Characteristics of magnetocardiography and electrocardiography in the time-frequency domain

Liu, Xinyuan; Pei, Liuqing; Zhang, Suming; Yin, Wang; Dai, Yongheng

doi:10.1007/s11434-010-4066-7

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…Periods are the inverses of frequency at the point of maximum spectral power density SPD max . The half-power bandwidth (W b ) is the width of a spectral peak measured at the half spectral power point SPD max (2) −1/2 (Liu et al, 2011); it is used here as a measure of variability and to derive upper and lower bounds for a given period.…”

Section: Methodsmentioning

confidence: 99%

Quantifying the periodicity of Heinrich and Dansgaard–Oeschger events during Marine Oxygen Isotope Stage 3

Long¹,

Stoy²

2013

Quat. res.

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Data from multiple ice and sediment cores in the North Atlantic show that Marine Oxygen Isotope Stage 3 (MIS 3) was characterized by recurring millennial-scale variations in climate, but the periodic behavior of the well-known millennial-scale variations, Heinrich events and Dansgaard–Oeschger events, is uncertain. We use oxygen isotope values from the Greenland Ice Sheet Project 2 (GISP2) and North Greenland Ice Core Project (NGRIP) ice cores and estimated sea-surface temperature derived from a Bermuda Rise marine sediment core as climate proxies to assess the periodic behavior of Heinrich events and Dansgaard–Oeschger events using Lomb–Scargle spectral decomposition and continuous time autoregressive models. We find that continuous time autoregressive models produce less variable estimates of periodicity for Heinrich events than Lomb–Scargle methods. Heinrich events during MIS 3 are periodic with an estimated periodicity of 6.29–6.49 ka in the GISP 2 ice core, 6.71–6.76 ka in the marine sediment core, and 7.89–8.23 ka in the NGRIP core. There is insufficient evidence from these data to conclude that Dansgaard–Oeschger events exhibit a single periodicity during MIS 3. We also find that the periodic behavior of millennial-scale variations depends on the observational time frame.

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Section: Methodsmentioning

confidence: 99%

Quantifying the periodicity of Heinrich and Dansgaard–Oeschger events during Marine Oxygen Isotope Stage 3

Long¹,

Stoy²

2013

Quat. res.

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“…When the uncertainty principle in the TFD is satisfied, the three-dimensional (3D) evolutionary spectrum that is the local timefrequency power density distribution of an NSS in the neighbourhood for an instant in time, will be obtained. [18] Detailed evolutionary spectrum analysis methods (ESAM) and corresponding algorithms can be found in Refs. [9] and [16].…”

Section: Brief Introduction Of the Evolutionary Spectrummentioning

confidence: 99%

Characteristic parameters of electromagnetic signals from a human heart system

刘新元¹,

裴留庆²,

王寅³

et al. 2011

Chinese Phys. B

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The electromagnetic field of a human heart system is a bioelectromagnetic field. Electrocardiography (ECG) and magnetocardiography (MCG) are both carriers of electromagnetic information about the cardiac system, and they are nonstationary signals. In this study, ECG and MCG data from healthy subjects are acquired; the MCG data are captured using a high-Tc radio frequency superconducting quantum interference device (HTc rf SQUIDs) and the QRS complexes in these data are analysed by the evolutionary spectrum analysis method. The results show that the quality factor Q and the central frequency fz of the QRS complex evolutionary spectrum are the characteristic parameters (CHPs) of ECG and MCG in the time-frequency domain. The confidence intervals of the mean values of the CHPs are estimated by the Student t distribution method in mathematical statistics. We believe that there are threshold ranges of the mean values of Q and fz for healthy subjects. We have postulated the following criterion: if the mean values of CHPs are in the proper ranges, the cardiac system is in a normal condition and it possesses the capability of homeostasis. In contrast, if the mean values of the CHPs do not lie in the proper ranges, the homeostasis of the cardiac system is lacking and some cardiac disease may follow. The results and procedure of MCG CHPs in the study afford a technological route for the application of HTc rf SQUIDs in cardiology.

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“…The power spectrum distribution of the plant electrical signal is related to the transmembrane transportation of various ions, changes in membrane potential, and electrical coupling between cells. It is the result of interactions and coordination among cells [22]. There is a particular power spectrum distribution of the electrical signal when plants are in a particular life stage.…”

mentioning

confidence: 99%

Changes in the power spectrum of electrical signals in maize leaf induced by osmotic stress

Zhang

et al. 2012

Chin. Sci. Bull.

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To quantify the characteristics of the power spectrum of plant electrical signals, we defined the following concepts: spectral edge frequency (SEF), spectral center frequency (SCF), power index (PI) and power spectral entropy (PSE). These parameters were used to examine and quantify changes in the power spectrum of electrical signals in maize leaves under osmotic stress. In the absence of osmotic stress, the SEF of the electrical signal in maize leaves was approx. 0.2 Hz and the SCF was approx. 0.1 Hz. The electrical signal in maize leaves was mainly a slow wave signal with a frequency of 0-0.1 Hz. After 2 h osmotic stress, the SEF and SCF of the electrical signal increased to higher frequencies. The proportion of the fast wave frequency also increased to 0.1-0.2 Hz, resulting in a dramatic increase in PSE. We also found that the changes in PSE and SCF were significantly correlated during osmotic stress. We propose that the changes in the PSE and SCF in maize leaves can be used as a sensitive signal indicating water deficit in leaf cells under osmotic stress. Thus, measurement of SCF or PSE of electrical signals in maize leaves could be used to develop early warning and rapid diagnosis techniques for the water demands of plants. plant electrical signal, power spectrum, osmotic stress, maize Citation: Zhang X H, Yu N M, Xi G, et al. Changes in the power spectrum of electrical signals in maize leaf induced by osmotic stress. Chin Sci Bull, 2012, 57: 413420,In recent years, there has been increasing interest in plant electrical signals. This is because plant electrical signals, chemical signals (phytohormones), mechanical signals, and water signals constitute the plant information system [1,2]. Electrical signals are not only able to rapidly transmit information over long distances within the plant body [1,3,4], but also affect major physiological processes such as respiratory metabolism, photosynthesis, moisture absorption, and stomatal conductance [1,[5][6][7]. It is now generally considered that plants undergoing normal growth and development show fluctuations of potential. On one hand, this reflects the flow of information throughout the tissues and organs of the plant, and on the other, it reflects a level of direct control and regulation of responses to environmental stimuli [3,4,[8][9][10].At present, studies on plant electrical signals focus on two main aspects. One aspect is the production, transmission, reception, and transformation mechanisms of plant electrical signals. The purpose of such studies is to unravel the internal information network of the plant and to understand how plants respond to environmental stimuli; that is, to clarify aspects of plant neurobiology [1,4,[11][12][13]. The other research focus is to understand how plant electrical signals convey information. Plant electrical signals respond quickly to changes in light intensity, osmotic pressure, temperature, mechanical damage, mechanical stimulation, water availability, chemical compounds (i.e., plant growth stimulators or herbicides),...

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Characteristics of magnetocardiography and electrocardiography in the time-frequency domain

Cited by 4 publications

References 13 publications

Quantifying the periodicity of Heinrich and Dansgaard–Oeschger events during Marine Oxygen Isotope Stage 3

Quantifying the periodicity of Heinrich and Dansgaard–Oeschger events during Marine Oxygen Isotope Stage 3

Characteristic parameters of electromagnetic signals from a human heart system

Changes in the power spectrum of electrical signals in maize leaf induced by osmotic stress

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