Seismocardiography: An alternate method to estimate electro-mechanical window
01 Jan 2016-pp 136-139
TL;DR: In this article, the authors presented a novel system to estimate the electromechanical (E-M) window using seismocardiogaphy (SCG) in replacement of the phonocardiography (PCG).
Abstract: Analysis of electromechanical (E-M) window provides an early marker of several cardiovascular diseases. The E-M window is defined as the duration between the electrical systole (QT) and the mechanical systole (QS2). Traditional methods for the estimation of the electrical systole and the mechanical systole are electrocardiography (ECG) and phonocardiography (PCG). PCG is a widely used method due its features such as portability and cost effectiveness. However, it needs to be improvise in terms of its size and weight, to make it convenient to wear for long-term. Further, the PCG signal is susceptible to various noises, which limits its use in clinical environment. Henceforth, in this paper, we presented a novel system to estimate the E-M window using seismocardiogaphy (SCG) in replacement of the PCG. The SCG uses a sensor called accelerometer, which is small in size and low weight and hence it is convenient to wear. Furthermore, it does not require a microphone, as required in case of the PCG, and hence it is robust to environmental noises. We analysed the performance of the proposed system compared to the PCG, for the estimation of the E-M window. For this purpose ECG, PCG, and SCG signals are acquired simultaneously, for 10 subjects and then validated the obtained results using Bland-Altman plots. Results show that the proposed method is a suitable alternative to estimate the E-M window.
Citations
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01 Jan 2002
TL;DR: Congestive heart failure and hypertension also provide important lessons about the adverse effects of sympathetic predominance, as well as illustrate the benefits of beta-blockers and angiotensin-converting enzyme inhibitors, 2 classes of drugs that reduce adrenergic tone.
Abstract: Chronic imbalance of the autonomic nervous system is a prevalent and potent risk factor for adverse cardiovascular events, including mortality. Although not widely recognized by clinicians, this risk factor is easily assessed by measures such as resting and peak exercise heart rate, heart rate recovery after exercise, and heart rate variability. Any factor that leads to inappropriate activation of the sympathetic nervous system can be expected to have an adverse effect on these measures and thus on patient outcomes, while any factor that augments vagal tone tends to improve outcomes. Insulin resistance, sympathomimetic medications, and negative psychosocial factors all have the potential to affect autonomic function adversely and thus cardiovascular prognosis. Congestive heart failure and hypertension also provide important lessons about the adverse effects of sympathetic predominance, as well as illustrate the benefits of β-blockers and angiotensin-converting enzyme inhibitors, 2 classes of drugs that reduce adrenergic tone. Other interventions, such as exercise, improve cardiovascular outcomes partially by increasing vagal activity and attenuating sympathetic hyperactivity.
386 citations
14 Jan 2019
TL;DR: This paper reviews the recent advances in the field of SCG and focuses on developing proper signal processing algorithms for noise reduction, and SCG signal feature extraction and classification.
Abstract: Cardiovascular disease is a major cause of death worldwide. New diagnostic tools are needed to provide early detection and intervention to reduce mortality and increase both the duration and quality of life for patients with heart disease. Seismocardiography (SCG) is a technique for noninvasive evaluation of cardiac activity. However, the complexity of SCG signals introduced challenges in SCG studies. Renewed interest in investigating the utility of SCG accelerated in recent years and benefited from new advances in low-cost lightweight sensors, and signal processing and machine learning methods. Recent studies demonstrated the potential clinical utility of SCG signals for the detection and monitoring of certain cardiovascular conditions. While some studies focused on investigating the genesis of SCG signals and their clinical applications, others focused on developing proper signal processing algorithms for noise reduction, and SCG signal feature extraction and classification. This paper reviews the recent advances in the field of SCG.
145 citations
Cites methods from "Seismocardiography: An alternate me..."
...[57] showed that SCG is a suitable alternative to PCG for estimating the EMw....
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01 Jan 2018
19 citations
Cites background or methods from "Seismocardiography: An alternate me..."
...[67] 3-MEMS-Acc MMA 7361, Freescale Semiconductor above xiphoid...
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...[67] showed that SCG is a suitable alternative for PCG for estimating the EMw....
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26 Jun 2019
TL;DR: A smart textile based on fiber Bragg grating (FBG) sensor has been proposed to detect the precordial motions on the chest and promising results foster future investigations on the capability and performance of the system in estimating heart rate.
Abstract: In recent years, wearables are exploding in popularity as unobtrusive devices able to extend traditional healthcare delivery systems. Smart textiles are one of the main innovative types of wearables used for non-invasive and continuous monitoring of cardiac activity. A prominent solution is based on the detection of vibrations induced on the chest surface by the heart beating (i.e., precordial motions). In the literature, different sensor positions have been investigated, but it appears to be a lack of accepted standard points for the detection of heart-induced motions. In this work, a smart textile based on fiber Bragg grating (FBG) sensor has been proposed to detect the precordial motions on the chest. The feasibility of the smart textile for cardiac monitoring has been evaluated on three volunteers at three measurement points. Then, the influence of the measurement site on the response of the smart textile has been preliminarily assessed in terms of peak-to-peak amplitude of the signal. The signal amplitude is greater than the noise, so it allows detecting precordial motions. These promising results foster future investigations on the capability and performance of the system in estimating heart rate. Further tests will also be devoted to finding out the optimal measurement points to standardize the sensors positioning in this specific application.
12 citations
Cites methods from "Seismocardiography: An alternate me..."
...The most popular techniques used for SCG monitoring are based on accelerometers placed on the thorax [24]–[27]....
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01 Jun 2022
TL;DR: In this paper , a wearable device for monitoring heart health is presented, which consists of three sensors to monitor electrocardiogram (ECG), phonocardiogram (PCG), and seismocardiograms (SCG) signals, and a microcontroller module with Bluetooth wireless connectivity.
Abstract: Heart disease is a major public health problem and one of the leading causes of death worldwide. Therefore, cardiac monitoring is of great importance for early detection and prevention of adverse conditions. Recently, there has been extensive research interest in long-term, continuous, and non-invasive cardiac monitoring using wearable technology. Here we introduce a wearable device for monitoring heart health. This prototype consists of three sensors to monitor electrocardiogram (ECG), phonocardiogram (PCG), and seismocardiogram (SCG) signals, and a microcontroller module with Bluetooth wireless connectivity. Our preliminary results show that the device can record all three signals in real time. In our initial attempt at signal processing, a recurrent neural network (RNN) based machine learning algorithm, Long Short-Term Memory (LSTM), is used to monitor and identify key features in the ECG data. The next phase of our research will include cross-examination of all three sensor signals, development of machine learning algorithms on PCG and SCG signals, and continuous improvement of the wearable device.
References
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37,017 citations
"Seismocardiography: An alternate me..." refers methods in this paper
...The threshold is obtained using Otsu’s threshold method [23], which selects a threshold such that the intra-class variance will be minimum....
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TL;DR: The 95% limits of agreement, estimated by mean difference 1.96 standard deviation of the differences, provide an interval within which 95% of differences between measurements by the two methods are expected to lie.
Abstract: Agreement between two methods of clinical measurement can be quantified using the differences between observations made using the two methods on the same subjects. The 95% limits of agreement, estimated by mean difference +/- 1.96 standard deviation of the differences, provide an interval within which 95% of differences between measurements by the two methods are expected to lie. We describe how graphical methods can be used to investigate the assumptions of the method and we also give confidence intervals. We extend the basic approach to data where there is a relationship between difference and magnitude, both with a simple logarithmic transformation approach and a new, more general, regression approach. We discuss the importance of the repeatability of each method separately and compare an estimate of this to the limits of agreement. We extend the limits of agreement approach to data with repeated measurements, proposing new estimates for equal numbers of replicates by each method on each subject, for unequal numbers of replicates, and for replicated data collected in pairs, where the underlying value of the quantity being measured is changing. Finally, we describe a nonparametric approach to comparing methods.
7,976 citations
"Seismocardiography: An alternate me..." refers methods in this paper
...Bland-Altman’s plot is a statistical method used to assess the relative agreement between two measurements, measured on the same scale [24]....
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TL;DR: In the Global Burden of Disease Study 2013 (GBD 2013) as discussed by the authors, the authors used the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data.
5,792 citations
01 Jan 2002
TL;DR: Congestive heart failure and hypertension also provide important lessons about the adverse effects of sympathetic predominance, as well as illustrate the benefits of beta-blockers and angiotensin-converting enzyme inhibitors, 2 classes of drugs that reduce adrenergic tone.
Abstract: Chronic imbalance of the autonomic nervous system is a prevalent and potent risk factor for adverse cardiovascular events, including mortality. Although not widely recognized by clinicians, this risk factor is easily assessed by measures such as resting and peak exercise heart rate, heart rate recovery after exercise, and heart rate variability. Any factor that leads to inappropriate activation of the sympathetic nervous system can be expected to have an adverse effect on these measures and thus on patient outcomes, while any factor that augments vagal tone tends to improve outcomes. Insulin resistance, sympathomimetic medications, and negative psychosocial factors all have the potential to affect autonomic function adversely and thus cardiovascular prognosis. Congestive heart failure and hypertension also provide important lessons about the adverse effects of sympathetic predominance, as well as illustrate the benefits of β-blockers and angiotensin-converting enzyme inhibitors, 2 classes of drugs that reduce adrenergic tone. Other interventions, such as exercise, improve cardiovascular outcomes partially by increasing vagal activity and attenuating sympathetic hyperactivity.
386 citations
"Seismocardiography: An alternate me..." refers background in this paper
...The E-M window provides early risk indicators for several cardiovascular diseases [4]....
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...The E-M window also represents a reliable and sensitive index of autonomic tone change [6], [11], which is a risk indicator of sever ventricular arrhythmia and sudden death [4]....
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