Systolic and diastolic cardiac function time intervals and exercise capacity in women

Libonati, Joseph R.; Colby, A. M.; Caldwell, Theodore M.; Kasparian, R.; Glassberg, Helene

doi:10.1097/00005768-199902000-00009

Cited by 14 publications

(15 citation statements)

References 29 publications

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“…In this study, addition of SCG significantly improved the sensitivity of the model when compared to using only exercise (ECG), demographic data and angina status [19]. Libonati and coworkers found that increased exercise capacity, defined as time to exhaustion on a treadmill test, correlated with a lower Tei Index, derived from the SCG [9,20].…”

Section: Introductionmentioning

confidence: 86%

“…The faster pressure drop in the LV causes a larger pressure difference between the LV and the ascending aorta, creating a larger amplitude in the SCG as the aortic valve closes. Libonati and colleagues did not find a significant difference in the timing of IVCT, derived from SCG, but documents that there was a non-significant trend towards shorter LV diastolic time intervals for the group who endured the test for more than 15 minutes [20].…”

Section: Link Between Scg and Cardiorespiratory Fitnessmentioning

confidence: 95%

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A Clinical Method for Estimation of VO2max Using Seismocardiography

et al. 2020

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The purpose of this study was to investigate the correlation between the seismocardiogram and cardiorespiratory fitness. Cardiorespiratory fitness can be estimated as VO2max using non-exercise algorithms, but the results can be inaccurate. Healthy subjects were recruited for this study. Seismocardiogram and electrocardiogram were recorded at rest. VO2max was measured during a maximal effort cycle ergometer test. Amplitudes and timing intervals were extracted from the seismocardiogram and used in combination with demographic data in a non-exercise prediction model for VO2max. 26 subjects were included, 17 females. Mean age: 38.3±9.1 years. The amplitude following the aortic valve closure derived from the seismocardiogram had a significant correlation of 0.80 (p<0.001) to VO2max. This feature combined with age, sex and BMI in the prediction model, yields a correlation to VO2max of 0.90 (p<0.001, 95% CI: 0.83–0.94) and a standard error of the estimate of 3.21 mL·kg−1·min−1 . The seismocardiogram carries information about the cardiorespiratory fitness. When comparing to other non-exercise models the proposed model performs better, even after cross validation. The model is limited when tracking changes in VO2max. The method could be used in the clinic for a more accurate estimation of VO2max compared to current non-exercise methods.

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Section: Introductionmentioning

confidence: 86%

Section: Link Between Scg and Cardiorespiratory Fitnessmentioning

confidence: 95%

A Clinical Method for Estimation of VO2max Using Seismocardiography

et al. 2020

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“…The authors in [ 5 ] measured the left ventricular functions on 58 subjects using SCG and compared with literature; the SCG provided good data for all functions even with exercise while literature did not. The cardiac time intervals measured by SCG and ECG were studied on two groups of 12 women running on treadmill to determine the difference between trained and untrained women [ 6 ]. Doctors in [ 7 ] investigated the systolic time intervals (STIs) with left ventricular ejection time (LVET) and pre-ejection period (PEP) extracted from an accelerometer on the chest of young patients in head upright and tilt testing.…”

Section: Introductionmentioning

confidence: 99%

Artifact Noise Removal Techniques on Seismocardiogram Using Two Tri-Axial Accelerometers

Luu

Dinh

2018

Sensors

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The aim of this study is on the investigation of motion noise removal techniques using two-accelerometer sensor system and various placements of the sensors on gentle movement and walking of the patients. A Wi-Fi based data acquisition system and a framework on Matlab are developed to collect and process data while the subjects are in motion. The tests include eight volunteers who have no record of heart disease. The walking and running data on the subjects are analyzed to find the minimal-noise bandwidth of the SCG signal. This bandwidth is used to design filters in the motion noise removal techniques and peak signal detection. There are two main techniques of combining signals from the two sensors to mitigate the motion artifact: analog processing and digital processing. The analog processing comprises analog circuits performing adding or subtracting functions and bandpass filter to remove artifact noises before entering the data acquisition system. The digital processing processes all the data using combinations of total acceleration and z-axis only acceleration. The two techniques are tested on three placements of accelerometer sensors including horizontal, vertical, and diagonal on gentle motion and walking. In general, the total acceleration and z-axis acceleration are the best techniques to deal with gentle motion on all sensor placements which improve average systolic signal-noise-ratio (SNR) around 2 times and average diastolic SNR around 3 times comparing to traditional methods using only one accelerometer. With walking motion, ADDER and z-axis acceleration are the best techniques on all placements of the sensors on the body which enhance about 7 times of average systolic SNR and about 11 times of average diastolic SNR comparing to only one accelerometer method. Among the sensor placements, the performance of horizontal placement of the sensors is outstanding comparing with other positions on all motions.

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“…The peaks in a seismocardiographic signal coincide with specific cardiac events of the cardiac cycle, such as the opening and closing of the heart valves [4–7]. The amplitude and morphology of seismocardiographic signals may be affected by factors such as respiration [7], cardiac contractility [8], and heart rhythm [9]. The effect of respiration on seismocardiographic signal morphology is shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Untitled

Gurev

Tavakolian²,

Constantino³

et al. 2012

J. Med. Biol. Eng.

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A three-dimensional (3D) finite element electromechanical model of the heart is employed in simulations of seismocardiograms (SCGs). To simulate SCGs, a previously developed 3D model of ventricular contraction is extended by adding the mechanical interaction of the heart with the chest and internal organs. The proposed model reproduces the major peaks of seismocardiographic signals during the phases of the cardiac cycle. Results indicate that SCGs record the pressure of the heart acting on the ribs. In addition, the model reveals that the rotation of the rib with respect to the heart has a minor effect on seismocardiographic signal morphology during the respiratory cycle. SCGs are obtained from 24 human volunteers and their morphology is analyzed. Experimental results demonstrate that the peak of the maximum acceleration of blood in the aorta occurs at the same time as the global minimum of the SCG. It is confirmed that the first SCG peak after the electrocardiogram R-wave corresponds to aortic valve opening, as determined from the impedance cardiogram (p = 0.92). The simulation results reveal that the SCG peaks corresponding to aortic valve opening and the maximum acceleration of blood in the aorta result from ventricular contraction in the longitudinal direction of the ventricles and a decrease in the dimensions of the ventricles due to the ejection of blood, respectively.

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Systolic and diastolic cardiac function time intervals and exercise capacity in women

Abstract: Independent of HR, increased treadmill time in young women is associated with greater resting systolic time intervals and decreased diastolic cardiac function time intervals.

Cited by 14 publications

References 29 publications

A Clinical Method for Estimation of VO2max Using Seismocardiography

A Clinical Method for Estimation of VO2max Using Seismocardiography

Artifact Noise Removal Techniques on Seismocardiogram Using Two Tri-Axial Accelerometers

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