3707 Real-time human condition monitoring using moving point correlation dimension analysis

The proceedings of the JSME annual meeting ◽

10.1299/jsmemecjo.2008.5.0_247 ◽

2008 ◽

Vol 2008.5 (0) ◽

pp. 247-248

Author(s):

Akio SUZUKI ◽

Naoki ICHIKAWA

Keyword(s):

Real Time ◽

Condition Monitoring ◽

Correlation Dimension ◽

Human Condition ◽

Dimension Analysis ◽

Point Correlation ◽

Point Correlation Dimension

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Point correlation dimension analysis of void fraction time series

The proceedings of the JSME annual meeting ◽

10.1299/jsmemecjo.2003.2.0_315 ◽

2003 ◽

Vol 2003.2 (0) ◽

pp. 315-316

Author(s):

Akio SUZUKI ◽

Masaki MISAWA ◽

Akihiko MINATO

Keyword(s):

Time Series ◽

Void Fraction ◽

Correlation Dimension ◽

Dimension Analysis ◽

Point Correlation ◽

Point Correlation Dimension

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Working memory load and EEG-dynamics as revealed by point correlation dimension analysis

International Journal of Psychophysiology ◽

10.1016/s0167-8760(99)00039-2 ◽

1999 ◽

Vol 34 (1) ◽

pp. 89-102 ◽

Author(s):

Gebhard Sammer

Keyword(s):

Working Memory ◽

Correlation Dimension ◽

Memory Load ◽

Working Memory Load ◽

Dimension Analysis ◽

Point Correlation ◽

Point Correlation Dimension

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Fractal Dimension of Microseismic Events via the Two-Point Correlation Dimension, and its Correlation with b Values

4th EAGE Passive Seismic Workshop ◽

10.3997/2214-4609.20142359 ◽

2013 ◽

Author(s):

J.P. Verdon

Keyword(s):

Fractal Dimension ◽

Correlation Dimension ◽

B Values ◽

Point Correlation ◽

Microseismic Events ◽

Point Correlation Dimension

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Validating Differential Dermal Potentials for use in Real-time Human Condition Monitoring

IEEE Transactions on Instrumentation and Measurement ◽

10.1109/tim.2022.3141145 ◽

2022 ◽

pp. 1-1

Author(s):

Arindam Sarkar ◽

Bhaswati Goswami ◽

Ratna Ghosh

Keyword(s):

Real Time ◽

Condition Monitoring ◽

Human Condition

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S1601-1-3 Real-time human condition monitoring by nonlinear time series analysis

The proceedings of the JSME annual meeting ◽

10.1299/jsmemecjo.2009.5.0_175 ◽

2009 ◽

Vol 2009.5 (0) ◽

pp. 175-176

Author(s):

Akio SUZUKI ◽

Yoshitomi MORIKAWA ◽

Souhei MATSUMOTO

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Real Time ◽

Condition Monitoring ◽

Nonlinear Time Series ◽

Human Condition ◽

Nonlinear Time Series Analysis ◽

Series Analysis

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Quantitative Analysis of Two-Phase Flow Time Series Based on Optimal Orbit Reconstruction and Point Correlation Dimension

TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series B ◽

10.1299/kikaib.72.590 ◽

2006 ◽

Vol 72 (715) ◽

pp. 590-597

Author(s):

Akio SUZUKI ◽

Masaki MISAWA ◽

Akihiko MINATO

Keyword(s):

Time Series ◽

Quantitative Analysis ◽

Correlation Dimension ◽

Two Phase Flow ◽

Flow Time ◽

Two Phase ◽

Point Correlation ◽

Point Correlation Dimension

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P36.11 Point correlation dimension (PD2) changes after olfactory and gustatory stimulation

Clinical Neurophysiology ◽

10.1016/j.clinph.2006.06.622 ◽

2006 ◽

Vol 117 ◽

pp. 182

Author(s):

T. Járdánházy ◽

A. Járdánházy ◽

J. Tajti ◽

L. Vécsei

Keyword(s):

Correlation Dimension ◽

Point Correlation ◽

Gustatory Stimulation ◽

Point Correlation Dimension

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Improvement of Reliability of Two-phase Flow Characterization by Point Correlation Dimension Analysis and Verification Using Submerged Nozzle Pressure Fluctuation Time Series

TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series B ◽

10.1299/kikaib.70.896 ◽

2004 ◽

Vol 70 (692) ◽

pp. 896-903

Author(s):

Akio SUZUKI

Keyword(s):

Time Series ◽

Pressure Fluctuation ◽

Correlation Dimension ◽

Two Phase Flow ◽

Two Phase ◽

Flow Characterization ◽

Dimension Analysis ◽

Nozzle Pressure ◽

Point Correlation

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Point correlation dimension can reveal functional changes caused by gap junction blockers in the 4-aminopyridine in vivo rat epilepsy model

Chaos Solitons & Fractals ◽

10.1016/j.chaos.2007.07.099 ◽

2009 ◽

Vol 40 (1) ◽

pp. 286-297

Author(s):

Anett Járdánházy ◽

Márk Molnár ◽

Tamás Járdánházy

Keyword(s):

Gap Junction ◽

Correlation Dimension ◽

Functional Changes ◽

Point Correlation ◽

Point Correlation Dimension

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The point correlation dimension of R-R intervals predicts sudden cardiac death among high-risk patients

Proceedings of Computers in Cardiology Conference ◽

10.1109/cic.1993.378455 ◽

2002 ◽

Author(s):

T. Vybiral ◽

J.E. Skinner

Keyword(s):

High Risk ◽

Sudden Cardiac Death ◽

Cardiac Death ◽

Correlation Dimension ◽

High Risk Patients ◽

Risk Patients ◽

Point Correlation ◽

Point Correlation Dimension

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