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Typical SCG waveform with indication of the AO, AC, MO and MC fiducial points, and of the timings used for the estimation of the Cardiac Time Intervals. See text for the explanation of acronyms.
Source publication
Seismocardiogram, SCG, is the measure of precordial vibrations produced by the beating heart, from which cardiac mechanics may be explored on a beat-to-beat basis. We recently collected a large amount of SCG data (>69 recording hours) from an astronaut to investigate cardiac mechanics during sleep aboard the International Space Station and on Earth...
Contexts in source publication
Context 1
... typical SCG waveform, illustrated in Fig. 3, is characterized by a number of peaks and troughs. In particu- lar, some of these displacements are associated with the opening and closure of the aortic valve, AO and AC, and ...
Context 2
... extraction: indexes of cardiac mechanics. As illustrated in Fig. 3, from the R and Q peaks in the ECG and the AO, AC, MO and MC fiducial points in the SCG waveform we may estimate the RR interval, RRI (i.e. the time interval between consecutive R peaks) and the Cardiac Time Intervals, CTIs, considered as indexes of cardiac mechanical function and defined as ...
Context 3
... layers, etc. In detail 1. In each valid ECG complex the position of the R peak was identified and stored. 2. On the basis of the R peak timing, the ECG and the SCG were then split into individual heart beats. We considered as a heart beat a signal segment starting from −200 ms from the relevant R peak till −200 ms from the following R peak (see Fig. 3). The −200 ms offset was adopted to include in the beat also the cor- responding ECG P wave, although this information was not considered in the present study. 3. Gross artifacts were identified by checking the SCG amplitude and variance within each heart beat. Beats with the maximal peak to peak amplitude greater than 50 mg or a ...
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Citations
... Các dạng sóng BCG có thể được nhóm lại thành ba nhóm chính, tức là tiền tâm thu (thường bị bỏ qua), tâm thu và tâm trương. Hình 2. Ví dụ về tín hiệu điện tâm đồ điển hình BCG có thể rất hữu ích trong một số ứng dụng như theo dõi chức năng và hoạt động của tim ngoài việc theo dõi nhịp thở khi ngủ và rối loạn giấc ngủ [3,4]. Một trong những tính năng nổi bật nhất của BCG là khả năng truy cập và tính sẵn sàng, cho phép triển khai hệ thống tại nhà của người dùng mà không ảnh hưởng đến quyền riêng tư và các hoạt động hàng ngày của người dùng. ...
Hiện nay, tín hiệu Ballistocardiogram (BCG) đang nhận được rất nhiều sự quan tâm
nhờ cuộc cách mạng công nghệ thông tin, bao gồm cả công nghệ phần cứng cũng như phần mềm và dịch vụ. Có thể áp dụng cảm biến BCG trong môi trường xung quanh mà không cần sự hiện diện của nhân viên y tế. Do đó, BCG có tác động vượt trội đến các hệ thống y tế điện tử. BCG giúp giảm căng thẳng khi kiểm tra sức
khỏe cũng như phản ứng về cảm xúc và sự chú ý của bệnh nhân. Trong những năm gần đây, các cảm biến BCG đã được tích hợp trong các đồ gia dụng như nệm, gối, ghế, giường, hoặc thậm chí cân trọng lượng, để thu tín hiệu BCG và đo các
dấu hiệu quan trọng. Phân tích tín hiệu BCG là một quá trình đầy thách thức. Bài báo này sẽ giới thiệu các cảm biến đang được sử dụng để thu tín hiệu BCG và trình bày các đánh giá chuyên sâu về một số phương pháp xử lý tín hiệu được áp dụng cho các cảm biến khác nhau, để phân tích tín hiệu BCG và trích xuất các thông
số sinh lý như nhịp tim và nhịp thở, cũng như xác định các giai đoạn của giấc ngủ.
... In addition, to the authors' knowledge, there are not many articles that use SCG to detect sleep-disordered breathing. On the other hand, when used on the International Space Station [199] and at a high altitude [196] for sleep screening, it showed encouraging results. This demonstrates that SCG has the potential to be employed further for this purpose. ...
Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record the micromovements induced by cardiovascular activity at the body’s center of mass and on the chest, respectively. Since their inception, their potential for evaluating cardiovascular health has been studied. However, both BCG and SCG are impacted by respiration, leading to a periodic modulation of these signals. As a result, data processing algorithms have been developed to exclude the respiratory signals, or recording protocols have been designed to limit the respiratory bias. Reviewing the present status of the literature reveals an increasing interest in applying these techniques to extract respiratory information, as well as cardiac information. The possibility of simultaneous monitoring of respiratory and cardiovascular signals via BCG or SCG enables the monitoring of vital signs during activities that require considerable mental concentration, in extreme environments, or during sleep, where data acquisition must occur without introducing recording bias due to irritating monitoring equipment. This work aims to provide a theoretical and practical overview of cardiopulmonary interaction based on BCG and SCG signals. It covers the recent improvements in extracting respiratory signals, computing markers of the cardiorespiratory interaction with practical applications, and investigating sleep breathing disorders, as well as a comparison of different sensors used for these applications. According to the results of this review, recent studies have mainly concentrated on a few domains, especially sleep studies and heart rate variability computation. Even in those instances, the study population is not always large or diversified. Furthermore, BCG and SCG are prone to movement artifacts and are relatively subject dependent. However, the growing tendency toward artificial intelligence may help achieve a more accurate and efficient diagnosis. These encouraging results bring hope that, in the near future, such compact, lightweight BCG and SCG devices will offer a good proxy for the gold standard methods for assessing cardiorespiratory function, with the added benefit of being able to perform measurements in real-world situations, outside of the clinic, and thus decrease costs and time.
... It is clear that the differential sensing approach shows a significant lower variance which means that each individual signal has a higher information content relative to the actual BCG signal. In this paper, we avoid a deeper analysis of the BCG signal and therefore refer to [37], [38] for further details on general BCG signals. However, it is worth mentioning that all relevant physiological parameters are clearly present within the measured signals (e.g. ...
Comprehensive health monitoring is highly relevant
for the safety of manned spaced missions. Ballistocardiography
(BCG) is a method for providing information of the heart
physiology by measuring accelerations on the body surface that
are caused by forwarded heart and blood movements in the
vascular system. In order to provide a sensor system with a high
signal quality, this paper presents differential BCG sensing at the
system level for digital accelerometers and its integration into a
sensing system. The system is part of a running experiment of
the Cosmic Kiss mission on the International Space Station (ISS).
Compared to single sensor solutions, the noise power scales down
to about 50%, the Signal to Noise Ratio (SNR) is increased by a
factor of 1.87 and the BCG signal variability especially improves
for diastole area. Furthermore, by exploiting differential sensing
techniques, both high reliability is achieved and common mode
interference is mitigated, which is of high importance within the
scope of space applications. Beside the presentation of the entire
wireless sensor system including differential sensing approach,
pre-processing unit and Ultra Wideband (UWB) communication
module, results of the pre-flight tests show the performance of
the system as well as the suitability for targeted mission.
... It could be mitigated via identifying the real systolic and diastolic portions of the individual heartbeats by identifying aortic/mitral valve opening and closing points from simultaneously recorded wearable ECG and SCG signals. Although researchers explored different approaches to identify aortic/mitral valve opening and closing points from simultaneously recorded wearable ECG and SCG signals [41][42][43][44][45][46], the generalizability of these approaches remains questionable due to high inter-subject variability in SCG [15]. For example, our previous work demonstrates that general time-domain feature extraction of SCG and advanced machine learning regression algorithms can perform significantly well (p-value < 0.05) in estimating changes in the PEP of the heart due to exercise compared to the traditional method of utilizing SCG characteristic points to estimate PEP via identifying aortic valve opening points [15]. ...
Objective:
Tracking changes in hemodynamic congestion and the consequent proactive readjustment of treatment has shown efficacy in reducing hospitalizations for patients with heart failure (HF). However, the cost-prohibitive nature of these invasive sensing systems precludes their usage in the large patient population affected by HF. The objective of this research is to estimate the changes in pulmonary artery mean pressure (PAM) and pulmonary capillary wedge pressure (PCWP) following vasodilator infusion during right heart catheterization (RHC), using changes in simultaneously recorded wearable seismocardiogram (SCG) signals captured with a small wearable patch.
Methods:
A total of 20 patients with HF (20% women, median age 55 (interquartile range (IQR), 44-64) years, ejection fraction 24 (IQR, 16-43)) were fitted with a wearable sensing patch and underwent RHC with vasodilator challenge. We divided the dataset randomly into a trainingtesting set (n=15) and a separate validation set (n=5). We developed globalized (population) regression models to estimate changes in PAM and PCWP from the changes in simultaneously recorded SCG.
Results:
The regression model estimated both pressures with good accuracies: root-mean-square-error (RMSE) of 2.5 mmHg and R2 of 0.83 for estimating changes in PAM, and RMSE of 1.9 mmHg and R2 of 0.93 for estimating changes in PCWP for the training-testing set, and RMSE of 2.7 mmHg and R2 of 0.81 for estimating changes in PAM, and RMSE of 2.9 mmHg and R2 of 0.95 for estimating changes in PCWP for the validation set respectively.
Conclusion:
Changes in wearable SCG signals may be used to track acute changes in intracardiac hemodynamics in patients with HF.
Significance:
This method holds promise in tracking longitudinal changes in hemodynamic congestion in hemodynamically-guided remote home monitoring and treatment for patients with HF.
... Recorded mitral seismocardiogram-raw and filtered-MatLab ® As previously described, the SCG format may be affected by the location of the sensor in the body, in addition to respiratory movements and other factors. Investigating the effect of these interactions on estimating cardiac time intervals from SCG signals may possibly reveal clinically useful information or simple be used to monitor the breathing [15]. ...
Cardiovascular diseases are the leading cause of death globally. The increase in chronic diseases, such as Diabetes Mellitus and hypertensive heart disease, added to the ageing population, brings in risk factors that increase these statistics. In this scenario, studies related to these diseases are fundamental for the prevention of deaths and for improvements in quality of life. For this purpose, a cardiac monitor was constructed using a piezoelectric transducer as the sensor. The signal was conditioned using Rail-to-Rail amplifiers and digitized by a PIC microcontroller. A computer controls and receives data from the microcontroller through an interface developed on Qt. When data is received, the application presents a seismocardiogram (SCG) waveform on a real-time chart, allowing the user to save data to a file and estimate the heart rate. The developed software also applies a digital filter to reduce interferences in frequencies above 55 Hz. Recorded data were verified using MatLab®. The characteristic points of the SCG were identified in the graphs presented on interface.KeywordsHeart monitorPiezoelectricSCGPICSeismocardiogram
... From every heart beat the following information was obtained: in the BP signal, the systolic (S) and diastolic (D) BP values, defined as the maximal and minimal values of the pressure waveform; in the ECG, the timing of the R peak; in the z-axes acceleration, the occurrence time of the AO fiducial point. The resolution of the above timings was further improved from the original 5 ms (signals are sampled at 200Hz) to 1 ms by signal interpolation and resampling [31]. The Nyquist-Shannon sampling theorem guarantees that this was possible because all signals are bandlimited to 50 Hz as maximum and sampled at 200 Hz, thus the interpolation can accurately reconstruct the signal and allow the time locations of the points of interest at a higher resolution. ...
This study investigates the beat-to-beat relationships among Pulse Transit Times (PTTs) and Pulse Arrival Times (PATs) concomitantly measured from the heart to finger, ear and forehead vascular districts, and their correlations with continuous finger blood pressure. These aspects were explored in 22 young volunteers at rest and during cold pressure test (CPT, thermal stress), handgrip (HG, isometric exercise) and cyclo-ergometer pedalling (CYC, dynamic exercise). The starting point of the PTT measures was the opening of the aortic valve detected by the seismocardiogram. Results indicate that PTTs measured at the ear, forehead and finger districts are uncorrelated each other at rest, and during CPT and HG. The stressors produced district-dependent changes in the PTT variability. Only the dynamic exercise was able to induce significant changes with respect to rest in the PTTs mean values (-40%, -36% and -17%, respectively for PTTear, PTTfore, PTTfinger,), and synchronize their modulations. Similar trends were observed in the PATs. The isovolumic contraction time decreased during the stressors application with a minimum at CYC (-25%) reflecting an augmented heart contractility. The increase in blood pressure (BP) at CPT was greater than that at CYC (137 vs. 128 mmHg), but the correlations between beat-to-beat transit times and BP were maximal at CYC (PAT showed a higher correlation than PTT; correlations were greater for systolic than for diastolic BP). This suggests that pulse transit times do not always depend directly on the beat-to-beat BP values but, under specific conditions, on other factors and mechanisms that concomitantly also influence BP.
... Heart dynamics are routinely studied on ISS and several techniques, which have been or are currently being investigated could be used on the Moon such as ballistocardiography (Migeotte et al., 2011), seismocardiography (Di Rienzo et al., 2017), ultrasound imaging (Sargsyan et al., 2005), pneumography, as well as impedance and electro cardiography (Baevsky et al., 2007(Baevsky et al., , 2009). The measurement of exhaled nitric oxide (NO) has been tested in micro-C. ...
Humans are once again preparing to leave Earth and land on the surface of another planetary body. The two objects high on the list for permanent bases are the Moon and Mars. Both have been at the center of attention of many recent spaceflight activities, albeit these have so far been uncrewed. If humans indeed land on either one of them, science can potentially benefit tremendously.
In the past, most spaceflight missions have been implemented by adding scientific instruments after most of the engineering work is already finished. This has often limited scientific studies to relatively scattered, insular topics. However, if prepared appropriately, a research laboratory on either the Moon or Mars can help address scientific questions thoroughly and at a fundamental level.
In this paper we review the main scientific questions relating to the Moon that are still open and develop an overview of the instrumentation that would be necessary for a human astronaut inside a lunar laboratory to help answer these questions. Our primary focus is the Moon, however, we include an outlook to Mars, since we assume that the Moon not only provides a valuable testbed for many technologies to be used on Mars, but that both can be studied with the same habitat laboratory after some specific adaptations.
The research areas we focus on are related to (a) non-living matter (geophysics, geology, materials science), (b) extraterrestrial life (from chemistry of organic carbon compounds to astrobiology), and (c) life inside the human habitat (bioregenerative life-support systems, microbiomes, human physiology). We identify synergies between disciplines, in order to provide a list of priorities to mission planners, and provide a guideline of where further development of equipment would be desirable.
... BCG-based devices integrated into beds have been shown to be able to monitor HR during sleep and detect apnea episodes [18,19]. Wearable BCG devices have been developed for cardiac monitoring, in which an accelerometer or a gyroscope is positioned such that it rests on the patient's skin [14,[20][21][22][23][24]. Most wearable BCG devices involve the sensor being placed on the wearer's chest, as this is the optimum location for cardiac monitoring [20][21][22][23]. ...
... Wearable BCG devices have been developed for cardiac monitoring, in which an accelerometer or a gyroscope is positioned such that it rests on the patient's skin [14,[20][21][22][23][24]. Most wearable BCG devices involve the sensor being placed on the wearer's chest, as this is the optimum location for cardiac monitoring [20][21][22][23]. However, if the sensors need to be integrated into the mask for PAP therapy monitoring during PAP therapy, the sensors cannot be placed on the chest. ...
... Few devices have been developed for monitoring HR during sleep using only a BCG signal. Di Rienzo et al [23] used a wearable device that contained an accelerometer located on the sternum of the wearer to monitor cardiac intervals during sleep. However, to monitor these intervals, the BCG signal information was combined with an ECG signal that was used to locate and identify the heartbeats. ...
Background
Obstructive sleep apnea (OSA) is a condition in which a person’s airway is obstructed during sleep, thus disturbing their sleep. People with OSA are at a higher risk of developing heart problems. OSA is commonly treated with a positive airway pressure (PAP) therapy device, which is used during sleep. The PAP therapy setup provides a good opportunity to monitor the heart health of people with OSA, but no simple, low-cost method is available for the PAP therapy device to monitor heart rate (HR).
Objective
This study aims to develop a simple, low-cost device to monitor the HR of people with OSA during PAP therapy. This device was then tested on a small group of participants to investigate the feasibility of the device.
MethodsA low-cost and simple device to monitor HR was created by attaching a gyroscope to a PAP mask, thus integrating HR monitoring into PAP therapy. The gyroscope signals were then analyzed to detect heartbeats, and a Kalman filter was used to produce a more accurate and consistent HR signal. In this study, 19 participants wore the modified PAP mask while the mask was connected to a PAP device. Participants lay in 3 common sleeping positions and then underwent 2 different PAP therapy modes to determine if these affected the accuracy of the HR estimation.
ResultsBefore the PAP device was turned on, the median HR error was
... Monitoring techniques based on cardiac-associated vibrations have been proven adequately accurate for heart rate (HR) and heart rate variability (HRV) measurements in healthy subjects with bed-integrated ballistocardiography (BCG) [5], [6], [7] as well as wearable seismocardiography (SCG) sensors [9]. Brüser et al. achieved 0.61 % relative errorĒ rel with 85 % coverage in beat-to-beat interval (BBI) estimation with eight healthy subjects. ...
While bed-integrated ballistocardiography (BCG) has potential clinical applications such as unobtrusive monitoring of patients staying in the general hospital ward, it has so far mainly gained interest in the wellness domain. In this work, the potential of BCG to monitor hospitalized patients after surgical intervention was assessed. Long-term BCG recordings (mean duration 17.7 h) of 14 patients were performed with an EMFit QS bed sensor. In addition, ten healthy subjects were recorded during sleep (mean duration 7.8 h). Using an iterative algorithm, beat-to-beat intervals (BBIs) and the ultra-short-term heart-rate-variability (HRV) parameters standard deviation of NN intervals (SDNN) and root mean square of successive differences (RMSSD) were estimated and compared to an ECG reference in terms of average estimation error and temporal coverage. While the absolute BBI estimation error was found to be higher when full-day patient data was used (16.5 ms), no significant difference between healthy subjects (12.7 ms) and patient nighttime data (11.0 ms) was observed. Nevertheless, temporal coverage of BBI estimation was significantly lower in patients (39.3 % overall, 51.7 % at night) compared to the healthy sleepers (73.2 %). This resulted in reduced HRV estimation coverage (9.7 % vs. 37.2 %) at comparable estimation error levels.
... Continuous monitoring of hospital patients would be beneficial in the detection of deterioration of a patient's condition, which, if achieved early, could enable preventive measures. The BCG technique has been proven adequately accurate for heart rate variability measurement with healthy subjects and bed-integrated [1][2][3] as well as wearable seismocardiography (SCG) sensors [4]. Brüser et al. achieved 0.61 % relative errorĒ rel with 85 % coverage in beat-tobeat interval (BBI) estimation with eight healthy subjects. ...
