of different endogenous dynamics. Finally, by using two computational models we were able to simulate the transition between II and PIS activities. The RQA was applied to different periods of these simulations to compare the recurrences between artificial and real signals, showing that different ranges of regularity-chaoticity can be directly associated with the generation of PIS and II activities.     

Masculinized otoacoustic emissions in female spotted hyenas (Crocuta crocuta)

In humans and rhesus monkeys, click-evoked otoacoustic emissions (CEOAEs) are stronger in females than in males, and there is considerable circumstantial evidence that this sex difference is attributable to the greater exposure to androgens prenatally in males. Because female spotted hyenas are highly androgenized beginning early in prenatal development, we expected an absence of sexual dimorphism in the CEOAEs of this species. The CEOAEs obtained from 9 male and 7 female spotted hyenas confirmed that expectation. The implication is that the marked androgenization to which female spotted hyenas are exposed masculinizes the cochlear mechanism responsible for CEOAEs. The CEOAEs measured in 3 male and 3 female hyenas that had been treated with anti-androgenic agents during prenatal development were stronger than the CEOAEs of the untreated animals, in accord with the implied inverse relationship between prenatal androgen exposure and the strength of the cochlear mechanisms producing CEOAEs. The CEOAEs of three ovariectomized females and two castrated males were essentially the same as those for the untreated females and males, suggesting that there is little or no activational effect of hormones on CEOAE strength in spotted hyenas. Distortion product OAEs (DPOAEs) also were measured. Those sex differences also were generally small (as they are in humans), and the effects of the anti-androgen agents were inconsistent. Thus, prenatal androgen exposure apparently does affect OAEs, but the effects appear to be greater for the reflection-based cochlear mechanism that underlies CEOAEs than for the nonlinear cochlear mechanism underlying DPOAEs.     

Order patterns recurrence plots in the analysis of ERP data

Recurrence quantification analysis (RQA) is an established tool for data analysis in various behavioural sciences. In this article we present a refined notion of RQA based on order patterns. The use of order patterns is commonplace in time series analysis. Exploiting this concept in combination with recurrence plots (RP) and their quantification (RQA) allows for advances in contemporary EEG research, specifically in the analysis of event related potentials (ERP), as the method is known to be robust against non-stationary data. The use of order patterns recurrence plots (OPRPs) on EEG data recorded during a language processing experiment exemplifies the potentials of the method. We could show that the application of RQA to ERP data allows for a considerable reduction of the number of trials required in ERP research while still maintaining statistical validity.     

Elucidating protein secondary structures using alpha-carbon recurrence quantifications.

Secondary structures of proteins were studied by recurrence quantification analysis (RQA). High-resolution, 3-dimensional coordinates of alpha-carbon atoms comprising a set of 68 proteins were downloaded from the Protein Data Bank. By fine-tuning four recurrence parameters (radius, line, residue, separation), it was possible to establish excellent agreement between percent contribution of alpha-helix and beta-sheet structures determined independently by RQA and that of the DSSP algorithm (Define Secondary Structure of Proteins). These results indicate that there is an equivalency between these two techniques, which are based upon totally different pattern recognition strategies. RQA enhances qualitative contact maps by quantifying the arrangements of recurrent points of alpha carbons close in 3-dimensional space. For example, the radius was systematically increased, moving the analysis beyond local alpha-carbon neighborhoods in order to capture super-secondary and tertiary structures. However, differences between proteins could only be detected within distances up to about 6-11 A, but not higher. This result underscores the complexity of alpha-carbon spacing when super-secondary structures appear at larger distances. Finally, RQA-defined secondary structures were found to be robust against random displacement of alpha carbons upwards of 1 A. This finding has potential import for the dynamic functions of proteins in motion.     

Nonlinear time-course of lumbar muscle fatigue using recurrence quantifications

 Isometric skeletal muscle fatigue is usually assumed to be a linear process based upon the monotonic decrease in spectral frequency of the EMG. Since spectral analysis by fast Fourier transform (FFT) constitutes a linear transformation of the data, the present study was designed to reevaluate the time-course of muscle fatigue with a nonlinear tool, recurrence quantification analysis (RQA). Surface EMG recordings were obtained from the multifidus muscle of 17 human subjects during isometric posture-holding of the upper torso. The process of muscle fatigue was found to be linear for 59% of the subjects by FFT criteria, but nonlinear for 76% by RQA criteria. As a demonstrative control, both slow and fast transients occurring within a nonlinear mathematical process could be accurately depicted by RQA, but not by FFT. It is concluded that assessment of EMG patterns by nonlinear techniques can give insight into the time-course of fatiguing muscles attributed to the summation of several nonlinear and competing processes. Received: 12 November 1998 / Accepted in revised form: 29 November 1999     

Discrimination of single amino acid mutations of the p53 protein by means of deterministic singularities of recurrence quantification analysis

p53 is mutated in roughly 50% of all human tumors, predominantly in the DNA-binding domain codons. Structural, biochemical, and functional studies have reported that the different p53 mutants possess a broad range of behaviors that include the elimination of the tumor-suppression function of wild-type protein, the acquisition of dominant-negative function over the wild-type form, and the establishment of gain-of-function activities. The contribution of each of these types of mutations to tumor progression, grade of malignancy, and response to anticancer treatments has been so far analyzed only for a few "hot-spots." In an attempt to identify new approaches to systematically characterize the complete spectrum of p53 mutations, we applied recurrence quantification analysis (RQA), a non-linear signal analysis technique, to p53 primary structure. Moving from the study of the p53 hydrophobicity pattern, which revealed important similarities with the singular deterministic structuring of prions, we could statistically discriminate, on a pure amino acid sequence basis, between experimentally characterized DNA-contact defective and conformational p53 mutants with a very high percentage of success. This result indicates that RQA is a mathematical tool particularly advantageous for the development of a database of p53 mutations that integrates epidemiological data with structural and functional categorizations.     

Nonlinear features and complexity patterns of vegetation dynamics in the transition zone of North China

Normalized Difference Vegetation Index (NDVI) has been commonly used to estimate terrestrial vegetation distribution and productivity. In this study, we adopted recurrence quantification analysis (RQA) to investigate the spatial patterns of determinism of the vegetation dynamics ecological-geographical transition zones in North China, especially the differences between transition zone and the surrounding areas. The results indicated that there were obvious regional variances in spatial patterns of RQA indices—determinism, laminarity, entropy, and averaged diagonal line length. Remarkable differences of the determinism of NDVI time series also existed between transition zones and the surrounding areas. Moreover, the correlation analysis between the RQA indices and climatic factors suggested that the determinism of the NDVI time series was nonlinearly affected by hydrothermal conditions. Influenced by vegetation patterns, determinism reached the maximum when the annual precipitation is about 400 mm, which is the lower bound of cultivation and forest distribution, and along the 400 mm isohyet is the area where transition zones locate.     

Effect of prenatal androgens on click-evoked otoacoustic emissions in male and female sheep (Ovis aries)

Otoacoustic emissions (OAEs) were measured in male and female Suffolk sheep (Ovis aries). Some sheep had been administered androgens or estrogens during prenatal development, some were gonadectomized after birth, and some were allowed to develop normally. As previously reported for spotted hyenas, gonadectomy did not alter the OAEs for either sex; accordingly, the untreated/intact and the untreated/gonadectomized animals were pooled to form the control groups. The click-evoked otoacoustic emissions (CEOAEs) exhibited by the female control group (N = 12) were slightly stronger (effect size = 0.42) than those in the male control group (N = 15), which is the same direction of effect reported for humans and rhesus monkeys. Females administered testosterone prenatally (N = 16) had substantially weaker (masculinized) CEOAEs than control females (effect size = 1.15). Both of these outcomes are in accord with the idea that prenatal exposure to androgens weakens the cochlear mechanisms that underlie the production of OAEs. The CEOAEs of males administered testosterone prenatally (N = 5) were not different from those of control males, an outcome also seen in similarly treated rhesus monkeys. Males administered dihydrotestosterone (DHT) prenatally (N = 3) had slightly stronger (hypo-masculinized) CEOAEs than control males. No spontaneous otoacoustic emissions (SOAEs) were found in any ears, a common finding in non-human species. To our knowledge, this is the first ruminant species measured for OAEs.     

广义时频分析方法在耳声发射研究中的应用 Ⅱ.短声与短纯音诱发耳声发射信号的时频分布

为了进一步探讨耳声发射的产生机制,需要研究不同类型刺激诱发的耳声发射之间的相互关系,主要研究短声与短纯音诱发的耳声发射,用广义时频分析方法中的锥形核分布分别计算了它们的时频分布,从其时频分布分析了它们之间的相互关系。结果表明：具有不同中心频率的短纯音刺激诱发耳声发射的时频分布的迭加与短声刺激诱发的耳声发射的时频分布具有相似性,两者时频分布中的主要频率成分数目、潜伏期和持续时间完全相同,它们高度的相