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| import numpy as np
from typing import Tuple
class VitalSignExtractor:
"""
mmWave雷达生命体征提取器
基于微多普勒效应提取呼吸和心跳信号
"""
def __init__(self,
sample_rate: float = 1000.0,
breath_freq_range: Tuple[float, float] = (0.1, 0.5),
heart_freq_range: Tuple[float, float] = (0.8, 2.0)):
"""
Args:
sample_rate: 雷达采样率（Hz）
breath_freq_range: 呼吸频率范围（Hz）
heart_freq_range: 心跳频率范围（Hz）
"""
self.sample_rate = sample_rate
self.breath_freq_range = breath_freq_range
self.heart_freq_range = heart_freq_range
def extract_vital_signs(self,
range_doppler_map: np.ndarray,
range_bin: int,
window_sec: float = 10.0) -> dict:
"""
提取生命体征
Args:
range_doppler_map: 距离-多普勒图（时间×距离×多普勒）
range_bin: 目标距离单元
window_sec: 分析窗口（秒）
Returns:
vital_signs: 呼吸率、心率、置信度
"""
window_samples = int(window_sec * self.sample_rate)
phase_series = np.angle(range_doppler_map[-window_samples:, range_bin, :])
phase_unwrapped = np.unwrap(phase_series, axis=0)
doppler_var = np.var(phase_unwrapped, axis=0)
best_doppler = np.argmax(doppler_var)
phase_signal = phase_unwrapped[:, best_doppler]
fft_result = np.fft.fft(phase_signal)
freqs = np.fft.fftfreq(len(phase_signal), 1/self.sample_rate)
breath_mask = (np.abs(freqs) >= self.breath_freq_range[0]) & \
(np.abs(freqs) <= self.breath_freq_range[1])
breath_power = np.sum(np.abs(fft_result[breath_mask])**2)
positive_freqs = freqs[:len(freqs)//2]
positive_power = np.abs(fft_result[:len(freqs)//2])
breath_band_power = positive_power.copy()
breath_band_power[~breath_mask[:len(freqs)//2]] = 0
breath_freq = positive_freqs[np.argmax(breath_band_power)]
breath_rate = breath_freq * 60
heart_mask = (np.abs(freqs) >= self.heart_freq_range[0]) & \
(np.abs(freqs) <= self.heart_freq_range[1])
heart_power = np.sum(np.abs(fft_result[heart_mask])**2)
heart_band_power = positive_power.copy()
heart_band_power[~heart_mask[:len(freqs)//2]] = 0
heart_freq = positive_freqs[np.argmax(heart_band_power)]
heart_rate = heart_freq * 60
total_power = np.sum(np.abs(fft_result)**2)
breath_confidence = breath_power / total_power
heart_confidence = heart_power / total_power
return {
"breath_rate": float(breath_rate),
"heart_rate": float(heart_rate),
"breath_confidence": float(breath_confidence),
"heart_confidence": float(heart_confidence),
"phase_signal": phase_signal,
"freq_spectrum": {
"freqs": freqs,
"power": np.abs(fft_result)
}
}
def detect_child_presence(self,
vital_signs: dict,
threshold: dict = None) -> dict:
"""
检测儿童存在
Args:
vital_signs: 生命体征数据
threshold: 检测阈值
Returns:
detection_result: 检测结果
"""
if threshold is None:
threshold = {
"breath_confidence": 0.1,
"heart_confidence": 0.05
}
has_breath = vital_signs["breath_confidence"] > threshold["breath_confidence"]
has_heart = vital_signs["heart_confidence"] > threshold["heart_confidence"]
breath_valid = 10 <= vital_signs["breath_rate"] <= 40
heart_valid = 80 <= vital_signs["heart_rate"] <= 160
is_child_present = has_breath and has_heart and breath_valid and heart_valid
return {
"is_child_present": is_child_present,
"confidence": min(vital_signs["breath_confidence"],
vital_signs["heart_confidence"]),
"breath_rate": vital_signs["breath_rate"],
"heart_rate": vital_signs["heart_rate"],
"breath_valid": breath_valid,
"heart_valid": heart_valid
}
if __name__ == "__main__":
np.random.seed(42)
sample_rate = 1000
duration = 30
n_range_bins = 100
n_doppler_bins = 64
t = np.linspace(0, duration, sample_rate * duration)
breath_signal = 0.5 * np.sin(2 * np.pi * 0.25 * t)
heart_signal = 0.2 * np.sin(2 * np.pi * 1.2 * t)
phase_signal = breath_signal + heart_signal + np.random.normal(0, 0.05, len(t))
range_doppler_map = np.zeros((len(t), n_range_bins, n_doppler_bins), dtype=complex)
range_doppler_map[:, 50, 32] = np.exp(1j * phase_signal)
extractor = VitalSignExtractor(sample_rate=sample_rate)
vital_signs = extractor.extract_vital_signs(range_doppler_map, range_bin=50)
print(f"呼吸率: {vital_signs['breath_rate']:.1f} breaths/min")
print(f"心率: {vital_signs['heart_rate']:.1f} beats/min")
print(f"呼吸置信度: {vital_signs['breath_confidence']:.3f}")
print(f"心率置信度: {vital_signs['heart_confidence']:.3f}")
result = extractor.detect_child_presence(vital_signs)
print(f"\n儿童存在检测: {result['is_child_present']}")
print(f"综合置信度: {result['confidence']:.3f}")
|