BrainFlow【降采样】

降采样 （Downsample_Data）

一开始在一些脑机接口的参考书中没找到，有也是简单略过，接着就去问了问度娘：

• 采样率的单位是Hz，指的是一秒内要记录多少个数据点的意思，比如原始数据的采样率是1000Hz的话，就是代表一秒内有1000个数据点。
• 在后期分析的时候，我们有时候会想要降低采样率，比如降到500Hz或者250Hz。这样做最大的好处其实就是减小数据量，以提高计算速度，没有其他的作用了。所以这一步并不是必须的。
• 但降低采样率需要注意两点，一是降低采样率要在滤波之后。因为降低采样率会使我们丢失高频信息，使高频信息变得扭曲，所以最好在保留了我们感兴趣波段之后再去降低采样率，这样可以保证信号最大程度不会失真。二是有一个采样定理，理论上来说，我们的采样率必须是我们想要分析的波段的两倍，比如我们想要分析60Hz的波，那数据采样率为120Hz就足够了。实际上，建议采样率最好在分析波段的三到四倍。

代码块

 

import time
import numpy as np
import brainflow
from brainflow.board_shim import BoardShim, BrainFlowInputParams, LogLevels, BoardIds
from brainflow.data_filter import DataFilter, FilterTypes, AggOperations

def main ():
    BoardShim.enable_dev_board_logger ()

    # use synthetic board for demo
    #GET PARAMS
    params = BrainFlowInputParams ()
    board = BoardShim (BoardIds.SYNTHETIC_BOARD.value, params)
    board.prepare_session ()
    board.start_stream ()
    BoardShim.log_message (LogLevels.LEVEL_INFO.value, 'start sleeping in the main thread')
    time.sleep (10)
    data = board.get_current_board_data (20) # get 20 latest data points dont remove them from internal buffer
    board.stop_stream ()
    board.release_session ()

    eeg_channels = BoardShim.get_eeg_channels (BoardIds.SYNTHETIC_BOARD.value)
    # demo for downsampling, it just aggregates data
    #DataFilter to perform signal processing, it calls methods from underlying DataHandler library
    for count, channel in enumerate (eeg_channels):
        print ('Original data for channel %d:' % channel)
        print (data[channel])
        if count == 0:
            downsampled_data = DataFilter.perform_downsampling (data[channel], 3, AggOperations.MEDIAN.value)
        elif count == 1:
            downsampled_data = DataFilter.perform_downsampling (data[channel], 2, AggOperations.MEAN.value)
        else:
            downsampled_data = DataFilter.perform_downsampling (data[channel], 2, AggOperations.EACH.value)
        print ('Downsampled data for channel %d:' % channel)
        print (downsampled_data)


if __name__ == "__main__":
    main ()

 

相关函数

（1） classmethod perform_downsampling(data, period, operation)

perform data downsampling, it doesnt apply lowpass filter for you, it just aggregates several data points

Parameters

• data (1d numpy array) – initial data

• period (int) – downsampling period

• operation (int) – int value from AggOperation enum

Returns

downsampled data

Return type

1d numpy array

 

（2）class brainflow_data_filter.AggOperations


Bases: enum.Enum

Enum to store all supported aggregation operations

　　　　· MEAN= 0

　　　　· MEDIAN= 1

　　　　· EACH= 2