Pulse Rate Estimation using PPG Affected with Motion Artifacts Base d on VMD and Hilbert Transform Physiological information such as pulse rate (PR) can be extracted from photoplethysmography (PPG) signal. However, pulse rate estimation becomes very difficult during physical exercise since PPG is susceptible to motion artifacts (MA). This paper proposes a PR estimation method using PPG with MA based on variational mode decomposition (VMD) and Hilbert transform. VMD was used to decompose PPG and acceleration signals to generate several intrinsic mode functions (IMFs), respectively. And these obtained IMFs are used to generate corresponding marginal spectrum by Hilbert transform. Finally, MA interference were excluded by spectral peak tracking to obtain accurate PR estimation. The performance of the proposed method has been evaluated using the datasets of 2015 IEEE Signal Processing Cup. Experimental results showed that the average absolute error was 1.97 beat per minute (BPM) and standard deviation of the absolute error was 2.73 BPM. The Pearson correlation between Estimated PR and the groundtruth PR was 0.994. The proposed method can be applied on wearable devices to estimate PR using PPG during physical exercise conditions.

A Wavelet Adaptive Cancellation Algorithm Based on MultiInertial Sensors for the Reduction of Motion Artifacts in Ambulatory ECGs Wearable electrocardiogram (ECG) devices are universally used around the world for patients who have cardiovascular disease (CVD). At present, how to suppress motion artifacts is one of the most challenging issues in the field of physiological signal processing. In this paper, we propose an adaptive cancellation algorithm based on multiinertial sensors to suppress motion artifacts in ambulatory ECGs. Firstly, this method collects information related to the electrode motion through multiinertial sensors. Then, the part that is not related to the electrode motion is removed through wavelet transform, which improves the correlation of the reference input signal. In this way, the ability of the adaptive cancellation algorithm to remove motion artifacts is improved in the ambulatory ECG. Subsequent experimentation demonstrated that the wavelet adaptive cancellation algorithm based on multiinertial sensors can effectively remove motion artifacts in ambulatory ECGs.