Improved Heart Rate Tracking Using Multiple Wrist-type Photoplethysmography during Physical Activities
Improved Heart Rate Tracking Using Multiple Wrist-type Photoplethysmography during Physical Activities
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DOI：
10.1109/embc.2018.8512736
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发表时间：
2018-07
期刊：
影响因子：
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通讯作者：
Lianning Zhu;D. Du
中科院分区：
文献类型：
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作者：
Lianning Zhu;D. Du
可穿戴传感设备在运动过程中采集的光电容积脉搏波（PPG）信号易受运动伪影（MA）的干扰，给心率估计带来了很大的挑战。本文提出了一种新的框架，以准确地估计HR使用两个导联的PPG信号结合加速度计（ACC）的数据在MA的存在。首先使用移动时间窗来分割PPG信号和ACC信号。然后，在每个时间窗口中通过联合稀疏谱重建来衰减MA，其中从PPG信号的谱频率中减去ACC的最大谱频率。此外，根据稀疏频谱中具有最大幅度的频率来估计每个净化PPG的HR。使用从每个重建的PPG信号计算的谱带功率来确定实际HR。使用2015 IEEE Signal Processing Cup数据集验证了所提出的方法。平均绝对误差为1.15次/分钟（BPM）（标准差：2.00 BPM），平均绝对误差百分比为0.95%（标准差：1.86%）。所提出的方法优于以前报道的工作的准确性。
Photoplethysmography (PPG) signals collected from wearable sensing devices during physical exercise are easily corrupted by motion artifact (MA), which poses great challenge on heart rate (HR) estimation. This paper proposes a new framework to accurately estimate HR using two leads of PPG signals in combination with accelerometer (ACC) data in the presence of MA. A moving time window is first used to segment PPG signals and ACC signals. Then, MA is attenuated by joint sparse spectrum reconstruction in each time window, where maximum spectrum frequencies of ACC are subtracted from the spectrum frequency of PPG signals. Further, HR for each cleansed PPG is estimated from the frequency with maximum amplitude in the sparse spectrum. The actual HR is determined using spectral band powers calculated from each reconstructed PPG signals. The proposed method was validated using the 2015 IEEE Signal Processing Cup dataset. The average absolute error is 1.15 beats per minutes (BPM) (standard deviation: 2.00 BPM), and the average absolute error percentage is 0.95% (standard deviation: 1.86%). The proposed method outperforms the previously reported work in terms of accuracy.