title: [Research on PPG Signal Reconstruction Based on Compressed Sensing].
abstract: In order to improve the storage and transmission efficiency of dynamic photoplethysmography (PPG) signals in the detection process and reduce the redundancy of signals, the modified adaptive matching pursuit (MAMP) algorithm was proposed according to the sparsity of the PPG signal. The proposed algorithm which is based on reconstruction method of sparse adaptive matching pursuit (SAMP), could improve the accuracy of the sparsity estimation of signals by using both variable step size and the double threshold conditions. After experiments on the simulated and the actual PPG signals, the results show that the modified algorithm could estimate the sparsity of signals accurately and quickly, and had good anti-noise performance. Contrasting with SAMP and orthogonal matching pursuit (OMP), the reconstruction speed of the algorithm was faster and the accuracy was high.
authors.forename: Aihua
authors.initials: A
authors.lastname: Zhang
authors.forename: Jiqing
authors.initials: J
authors.lastname: Ou
authors.forename: Yongxin
authors.initials: Y
authors.lastname: Chou
authors.forename: Bin
authors.initials: B
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted; D017156:Photoplethysmography