Fluctuation Analysis Of The Heart Rate Related To Instantaneous Lung Volume: A Time Domain Approach

Yana, Kazuo; Saul, J. Philip; Berger, Ronald D.; Perrott, Michael H.; Cohen, Richard J.

doi:10.1109/iembs.1990.691333

Cited by 7 publications

(9 citation statements)

References 5 publications

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“…The filter characteristics are: passband 0-0.7 Hz; stopband 0.9-2.0 Hz; ripple 0.01. A statistically independent high pass filtered noise is added to ILV and SVP envelope for stabilizing the system parameter estimation [6]. For yielding the noise, white Gaussian i.i.d.s are shaped by a FIR filter with the specification: passband 0.9-2.0 Hz; stopband 0-0.7 Hz; ripple 0.01.…”

Section: Signal Processingmentioning

confidence: 99%

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Heart Rate Signal Decomposition

Mizuta

Yana²

2000

Methods Inf Med

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Abstract:This paper proposes a method for decomposing heart rate fluctuations into background, respiratory and blood pressure oriented fluctuations. A signal cancellation scheme using the adaptive RLS algorithm has been introduced for canceling respiration and blood pressure oriented changes in the heart rate fluctuations. The computer simulation confirmed the validity of the proposed method. Then, heart rate fluctuations, instantaneous lung volume and blood pressure changes are simultaneously recorded from eight normal subjects aged 20-24 years. It was shown that after signal decomposition, the power spectrum of the heart rate showed a consistent monotonic 1/fa type pattern. The proposed method enables a clear interpretation of heart rate spectrum removing uncertain large individual variations due to the respiration and blood pressure change.

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Section: Signal Processingmentioning

confidence: 99%

“…h rh , h bh and h hb are set as follows: . These values are determined from previous bivariate analysis [6,9]. ILV signals are generated by the superposition of shifted single respiratory waveform modeled as:…”

Section: Heart Rate Signal Decompositionmentioning

confidence: 99%

Heart Rate Signal Decomposition

Mizuta

Yana²

2000

Methods Inf Med

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“…high-pass filtered white Gaussian noise has been added to the IL V signal to stabilize the estimate of the impulse response. A detailed description and the effect of this noise injection procedure can be found in [3].…”

Section: Uncorrelatedmentioning

confidence: 99%

“…Heart rate variability (HRV) has been extensively studied as a non-invasive means for examining the autonomic nervous activity [1]. Recently, effective procedures to relate HRV to the instantaneous lung volume (IL V) have been proposed in either the frequency [2] or the time domain [3]. Random breathing techniques for data acquisition [2] and noise injection techniques for signal processing [3] play important roles in these data analyses.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, effective procedures to relate HRV to the instantaneous lung volume (IL V) have been proposed in either the frequency [2] or the time domain [3]. Random breathing techniques for data acquisition [2] and noise injection techniques for signal processing [3] play important roles in these data analyses. We extended these earlier methods to one that is applicable to non-stationary data, since it is important to see changes in the relationship between HRV and IL V, such as when examining the gradual effect of an autonomic blocking agent on the HRV, or when examining changes in autonomic activity during a change in posture.…”

Section: Introductionmentioning

confidence: 99%

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Change in Impulse Response of Heart Rate to Instantaneous Lung Volume

Mizuta

Iida²,

Yana³

et al. 1994

Methods Inf Med

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Abstract:A method is presented that relates the heart rate variability (HRV) to the change in instantaneous lung volume (ILV) under non-stationary conditions. Methods utilizing a recursive least squares (RLS) algorithm and a modified Widrow LMS algorithm are proposed to keep track of changes in impulse response of HRV to ILV. Results are presented of real data analysis and a dedicated system is proposed utilizing DSP chips for the real time data processing.

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An Application Of A Neural Network For The Analysis Of Heart Rate Fluctuations Related To Instantaneous Lung Volume

Yana

Okamoto²,

Saul³

et al.

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991

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This paper presents an application of a neural network for the analysis of the heart rate fluctuations. A three layer neural network was trained by the back propagation algorithm to relate fluctuations in heart rate to instantaneous lung volume. Considerable reduction of the residual variance was attained compaired to the optimum linear system as increasing the number of hidden layer units up to 10. The result suggests the involvement of a nonlinear factor in the transfer characteristics from the instantaneous lung volume to heart rate.

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Fluctuation Analysis Of The Heart Rate Related To Instantaneous Lung Volume: A Time Domain Approach

Cited by 7 publications

References 5 publications

Heart Rate Signal Decomposition

Heart Rate Signal Decomposition

Change in Impulse Response of Heart Rate to Instantaneous Lung Volume

An Application Of A Neural Network For The Analysis Of Heart Rate Fluctuations Related To Instantaneous Lung Volume

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