Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 4 de 4
Filtrar
Añadir filtros








Intervalo de año
1.
Journal of Biomedical Engineering ; (6): 281-290, 2019.
Artículo en Chino | WPRIM | ID: wpr-774209

RESUMEN

The requirement for unconstrained monitoring of heartbeat during sleep is increasing, but the current detection devices can not meet the requirements of convenience and accuracy. This study designed an unconstrained ballistocardiogram (BCG) detection system using acceleration sensor and developed a heart rate extraction algorithm. BCG is a directional signal which is stronger and less affected by respiratory movements along spine direction than in other directions. In order to measure the BCG signal along spine direction during sleep, a 3-axis acceleration sensor was fixed on the bed to collect the vibration signals caused by heartbeat. An approximate frequency range was firstly assumed by frequency analysis to the BCG signals and segmental filtering was conducted to the original vibration signals within the frequency range. Secondly, to identify the true BCG waveform, the accurate frequency band was obtained by comparison with the theoretical waveform. The J waves were detected by BCG energy waveform and an adaptive threshold method was proposed to extract heart rates by using the information of both amplitude and period. The accuracy and robustness of the BCG detection system proposed and the algorithm developed in this study were confirmed by comparison with electrocardiogram (ECG). The test results of 30 subjects showed a high average accuracy of 99.21% to demonstrate the feasibility of the unconstrained BCG detection method based on vibration acceleration.


Asunto(s)
Humanos , Aceleración , Balistocardiografía , Electrocardiografía , Frecuencia Cardíaca , Procesamiento de Señales Asistido por Computador , Vibración
2.
Journal of Biomedical Engineering ; (6): 834-840, 2019.
Artículo en Chino | WPRIM | ID: wpr-774135

RESUMEN

In order to solve imperfection of heart rate extraction by method of traditional ballistocardiogram (BCG), this paper proposes an improved method for detecting heart rate by BCG. First, weak cardiac activity signals are acquired in real time by embedded sensors. Local BCG beats are obtained by signal filtering and signal conversion. Second, the heart rate is estimated directly from the BCG beat without the use of a heartbeat template. Compared with other methods, the proposed method has strong advantages in heart rate data accuracy and anti-interference, and it also realizes non-contact online detection. Finally, by analyzing the data of more than 20,000 heart rates of 13 subjects, the average beat error was 0.86% and the coverage was 96.71%. It provides a new way to estimate heart rate for hospital clinical and home care.


Asunto(s)
Humanos , Algoritmos , Balistocardiografía , Frecuencia Cardíaca , Procesamiento de Señales Asistido por Computador
3.
Journal of Biomedical Engineering ; (6): 7-15, 2019.
Artículo en Chino | WPRIM | ID: wpr-773325

RESUMEN

Simultaneous recording of electroencephalogram (EEG)-functional magnetic resonance imaging (fMRI) plays an important role in scientific research and clinical field due to its high spatial and temporal resolution. However, the fusion results are seriously influenced by ballistocardiogram (BCG) artifacts under MRI environment. In this paper, we improve the off-line constrained independent components analysis using real-time technique (rt-cICA), which is applied to the simulated and real resting-state EEG data. The results show that for simulated data analysis, the value of error in signal amplitude (Er) obtained by rt-cICA method was obviously lower than the traditional methods such as average artifact subtraction ( <0.005). In real EEG data analysis, the improvement of normalized power spectrum (INPS) calculated by rt-cICA method was much higher than other methods ( <0.005). In conclusion, the novel method proposed by this paper lays the technical foundation for further research on the fusion model of EEG-fMRI.

4.
Journal of Biomedical Engineering ; (6): 727-732, 2018.
Artículo en Chino | WPRIM | ID: wpr-687570

RESUMEN

Ballistocardiogram (BCG) and electrocardiogram (ECG) can realize the detection of cardiac function from mechanical and electrical dimensions respectively. By extracting the corresponding characteristic parameters of the two signals and carrying out joint analysis, an important cardiac physiological index such as cardiac contractility, can be reflected. To overcome the shortcomings of complication and heaviness of the existing acquisition equipment, a wearable BCG-ECG signal acquisition system is designed in this paper, which realizes BCG signal acquisition based on accelerometer and ECG signal acquisition based on conductive rubber electrodes. The signals of 6 healthy persons were collected, and BCG signals collected by piezoelectric films were used as reference signals. The waveform characteristics of signals were compared, and the difference of cardiac cycle acquisition was analyzed. The waveform characteristics of the two signals acquired by the device were consistent with the standard signals, and there was no significant difference in the acquisition of the cardiac cycle between the proposed method and the traditional method. The results show that the system can accurately collect human BCG signals and ECG signals. The system provides a basis for subsequent research on BCG signal formation mechanism and health applications.

SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA