| Coronary heart disease (CHD) is a common cardiovascular disease. According to the statistic by world health organization (WHO), there are about 12 million people die from acute miocardial infarction, and one third of them die from CHD. The diagnosis and treatment of CHD are obtained much emphasis. So it is a very significant subject to aid the doctors in exact, quick and easy detection of the high risk group of CHD, and adopt active intervention.Electrocardiogram (ECG) treadmill exercise test is commonly used for the clinical diagnosis of CHD for it is convenient and non-created. The traditional heart function examination tool is touch-tone bicycle ergo-meter. It is expensive, single-function, difficult for update, expensive for maintenance, and inconvenient for communication with computer. In this thesis, according to the biggest ST/ HR slope theory, one computer-controllable, simple, opened ,and flexible heart function detection system was designed which was also based on virtual device technology.This system was made up of up and down machine. Down machine was controlled by PIC16F877A single chip micyoco (SCM). The amplified and filered ECG signal was collected by down machine, then the analog signals was transformed to digital signals, and transferred to up machine by USB interface. The working process of controlling electric circuit for cycle was designed as following. When down machine received the controlling signal for up machine by USB interface, the resistance of cycle was produced under the control of this circuit. Designed ECG collecting modes including a pre amplifier, second-order Butterworth low-pass filter, high-pass filter, and 50Hz double-T trap circuit.The software of up machine is based on the virtual device software LabVIEW from National Instrument Inc. Collected ECG needed to be pretreated by digital filtering. Here two kinds of pretreatments and two kinds of wave recognition arithmetic were adopted. In real-time collecting phase of ECG data, IIR filter and alterable differential threshold method with simple arithmetic and good real-time performance were adopted. In off-line analysis, wavelet transform method was used for the pretreatment of waveform and recognition of feature point. Simulating result and practical detection showed that this arithmetic was of good filter effect and recognizing capability of feature points.This thesis describes how to implement the hardware and software of a heart functions detection experiment system. The experimental system works well in the collection of ECG signal generated by generator. |
