scholarly journals Tracking Rhythms Coherence From Polysomnographic Records: A Time-Frequency Approach

2021 ◽  
Vol 7 ◽  
Author(s):  
Alexandre Guillet ◽  
Alain Arneodo ◽  
Françoise Argoul
Keyword(s):  
Wavelet Transforms ◽  
Dynamical Process ◽  
Frequency Range ◽  
Sinus Arrhythmia ◽  
Time Frequency ◽  
Physiological Processes ◽  
Spectral Ranges ◽  
Frequency Coherence ◽  
The Brain ◽  
Organ Dysfunctions

The crosstalk between organs plays a crucial role in physiological processes. This coupling is a dynamical process, it must cope with a huge variety of rhythms with frequencies ranging from milliseconds to hours, days, seasons. The brain is a central hub for this crosstalk. During sleep, automatic rhythmic interrelations are enhanced and provide a direct insight into organ dysfunctions, however their origin remains a difficult issue, in particular in sleep disorders. In this study, we focus on EEG, ECG, and airflow recordings from polysomnography databases. Because these signals are non-stationary, non-linear, noisy, and span wide spectral ranges, a time-frequency analysis, based on wavelet transforms, is more appropriate to handle this complexity. We design a wavelet-based extraction method to identify the characteristic rhythms of these different signals, and their temporal variability. These new constructs are combined in pairs to compute their wavelet-based time-frequency complex coherence. These time-frequency coherence maps highlight the occurrence of a slowly modulated coherence pattern in the frequency range [0.01–0.06] Hz, which appears in both obstructive and central apnea. A preliminary exploration of a large database from the National Sleep Research Resource with respiration disorders, such as apnea provides some clues on its relation with autonomic cardio-respiratory coupling and brain rhythms. We also observe that during sleep apnea episodes (either obstructive or central), the cardiopulmonary coherence (in particular respiratory sinus-arrhythmia) in the frequency range [0.1–0.7] Hz strongly diminishes, suggesting a modification of this coupling. Finally, comparing time-averaged coherence with heart rate variability spectra in different apnea episodes, we discuss their common trait and their differences.

scholarly journals Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pablo Armañac-Julián ◽  
David Hernando ◽  
Jesús Lázaro ◽  
Candelaria de Haro ◽  
Rudys Magrans ◽  
...  
Keyword(s):  
Heart Rate ◽  
Mechanical Ventilation ◽  
Spontaneous Breathing Trial ◽  
Sinus Arrhythmia ◽  
Time Frequency ◽  
Cardiopulmonary Coupling ◽  
Cardiac Pumping ◽  
Successful Weaning ◽  
Frequency Coherence ◽  
Subspace Projections

AbstractThe ideal moment to withdraw respiratory supply of patients under Mechanical Ventilation at Intensive Care Units (ICU), is not easy to be determined for clinicians. Although the Spontaneous Breathing Trial (SBT) provides a measure of the patients’ readiness, there is still around 15–20% of predictive failure rate. This work is a proof of concept focused on adding new value to the prediction of the weaning outcome. Heart Rate Variability (HRV) and Cardiopulmonary Coupling (CPC) methods are evaluated as new complementary estimates to assess weaning readiness. The CPC is related to how the mechanisms regulating respiration and cardiac pumping are working simultaneously, and it is defined from HRV in combination with respiratory information. Three different techniques are used to estimate the CPC, including Time-Frequency Coherence, Dynamic Mutual Information and Orthogonal Subspace Projections. The cohort study includes 22 patients in pressure support ventilation, ready to undergo the SBT, analysed in the 24 h previous to the SBT. Of these, 13 had a successful weaning and 9 failed the SBT or needed reintubation –being both considered as failed weaning. Results illustrate that traditional variables such as heart rate, respiratory frequency, and the parameters derived from HRV do not differ in patients with successful or failed weaning. Results revealed that HRV parameters can vary considerably depending on the time at which they are measured. This fact could be attributed to circadian rhythms, having a strong influence on HRV values. On the contrary, significant statistical differences are found in the proposed CPC parameters when comparing the values of the two groups, and throughout the whole recordings. In addition, differences are greater at night, probably because patients with failed weaning might be experiencing more respiratory episodes, e.g. apneas during the night, which is directly related to a reduced respiratory sinus arrhythmia. Therefore, results suggest that the traditional measures could be used in combination with the proposed CPC biomarkers to improve weaning readiness.

scholarly journals Quantitative feature analysis of continuous analytic wavelet transforms of electrocardiography and electromyography

2018 ◽  
Vol 376 (2126) ◽  
pp. 20170250 ◽  
Author(s):  
Mark P. Wachowiak ◽  
Renata Wachowiak-Smolíková ◽  
Michel J. Johnson ◽  
Dean C. Hay ◽  
Kevin E. Power ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Wavelet Transforms ◽  
Continuous Wavelet ◽  
Theme Issue ◽  
Practical Applications ◽  
Time Frequency ◽  
New Family ◽  
Physiological Processes ◽  
Analytic Wavelet

Theoretical and practical advances in time–frequency analysis, in general, and the continuous wavelet transform (CWT), in particular, have increased over the last two decades. Although the Morlet wavelet has been the default choice for wavelet analysis, a new family of analytic wavelets, known as generalized Morse wavelets, which subsume several other analytic wavelet families, have been increasingly employed due to their time and frequency localization benefits and their utility in isolating and extracting quantifiable features in the time–frequency domain. The current paper describes two practical applications of analysing the features obtained from the generalized Morse CWT: (i) electromyography, for isolating important features in muscle bursts during skating, and (ii) electrocardiography, for assessing heart rate variability, which is represented as the ridge of the main transform frequency band. These features are subsequently quantified to facilitate exploration of the underlying physiological processes from which the signals were generated. This article is part of the theme issue ‘Redundancy rules: the continuous wavelet transform comes of age’.

scholarly journals The brain dynamics of architectural affordances during transition

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zakaria Djebbara ◽  
Lars Brorson Fich ◽  
Klaus Gramann
Keyword(s):  
Occipital Cortex ◽  
The Body ◽  
Brain Dynamics ◽  
Alpha Band ◽  
Time Frequency ◽  
Posterior Cingulate ◽  
Sensory Signals ◽  
Event Related Desynchronization ◽  
The Brain ◽  
Attentional Mechanisms

AbstractAction is a medium of collecting sensory information about the environment, which in turn is shaped by architectural affordances. Affordances characterize the fit between the physical structure of the body and capacities for movement and interaction with the environment, thus relying on sensorimotor processes associated with exploring the surroundings. Central to sensorimotor brain dynamics, the attentional mechanisms directing the gating function of sensory signals share neuronal resources with motor-related processes necessary to inferring the external causes of sensory signals. Such a predictive coding approach suggests that sensorimotor dynamics are sensitive to architectural affordances that support or suppress specific kinds of actions for an individual. However, how architectural affordances relate to the attentional mechanisms underlying the gating function for sensory signals remains unknown. Here we demonstrate that event-related desynchronization of alpha-band oscillations in parieto-occipital and medio-temporal regions covary with the architectural affordances. Source-level time–frequency analysis of data recorded in a motor-priming Mobile Brain/Body Imaging experiment revealed strong event-related desynchronization of the alpha band to originate from the posterior cingulate complex, the parahippocampal region as well as the occipital cortex. Our results firstly contribute to the understanding of how the brain resolves architectural affordances relevant to behaviour. Second, our results indicate that the alpha-band originating from the occipital cortex and parahippocampal region covaries with the architectural affordances before participants interact with the environment, whereas during the interaction, the posterior cingulate cortex and motor areas dynamically reflect the affordable behaviour. We conclude that the sensorimotor dynamics reflect behaviour-relevant features in the designed environment.

scholarly journals Interpolation in wavelet spaces and the HRT-conjecture

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Eirik Berge
Keyword(s):  
Compact Group ◽  
Wavelet Transforms ◽  
Reproducing Kernel ◽  
Reproducing Kernel Hilbert Space ◽  
Space Structure ◽  
Locally Compact Group ◽  
Locally Compact ◽  
Positive Type ◽  
Time Frequency ◽  
Hrt Conjecture

AbstractWe investigate the wavelet spaces $$\mathcal {W}_{g}(\mathcal {H}_{\pi })\subset L^{2}(G)$$ W g ( H π ) ⊂ L 2 ( G ) arising from square integrable representations $$\pi :G \rightarrow \mathcal {U}(\mathcal {H}_{\pi })$$ π : G → U ( H π ) of a locally compact group G. We show that the wavelet spaces are rigid in the sense that non-trivial intersection between them imposes strong restrictions. Moreover, we use this to derive consequences for wavelet transforms related to convexity and functions of positive type. Motivated by the reproducing kernel Hilbert space structure of wavelet spaces we examine an interpolation problem. In the setting of time–frequency analysis, this problem turns out to be equivalent to the HRT-conjecture. Finally, we consider the problem of whether all the wavelet spaces $$\mathcal {W}_{g}(\mathcal {H}_{\pi })$$ W g ( H π ) of a locally compact group G collectively exhaust the ambient space $$L^{2}(G)$$ L 2 ( G ) . We show that the answer is affirmative for compact groups, while negative for the reduced Heisenberg group.

Time–Frequency and Wavelet Transforms of EMI Dynamic Spectrum in Chaotic Converter

2009 ◽  
Vol 24 (4) ◽  
pp. 1083-1092 ◽  
Author(s):  
Ru Yang ◽  
Bo Zhang ◽  
Dongyuan Qiu ◽  
Zuolian Liu
Keyword(s):  
Wavelet Transforms ◽  
Dynamic Spectrum ◽  
Time Frequency

scholarly journals The wavelet transforms technique in the computer-aided system for controlling the quarry unmanned vehicles

2021 ◽  
Vol 315 ◽  
pp. 03022
Author(s):  
Ivan Chicherin ◽  
Boris Fedosenkov ◽  
Dmitriy Dubinkin ◽  
Wang Zhenbo
Keyword(s):  
Wavelet Transforms ◽  
Matching Pursuit ◽  
Effective Means ◽  
Unmanned Vehicles ◽  
Open Pit ◽  
Open Pit Mining ◽  
Frequency Distributions ◽  
One Dimensional ◽  
Time Frequency ◽  
Computer Aided

Introduction. Purpose of the work. Within the framework of the computer-aided system, a technology has been formed for the method of controlling the current trajectories (CTs) of unmanned vehicles (UMVs) when they move along routes in a quarry in open pit mining. The purpose of the presented studies is to analyze the application of a wavelet transforms technique to the problem of routing unmanned vehicles when they move along routes within open pit roads. Methodology. The results of modeling certain one-dimensional signals corresponding to the UMV current trajectories when they deviate to the left / right from a nominal axial trajectory (NAT), as well as their time-frequency representations in a wavelet medium are presented. An algorithm of the procedure for displaying scalar UMV CT control signals in a complex medium of time-frequency wavelet transforms has been developed and described. Such a transformation allows for a functionally transparent and information-capacious monitoring of the UMV movement and efficiently manage the processes of trajectory routing dump trucks in an open pit. Research results, analysis. The processes of modifying the UMV movement current trajectories under the control of the computer-aided system are generated using wavelet transforms methods. They are based on algorithms for projecting the trajectory signals with a time-dependent frequency (chirp signals) onto a set of wavelet functions as part of a wavelet thesaurus (wavelet dictionary), executing certain wavelet matching pursuit procedures, and displaying the CT scalar signals in a specific multidimensional medium of Cohen’s class time-frequency distributions. The simulation results in the form of the current trajectory (CT-) signals waveforms and their three-dimensional time-frequency representations as Wigner maps showing the UMV movement in a start-stop mode, as well as the signals of formed continuous deviation trajectories when they leave to the left and to the right from the NAT, are presented. An algorithm for the formation of 3D-representations of UMV current trajectory one-dimensional signals is presented. Conclusion. The conclusion is made that the mathematical technique of wavelet transforms is the most expedient and effective means for computer-aided monitoring and controlling the dynamics of UMV movement along routes within open pit roads.

scholarly journals Orthogonal-based wavelet analysis of wind turbulence and correlation between turbulence and forces

2007 ◽  
Vol 29 (2) ◽  
pp. 73-82 ◽  
Author(s):  
Le Thai Hoa ◽  
Nguyen Dong Anh
Keyword(s):  
Wavelet Transforms ◽  
Discrete Wavelet ◽  
Time Frequency ◽  
Existing Problems ◽  
Physical Measurements ◽  
Force Relation ◽  
Wind Turbulence ◽  
Time Frequency Localization ◽  
Physical Simulations ◽  
Wavelet Decompositions

Recent models of wind turbulence and turbulence-force relation as well still contain uncertainties. Further studies on them are needed to gain the better knowledge to refine the existing problems from analytical computations to wind tunnel's physical simulations in the wind engineering. The continuous and discrete wavelet transforms have been applied as powerful transformation tools to represent time series into the time-frequency localization. This paper will apply the orthogonal-based wavelet decomposition to investigate the intermittency of the turbulence and to detect the turbulence-force correlation in the both temporal-spectral information using proposed cross energy of wavelet decompositions. Analyzing data have been obtained by physical measurements on model from the wind tunnel tests.

scholarly journals Design and construction of a prototype for the analysis of vibrations in an induction motor for the detection of faults

2020 ◽  
pp. 27-33
Author(s):  
Javier Garrido ◽  
Beatris Escobedo-Trujillo ◽  
Guillermo Miguel Martínez-Rodríguez ◽  
Oscar Fernando Silva-Aguilar
Keyword(s):  
Fourier Transform ◽  
Induction Motor ◽  
Wavelet Transforms ◽  
Data Acquisition System ◽  
Time Frequency ◽  
Different Types ◽  
Control Devices ◽  
The Fourier Transform ◽  
And Control ◽  
Types Of Faults

The contribution of this work is to present the design of a prototype integrated by an induction motor, a data acquisition system, accelerometers and control devices for stop and start, to generate and identify different types of faults by means of vibration analysis. in the domain: time, frequency or frequency-time, through the use of the Fourier Transform, Fast Fourier Transform or Wavelet Transforms (wavelet transform). In this prototype, failures can be generated in the induction motor such as: unbalance, different types of misalignment, mechanical looseness, and electrical failures such as broken bars or short-circuited rings, an example of a misalignment failure is presented to show the process of analysis and detection.

scholarly journals EEG and Sonic Platforms to Enhance Mindfulness Meditation

2016 ◽  
Vol 5 (9) ◽  
pp. 1
Author(s):  
Caitilin De Berigny ◽  
Freya Zinovieff ◽  
Karen Cochrane ◽  
Youngdong Kim ◽  
Zhepeng Rui
Keyword(s):  
Clinical Practice ◽  
Mindfulness Meditation ◽  
Interactive Design ◽  
Historical Background ◽  
Technology Research ◽  
Interactive Installation ◽  
Interactive Applications ◽  
Physiological Processes ◽  
Electroencephalogram Eeg ◽  
The Brain

<p>This paper explores interactive applications that encourage mindfulness through sensors and novel input technology. Research in psychology and neuroscience demonstrating the benefits of mindfulness is initiating a new movement in interactive design. As cutting edge technologies become more accessible they are being employed to research and explore the practice of mindfulness. We examine three interactive installation artworks that promote mindfulness. In order to contextualize the interactive artworks discussed we first examine the historical background of the Electroencephalogram (EEG). We then discuss the physiological processes of meditation and the history behind the clinical practice of mindfulness. We show how artists and designers employ EEG sensors, to record the electrical activity of the brain to visualize mindfulness meditation practices. Lastly, we conclude the paper by discussing the future of the three artworks.</p>

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