最近另外一篇基于PPG信号的心率估计算法的文章被IEEE Transactions on Biomedical Engineering接收。文章信息如下：

Title: Photoplethysmography-Based Heart Rate Monitoring in Physical Activities via Joint Sparse Spectrum Reconstruction

Journal: IEEE Transactions on Biomedical Engineering

DOI: 10.1109/TBME.2015.2406332

下载链接：https://www.academia.edu/attachments/36714861/download_file?s=swp-sidebar 

Abstract:

Goal: A new method for heart rate monitoring

using photoplethysmography (PPG) during physical activities is

proposed. Methods: It jointly estimates spectra of PPG signals

and simultaneous acceleration signals, utilizing the multiple

measurement vector model in sparse signal recovery. Due to a

common sparsity constraint on spectral coefficients, the method

can easily identify and remove spectral peaks of motion artifact

(MA) in PPG spectra. Thus, it does not need any extra signal

processing modular to remove MA as in some other algorithms.

Furthermore, seeking spectral peaks associated with heart rate

is simplified. Results: Experimental results on 12 PPG datasets

sampled at 25 Hz and recorded during subjects’ fast running

showed that it had high performance. The average absolute

estimation error was 1.28 beat per minute and the standard

deviation was 2.61 beat per minute. Conclusion and Significance:

These results show that the method has great potential to be

used for PPG-based heart rate monitoring in wearable devices

for fitness tracking and health monitoring.