A chair based ballistocardiogram time interval measurement with cardiovascular provocations

Rajala, Satu; Ahmaniemi, Teemu; Lindholm, Harri; Müller, Kiti; Taipalus, Tapio

doi:10.1109/embc.2018.8513455

Cited by 3 publications

(3 citation statements)

References 21 publications

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“…In the system, two points are taken, and the time between two measurements is calculated. These measurements include electrocardiography (ECG) [55,56], PPG, phonocardiography (PCG) [57][58][59], ballistocardiography (BCG) [60][61][62][63], seismocardiography (SCG) [64][65][66], impedance cardiography (ICG) [67][68][69][70], use of electrical impedance tomography (EIT) [71], and ultrasonic audio signals [72][73][74][75][76]. Figure 2a shows the normal and high blood pressure of the blood in the vessel.…”

Section: Noninvasive Blood Pressure Measurement Using Nonocclusive Mementioning

confidence: 99%

Towards wearable blood pressure measurement systems from biosignals: a review

Şentürk¹,

Polat²,

Yücedağ³

2019

Turk J Elec Eng & Comp Sci

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Blood pressure is the pressure by the blood to the vein wall. High blood pressure, which is called silent death, is the cause of nearly 13% of mortality all over the world. Blood pressure is not only measured in the medical environment, but the blood pressure measurement is also a need for people in their daily life. Blood pressure estimation systems with low error rates have been developed besides the new technologies and algorithms. Blood pressure measurements are differentiated as invasive blood pressure (IBP) measurement and noninvasive blood pressure (NIBP) measurement methods. Although IBP measurement provides the most accurate results, it cannot be used in daily life because it can only be performed by qualified medical staff with specialized medical equipment. NIBP measurement is based on measuring physiological signals taken from the body and producing results with decision mechanisms. Oscillometric, pulse transit time (PTT), pulse wave velocity, and feature extraction methods are mentioned in the literature as NIBP.In the oscillometric method of the sphygmomanometer, an electrocardiogram is used in PTT methods as a result of the comparison of signals such as electrocardiography, photoplethysmography, ballistocardiography, and seismocardiography.The increase in the human population and worldwide deaths due to the highly elevated blood pressure makes the need for precise measurements and technological devices more clear. Today, wearable technologies and sensors have been frequently used in the health sector. In this review article, the invasive and noninvasive blood pressure methods, including various biosignals, have been investigated and then compared with each other concerning the measurement of comfort and robust estimation.

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Section: Noninvasive Blood Pressure Measurement Using Nonocclusive Mementioning

confidence: 99%

Towards wearable blood pressure measurement systems from biosignals: a review

Şentürk¹,

Polat²,

Yücedağ³

2019

Turk J Elec Eng & Comp Sci

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“…Recent advances in electronics and sensor technologies have led to a variety of ways to collect BCG signals. Sensors can be embedded in objects such as bed legs (Mitsukura et al, 2020;Jung et al, 2021), mattresses (Hwang et al, 2014), chairs (Rajala et al, 2018), pillows (Sadek et al, 2017), weight scales (Liu et al, 2022), and even a camera (Li et al, 2020) to enable monitoring in a non-sensory state. By eliminating the need for direct contact between the subject and sensors, these methods minimize physical and psychological discomfort.…”

Section: Introductionmentioning

confidence: 99%

Non-invasive monitoring of cardiac function through Ballistocardiogram: an algorithm integrating short-time Fourier transform and ensemble empirical mode decomposition

Feng,

Huang,

Jiang

et al. 2023

Front. Physiol.

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The Ballistocardiogram (BCG) is a vibration signal that is generated by the displacement of the entire body due to the injection of blood during each heartbeat. It has been extensively utilized to monitor heart rate. The morphological features of the BCG signal serve as effective indicators for the identification of atrial fibrillation and heart failure, holding great significance for BCG signal analysis. The IJK-complex identification allows for the estimation of inter-beat intervals (IBI) and enables a more detailed analysis of BCG amplitude and interval waves. This study presents a novel algorithm for identifying the IJK-complex in BCG signals, which is an improvement over most existing algorithms that only perform IBI estimation. The proposed algorithm employs a short-time Fourier transform and summation across frequencies to initially estimate the occurrence of the J wave using peak finding, followed by Ensemble Empirical Mode Decomposition and a regional search to precisely identify the J wave. The algorithm’s ability to detect the morphological features of BCG signals and estimate heart rates was validated through experiments conducted on 10 healthy subjects and 2 patients with coronary heart disease. In comparison to commonly used methods, the presented scheme ensures accurate heart rate estimation and exhibits superior capability in detecting BCG morphological features. This advancement holds significant value for future applications involving BCG signals.

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“…However, these systems do not have an important property of other BCG systems—the ability to monitor cardiovascular data unobtrusively without effort from the user. Truly non-unobtrusive systems include chair-, bed-, video-, or radar-based systems [ 7 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ]. Of these, our team has experience with bed-based systems, and two sample BCGs acquired with a bed system that employs two different sensing technologies (electromechanical films (EMFis) and load cells) are illustrated in Figure 1 along with a time-aligned ECG.…”

Section: Introductionmentioning

confidence: 99%

Bed-Based Ballistocardiography: Dataset and Ability to Track Cardiovascular Parameters

Carlson

Turpin

Suliman

et al. 2020

Sensors

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Background: The goal of this work was to create a sharable dataset of heart-driven signals, including ballistocardiograms (BCGs) and time-aligned electrocardiograms (ECGs), photoplethysmograms (PPGs), and blood pressure waveforms. Methods: A custom, bed-based ballistocardiographic system is described in detail. Affiliated cardiopulmonary signals are acquired using a GE Datex CardioCap 5 patient monitor (which collects ECG and PPG data) and a Finapres Medical Systems Finometer PRO (which provides continuous reconstructed brachial artery pressure waveforms and derived cardiovascular parameters). Results: Data were collected from 40 participants, 4 of whom had been or were currently diagnosed with a heart condition at the time they enrolled in the study. An investigation revealed that features extracted from a BCG could be used to track changes in systolic blood pressure (Pearson correlation coefficient of 0.54 +/− 0.15), dP/dtmax (Pearson correlation coefficient of 0.51 +/− 0.18), and stroke volume (Pearson correlation coefficient of 0.54 +/− 0.17). Conclusion: A collection of synchronized, heart-driven signals, including BCGs, ECGs, PPGs, and blood pressure waveforms, was acquired and made publicly available. An initial study indicated that bed-based ballistocardiography can be used to track beat-to-beat changes in systolic blood pressure and stroke volume. Significance: To the best of the authors’ knowledge, no other database that includes time-aligned ECG, PPG, BCG, and continuous blood pressure data is available to the public. This dataset could be used by other researchers for algorithm testing and development in this fast-growing field of health assessment, without requiring these individuals to invest considerable time and resources into hardware development and data collection.

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A chair based ballistocardiogram time interval measurement with cardiovascular provocations

Cited by 3 publications

References 21 publications

Towards wearable blood pressure measurement systems from biosignals: a review

Towards wearable blood pressure measurement systems from biosignals: a review

Non-invasive monitoring of cardiac function through Ballistocardiogram: an algorithm integrating short-time Fourier transform and ensemble empirical mode decomposition

Bed-Based Ballistocardiography: Dataset and Ability to Track Cardiovascular Parameters

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