用python实现给定心电数据的P峰和T峰检测

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import find_peaks

data = np.loadtxt('ecg_data.txt')

plt.plot(data)
plt.xlabel('Sample')
plt.ylabel('Amplitude')
plt.title('ECG Signal')
plt.show()

# 使用SciPy库中的滤波函数
from scipy.signal import butter, filtfilt

# 设计低通滤波器
def butter_lowpass(cutoff, fs, order=5):
    nyquist = 0.5 * fs
    normal_cutoff = cutoff / nyquist
    b, a = butter(order, normal_cutoff, btype='low', analog=False)
    return b, a

# 应用滤波器
def butter_lowpass_filter(data, cutoff, fs, order=5):
    b, a = butter_lowpass(cutoff, fs, order=order)
    y = filtfilt(b, a, data)
    return y

# 设置滤波器参数
cutoff = 30.0  # 截止频率
fs = 1000.0  # 采样频率

# 应用滤波器
filtered_data = butter_lowpass_filter(data, cutoff, fs, order=5)

# 使用SciPy库中的峰值检测函数
peaks, _ = find_peaks(filtered_data, distance=100, prominence=0.5)

# 绘制P峰和T峰
plt.plot(filtered_data)
plt.plot(peaks, filtered_data[peaks], 'ro')
plt.xlabel('Sample')
plt.ylabel('Amplitude')
plt.title('ECG Signal with P and T Peaks')
plt.show()