EEG Pre_Processing

normalize.py

import numpy as np

# 加载数据
data = np.load('eeg.npy')

# 获取数据的形状
num_channels, num_timepoints, num_samples = data.shape

# 对每个 channel 进行正则化
for i in range(num_samples):
    for j in range(num_channels):
        # 取出当前 channel 的数据
        current_data = data[j, :, i]

        # 计算均值和标准差
        mean = np.mean(current_data)
        std = np.std(current_data)

        # 避免标准差为 0 的情况
        if std != 0:
            data[j, :, i] = (current_data - mean) / std
        else:
            data[j, :, i] = current_data - mean

# 保存标准化后的数据
np.save('normalized_eeg.npy', data)