init commit

Debug_64ch_Decoder_Optimize/blinkdetection/algorithm/eye_detection.py

@@ -0,0 +1,72 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Sep 29 16:14:17 2025
+
+@author: 23749
+"""
+
+
+import numpy as np
+from scipy.signal import butter, filtfilt
+
+## 1.Bandpass Filter
+def butter_bandpass(lowcut, highcut, fs, order=4):
+    # 滤波器
+    nyq = 0.5 * fs              #ny:Nyquist频率，即能表示的最大有效频率
+    low = lowcut / nyq
+    high = highcut / nyq
+    b, a = butter(order, [low, high], btype='band')   #巴特沃斯滤波器，order=4阶
+    return b, a
+
+def bandpass_filter(data, lowcut, highcut, fs, order=4):
+    b, a = butter_bandpass(lowcut, highcut, fs, order)    
+    return filtfilt(b, a, data)
+
+## 2.Eye Blink Dectection
+def blink_detection(F, fs, Dmin, Dmax, Emin, Emax):
+    """
+    波形检测
+    输入: 差分特征向量 F, 采样率 fs
+    输出: b (0/1), 以及计算出的 d, e
+    """
+
+    if F is None or len(F) < 3:
+        return 0, None, None
+
+    # 找最大时间(peak) & 最小时间(valley)
+    t_peak = np.argmax(F)
+    t_valley = np.argmin(F)
+
+    # 要求 peak 在 valley 之前（符合 blink 形态），否则交换
+    if t_valley < t_peak:
+        t_peak, t_valley = t_valley, t_peak
+
+    # 计算持续时间 d (ms)
+    d = (t_valley - t_peak) * 1000.0 / fs
+
+    # 计算能量 e (差分平方和)
+    e = np.sum(F[t_peak:t_valley + 1] ** 2)
+
+    # 阈值判定
+    if Dmin <= d <= Dmax and Emin <= e <= Emax:
+        b = 1  # 检测到眨眼
+    else:
+        b = 0  # 否则 no blink
+    return b, d, e
+
+if __name__ == '__main__':
+    import matplotlib.pyplot as plt
+    
+    fs = 250  # 采样率
+    t = np.arange(0, 5, 1/fs)
+    eog = 0.01 * np.random.randn(len(t))  # 基线+噪声
+    
+    # 模拟眨眼（在 2.0s 注入脉冲）
+    center = int(2.0 * fs)
+    eog[center:center+5] += 0.5
+    eog[center+5:center+15] -= 0.4
+    
+    # 测试 blink_detection
+    F = np.diff(eog)
+    b, d, e = blink_detection(F, fs, 70, 500, 0.1, 10)
+    print(f"Detected: {b}, Duration: {d}ms, Energy: {e}")