| import os |
| import numpy as np |
| from scipy.signal import butter, sosfilt, lfilter, iirnotch |
| from scipy.signal import find_peaks |
|
|
| def butter_bandpass(lowcut, highcut, fs, order=8): |
| low = lowcut |
| high = highcut |
| sos = butter(order, [low, high], btype='band', fs=fs, output='sos', analog=False) |
| return sos |
|
|
| def butter_highpass(lowcut, fs, order=8): |
| low = lowcut |
| sos = butter(order, low, btype='highpass', fs=fs, output='sos', analog=False) |
| return sos |
|
|
| def butter_lowpass(highcut, fs, order=8): |
| high = highcut |
| sos = butter(order, high, btype='lowpass', fs=fs, output='sos', analog=False) |
| return sos |
|
|
| def butter_bandpass_filter(data, lowcut, highcut, fs, order=8): |
| if highcut > fs/2: |
| sos = butter_highpass(lowcut, fs, order=order) |
| elif lowcut <= 0: |
| sos = butter_lowpass(highcut, fs, order=order) |
| else: |
| sos = butter_bandpass(lowcut, highcut, fs, order=order) |
| |
| y = sosfilt(sos, data) |
| return y |
|
|
| def correct_ecg_inversion(ecg_signal, sampling_rate): |
| """ |
| ECG ์ ํธ๊ฐ ๋ค์งํ๋์ง ๊ฐ์งํ๊ณ ์ฌ๋ฐ๋ฅด๊ฒ ์์ ํฉ๋๋ค. |
| |
| Args: |
| ecg_signal (np.array): ECG ์ ํธ ๋ฐ์ดํฐ. |
| sampling_rate (int): ์ํ๋ง ์ฃผํ์ (Hz). |
| |
| Returns: |
| np.array: ์์ ๋ ECG ์ ํธ. |
| bool: ๋ค์งํ์ด ๊ฐ์ง๋์๋์ง ์ฌ๋ถ. |
| """ |
| |
| |
| positive_peaks, _ = find_peaks(ecg_signal, prominence=0.1, distance=0.3 * sampling_rate) |
| |
| |
| negative_peaks, _ = find_peaks(-ecg_signal, prominence=0.1, distance=0.3 * sampling_rate) |
|
|
| |
| if len(positive_peaks) == 0 and len(negative_peaks) == 0: |
| return ecg_signal, False |
|
|
| |
| mean_pos_amp = np.mean(ecg_signal[positive_peaks]) if len(positive_peaks) > 0 else 0 |
| mean_neg_amp = np.mean(ecg_signal[negative_peaks]) if len(negative_peaks) > 0 else 0 |
|
|
| |
| is_inverted = abs(mean_neg_amp) > abs(mean_pos_amp) |
|
|
| if is_inverted: |
| |
| return ecg_signal * -1, True |
| else: |
| |
| return ecg_signal, False |
