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Balistocardiogram(BCG) is a method to record body vibrations caused by heart activity, which can be detected at the spine axis of body by sensitive force sensor. The raw BCG signal is so weak and often involves a lot of noise that some device should be designed to extract a clean BCG signal. According to the characteristics of BCG signal, a new insusceptibility detection and processing system of the...
Ballistocardiogram (BCG) is a new, noninvasive technique used to record the movement of the body synchronous with the heartbeat due to left ventricular pump activity. However, BCG signal is so weak and easy to be jammed. In this paper, we achieved it through the measure system which is made by our BCG laboratory. Then, attempt to detect useful information from noises by chaotic oscillators. Experimental...
Heart beat causes the synchronous body vibration, which can be measured on the spine axis by sensitive force sensor called ballistocardiogram. Ballistocardiogram was a kind of nonstationary physiological signal, which couldn't be analyzed and processed by traditional signal processing method. The generation and acquisition method of ballistocardiogram were explained. As examples of bilinear and linear...
The heart's mechanical activity while pumping out blood causes the vibration of physical and the object connecting with physical. The vibration is rhythmically with the heart rate and record as ballistocardiogram (BCG) on the spinal axis of the body. It is able to know humanpsilas heart rate by measuring the vibration. BCG is weak non-stationary random signal and contains a lot of noise caused by...
This paper presents a measurement of heart signal and analyzes to educe heart rate based on the pressure sensor. The heart pumps out blood and causes the vibration of body and the objects contacted with the body. The pressure sensor transforms the vibration into electrical signals. The electrical signals are put into filters, amplifiers, and other signal processing circuits. Then the output is analyzed...
Several methods of character analysis and classification for pulse condition are studied with the use of statistics theory. There methods are applied to character abstraction. Pulse condition is analyzed in time, frequency and wavelet domain. Two classifications methods are used, namely back-propagation neural network (BPNN) and fuzzy neural network (FNN). Withdrew pulse condition characteristic to...
In this study, we carry out a research of EEG analysis base on sounds of different frequency. Experiment schemes are designed to obtain the EEG data. Wavelet transform decomposes the EEGs into signals of different frequency. Modulus maximum is applied to detect the extrude spots and power spectrum is used to show the power distribution of EEG with frequency. Through studying, analyzing and comparing...
The examined signal of human body's pulse can reflect the complicated signal of pulse. The lead cause to disease is various, the manifestation and change is complicated, therefore the commonly seen pulse condition in clinical always the concurrent pulse which can reflect many aspects of the disease. This paper studies major identification of concurrent pulse based on fuzzy theory and neural networks...
Recognition of electrocardiogram (ECG) is an important area in intensive care. Automatic detection & classification of cardiac arrhythmias is important for diagnosis of cardiac abnormalities. Based on the wavelet transform theory, the wavelet networks have been wildly used for signal representation and classification. In this article, a new adaptive wavelet networks with one perceptron has been...
EEG signal recorded by scalp electrode is a mixture of signals from different brain regions and with noisy signal. Independent component analysis (ICA) is essentially a method for extracting individual signals from mixtures of signals. Time-frequency analysis provides a powerful tool for the analysis of EEG signals. The original EEG signal is divided into independent components, and the noisy components...
A high noisy environment severely contaminates the ECG signal. In this paper, the use of a wavelet transform domain filtering technique as an adaptive de-noising tool, implemented in ECG signal analysis, is presented. The multi-resolution representations of the signal, produced by wavelet transform (WT), are used for signal structure extraction. Experimental results have shown that the implementation...
This paper is about the design of a system that can detect four channel electromyogram (EMG) signals. EMG signals can be acquired, transformed into electrical signals and input into computer through AD acquisition card. The computer then processes the data and the signal figures are displayed on the screen. In the signals processing system various methods integrated such as adaptive filtering, the...
The surface electromyographic (SEMG) signal, which is produced by neural and muscular systems, is a complicated bioelectric signal recorded from skin surface using electrodes. It is very helpful for doctors to analyse the illness of patients. In the paper, four channel SEMG signals from four muscles (palmaris longus, brachioradialis, flexor carpi ulnaris, biceps brachii) are analyzed with wavelet...
Noise always influences on the result of signal-detection, therefore it is a hot topic to detect signal under the low signal-to-noise ratio (SNR) in current detection field. However, it is an intractable problem of signal-detection to extract weak signal under a high noisy environment. Adaptation filter provides a simple and useful way to detect signal. Through measuring and studying, it is possible...
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