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Medical Sensing Circuit Design And Signal Processing Research

Posted on:2015-03-18Degree:MasterType:Thesis
Country:ChinaCandidate:H ZhuFull Text:PDF
GTID:2268330425988326Subject:Communication and Information System
Abstract/Summary:PDF Full Text Request
Heart sound, respiratory sound and the oxygen saturation in blood are important parameters and indications which reflect physiologic and pathological situation of tissues, such as heart and lung. The auscultation of heart sound and the measure of oxygen saturation in blood are important methods to prevent and diagnose the diseases, such as cardiovascular disease and respiratory system disease. The accuracy of the traditional auscultation system is low because not only some weak signal cannot be auscultated effectively but also its result would be affected by doctor’s own factors. It needs to pierce the blood vessel to collect the blood and meased results can’t be monitored in real time with the traditional system which is expensive and large. The traditional intracranial pressure detection system is not only operated inconveniently but also with low precision. An auscultation system, a pulse oximeter system and a digital intracranial pressure detection system are designed in this paper. This auscultation system monitors the wave shape of heart sound and respiratory sound in real time and identify them automatically, this pulse oximeter system is noninvasive to measure the oxygen saturation in blood in real, and this digital intracranial pressure detection system conveniently monitors the intracranial pressure in real with high-precision.The design of the hardware system and the software system of the medical sense circuit system is expounded detailedly in the paper. The heart sound and respiratory sound auscultation system includes a power module, a sense circuit module, a signal condition circuit module, a single-chip module, RS485module and PC. In this hardware system, the weak signal would be collected, amplified, converted to digital signal, and filtered by the digital filtering method, and then sent to PC and identified automatcailly. In the software system of this single-chip MCU, noise mixed in the heart sound is filtered by digital bandpass, digital band-trap and a wavelet transform filters, and noise in the respiratory sound is filtered by digital bandpass and wavelet transform filters. Then filtered signal is processed with the Matlab software in PC, this system extracts the envelope of the heart sound signal with short-time average energy extraction method and then calculates its eigenvalue with the differential threshold, and the eigenvalue of respiratory sound is calculated with the wavelet packet algorithm, so that the heart sound and the respiratoty sound can be identified automatically.The pulse oximeter system includes a power module, a sense circuit module, a signal condition circuit module, a single-chip module, a light source driving and a control circuit module, LCD monitor module. In this system, the LED can be alternating light and light-off, the signal be collected, amplified, filtered and converted to digital signal, the value of heart rate and the oxygen saturation in blood be calculated and monitored in LCD. Its softerware system is operating in the single-chip MCU, which controls the hardwre system intelligently, locates the peak and valley of the signal with the threshold, and calculates the heart rate value and the value of the oxygen saturation in blood with an empirical formula.The digital intracranial pressure detection system includes a sense circuit module, a signal conditioning circuit module, a single-chip MCU, LCD monitor module and a power module. The pressure signal can be detected, amplified, filtered and converted to digital signal, and the pressure value be calculated and displayed. In its softerware system, a linear regression method and multiple linear approximation are used to correct the error to improve accuracy.
Keywords/Search Tags:heart sound, respiratory sound, blood oxygen saturation, intracranial pressure, digital filtering, sensor, wavelet de-noise method, characteristic value, linear regression, multiple linear approximation
PDF Full Text Request
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