Nature 2024：毫米波雷达高精度生命体征检测方法

论文来源： Nature Scientific Reports
期刊： Scientific Reports, October 26, 2024
核心创新： 呼吸谐波抑制 + 心率估计误差降低3.2%

论文信息

项目	内容
标题	A high precision vital signs detection method based on millimeter wave radar
期刊	Nature Scientific Reports
日期	October 26, 2024

核心算法：呼吸谐波抑制

import numpy as np
from scipy.fft import fft

def high_precision_vital_signs(radar_phase, fs=100):
    """
    高精度生命体征检测
    
    Nature 2024 论文核心：
    呼吸谐波干扰抑制 → 心率估计精度提升
    
    步骤：
    1. 相位解调
    2. 呼吸信号重构
    3. 呼吸谐波抑制
    4. 心率提取
    """
    # 1. 相位解调
    phase = np.unwrap(np.angle(radar_phase))
    phase_diff = np.diff(phase)
    
    # 2. FFT频谱分析
    N = len(phase_diff)
    freq = np.fft.fftfreq(N, 1/fs)[:N//2]
    spectrum = np.abs(fft(phase_diff))[:N//2]
    
    # 3. 呼吸信号提取（0.1-0.5 Hz）
    breath_mask = (freq >= 0.1) & (freq <= 0.5)
    breath_freq = freq[breath_mask][np.argmax(spectrum[breath_mask])]
    breath_rate = breath_freq * 60  # bpm
    
    # 4. 呼吸谐波抑制（关键创新）
    # 重建呼吸信号
    t = np.arange(N) / fs
    breath_signal = np.sin(2 * np.pi * breath_freq * t)
    
    # 从相位中去除呼吸成分
    residual = phase_diff - breath_signal * np.max(spectrum[breath_mask])
    
    # 5. 心率提取（0.8-2.0 Hz）
    residual_spectrum = np.abs(fft(residual))[:N//2]
    heart_mask = (freq >= 0.8) & (freq <= 2.0)
    heart_freq = freq[heart_mask][np.argmax(residual_spectrum[heart_mask])]
    heart_rate = heart_freq * 60  # bpm
    
    return {
        "breathing_rate": breath_rate,
        "heart_rate": heart_rate,
        "child_detected": heart_rate > 80  # 儿童心率特征
    }