直接给出我ecg_r_peak_detectionecg_q_peak_detectionecg_s_peak_detectionecg_t_peak_detection的函数

好的，以下是基于Python语言实现的心电图峰值检测函数：

import numpy as np
import scipy.signal as signal

def ecg_r_peak_detection(ecg_signal, sampling_rate):
    """
    心电图R波峰值检测函数
    :param ecg_signal: 心电图信号
    :param sampling_rate: 采样率
    :return: r_peak_indices: R波峰值所在样本点位置
    """
    # 1. 低通滤波
    b, a = signal.butter(2, 35 / (sampling_rate / 2), 'lowpass')
    filtered_signal = signal.filtfilt(b, a, ecg_signal)
    # 2. 将信号归一化到[0,1]范围内
    normalized_signal = (filtered_signal - np.min(filtered_signal)) / (np.max(filtered_signal) - np.min(filtered_signal))
    # 3. 直接使用scipy中的find_peaks函数进行峰值检测
    r_peak_indices, _ = signal.find_peaks(normalized_signal, height=0.5, distance=int(0.2 * sampling_rate))
    return r_peak_indices


def ecg_q_peak_detection(ecg_signal, r_peak_indices, sampling_rate):
    """
    心电图Q波峰值检测函数
    :param ecg_signal: 心电图信号
    :param r_peak_indices: R波峰值所在样本点位置
    :param sampling_rate: 采样率
    :return: q_peak_indices: Q波峰值所在样本点位置
    """
    q_peak_indices = []
    for i in range(len(r_peak_indices)):
        # 1. 以R波峰值为中心位置，向前取30ms(即0.03 * sampling_rate个样本点)作为Q波搜索范围
        search_range_left = int(r_peak_indices[i] - 0.03 * sampling_rate)
        search_range_right = r_peak_indices[i]
        if search_range_left < 0:
            search_range_left = 0
        search_range = ecg_signal[search_range_left:search_range_right]
        # 2. 搜索范围内的最小值即为Q波峰值
        q_peak_index = search_range_left + np.argmin(search_range)
        q_peak_indices.append(q_peak_index)
    return q_peak_indices


def ecg_s_peak_detection(ecg_signal, r_peak_indices, sampling_rate):
    """
    心电图S波峰值检测函数
    :param ecg_signal: 心电图信号
    :param r_peak_indices: R波峰值所在样本点位置
    :param sampling_rate: 采样率
    :return: s_peak_indices: S波峰值所在样本点位置
    """
    s_peak_indices = []
    for i in range(len(r_peak_indices)):
        # 1. 以R波峰值为中心位置，向后取30ms(即0.03 * sampling_rate个样本点)作为S波搜索范围
        search_range_left = r_peak_indices[i]
        search_range_right = int(r_peak_indices[i] + 0.03 * sampling_rate)
        if search_range_right > len(ecg_signal) - 1:
            search_range_right = len(ecg_signal) - 1
        search_range = ecg_signal[search_range_left:search_range_right]
        # 2. 搜索范围内的最小值即为S波峰值
        s_peak_index = search_range_left + np.argmin(search_range)
        s_peak_indices.append(s_peak_index)
    return s_peak_indices


def ecg_t_peak_detection(ecg_signal, r_peak_indices, sampling_rate):
    """
    心电图T波峰值检测函数
    :param ecg_signal: 心电图信号
    :param r_peak_indices: R波峰值所在样本点位置
    :param sampling_rate: 采样率
    :return: t_peak_indices: T波峰值所在样本点位置
    """
    t_peak_indices = []
    for i in range(len(r_peak_indices)):
        # 1. 以R波峰值为中心位置，向后取200ms(即0.2 * sampling_rate个样本点)作为T波搜索范围
        search_range_left = r_peak_indices[i]
        search_range_right = int(r_peak_indices[i] + 0.2 * sampling_rate)
        if search_range_right > len(ecg_signal) - 1:
            search_range_right = len(ecg_signal) - 1
        search_range = ecg_signal[search_range_left:search_range_right]
        # 2. 使用scipy中的find_peaks函数进行T波峰值检测
        t_peak_index, _ = signal.find_peaks(search_range, height=0.5, distance=int(0.15 * sampling_rate))
        if len(t_peak_index) > 0:
            t_peak_index = t_peak_index[0] + search_range_left
            t_peak_indices.append(t_peak_index)
    return t_peak_indices

这里实现了基于R波峰值位置的Q、S、T波峰值检测函数，其中使用了scipy库中的滤波和峰值检测函数。请注意，这些函数仅供参考，可能需要根据实际需求进行修改，例如修改滤波器类型、滤波器截止频率、峰值检测参数等等。