On the direction and manifest size of the variations of potential in the human heart and on the influence of the position of the heart on the form of the electrocardiogram

Einthoven, W.; Fahr, George; Waart, A. de

doi:10.1016/0002-8703(50)90165-7

Cited by 161 publications

(49 citation statements)

References 2 publications

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“…• Body posture: A factor that has been marginally examined in the prior art is the effect of body posture. The electrical heart vector changes in relation to body position [50]. Using limb leads, this work demonstrated that body position influences the cardiac response.…”

Section: Benchmark Testing Techniquesmentioning

confidence: 76%

On Evaluating ECG Biometric Systems: Session-Dependence and Body Posture

Wahabi

Pouryayevali

Hari

et al. 2014

IEEE Trans.Inform.Forensic Secur.

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This paper addresses the challenges of evaluating electrocardiogram (ECG) biometric recognition systems. While this new biometric modality has attracted significant interest, a majority of the prior art has approached it from the perspective of a typical biometric modality and has neglected the physiological factors that directly affect the behavior of the respective systems. In an effort to bring to the table the idiosyncratic properties of the ECG biometric modality, this paper presents the UofT ECG database and offers a comprehensive analysis of the underlying interindividual variability under a number of conditions, such as body posture, physical activity, and time lapse. The performance of various methodologies is reported under the above-mentioned conditions and a method based on template fusion is proposed to address these shortcomings.

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Section: Benchmark Testing Techniquesmentioning

confidence: 76%

On Evaluating ECG Biometric Systems: Session-Dependence and Body Posture

Wahabi

Pouryayevali

Hari

et al. 2014

IEEE Trans.Inform.Forensic Secur.

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“…The effects on the ECG of heart displacements produced by respiratory movements were first systematically analyzed by Einthoven et al [6]. In this classic paper, most of the changes in ECG amplitude and waveform were Manuscript attributed to these movements and to respiratory-induced cardiac rhythm variations.…”

Section: Effects Of Respiration On the Frontal Ecgmentioning

confidence: 99%

The effect of respiration-induced heart movements on the ECG

Pallás-Areny¹,

Colominas-Balague²,

Rosell³

1989

IEEE Trans. Biomed. Eng.

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Abstruct-We present a model describing the rotation of the cardiac vector as a possible mechanism resulting in the presence of respiratory information in the ECG. The way in which this information is revealed is analyzed and the predictions subjected to qualitative experimental assessment via spectral analysis.The results show that respiratory frequencies occur in the ECG spectrum due to heart movement. By measuring on a patient wearing a pacemaker and ventilated to control respiratory rate we show that even in the absence of respiratory sinus arrhythmia (RSA) there is a baseband information in the ECG spectrum, attributable neither to electrode artifacts nor to emg, and sidebands from the respiratory cycle.

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“…The effect of respiration-induced heart displacement on the ECG was first studied by Einthovan et al [1] and quantified further in [2], [3]. It is also evident from the literature that, the intraaortic blood pressure (ABP) signals are also modulated by respiratory activity [4].…”

mentioning

confidence: 98%

Estimation of respiration rate from ECG, BP and PPG signals using empirical mode decomposition

Madhav

Ram

Krishna

et al. 2011

2011 IEEE International Instrumentation and Measurement Technology Conference

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Estimation of respiration rates from electrocardiogram (ECG), blood pressure (BP) and photoplethysmographic (PPG) signals would be an alternative approach for obtaining respiration related information. This process is useful in situations when, ECG, BP and PPG but not respiration is routinely monitored or in cases where, the cardiac arrhythmias are to be studied in correlation with respiratory information and is extremely important. There have been several efforts on ECG-Derived Respiration (EDR), BP-Derived Respiration (BDR) and PPG Derived Respiration (PDR). These methods are based on different signal processing techniques like filtering, wavelets and other statistical methods, which work by extraction of respiratory trend embedded into various physiological signals, as an additive component, or an amplitude modulated (AM) component or frequency modulated (FM) component. The proposed method is a robust, yet simple and makes use of derived Intrinsic Mode Functions (IMF) using Empirical Mode Decomposition (EMD). Test results on ECG, BP and PPG signals of the well known MIMIC database fromPhysiobank archive reveal that the proposed EMD method has efficiently extracted respiratory information from ECG, BP and PPG signals. The evaluated similarity parameters in both time and frequency domains for original and estimated respiratory rates have shown the superiority of the method.

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On the direction and manifest size of the variations of potential in the human heart and on the influence of the position of the heart on the form of the electrocardiogram

Cited by 161 publications

References 2 publications

On Evaluating ECG Biometric Systems: Session-Dependence and Body Posture

On Evaluating ECG Biometric Systems: Session-Dependence and Body Posture

The effect of respiration-induced heart movements on the ECG

Estimation of respiration rate from ECG, BP and PPG signals using empirical mode decomposition

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