Compressed sensing for wireless pulse wave signal acquisition

Wireless-enable pulse wave (PW) biosensor is generally used for pervasive and non-invasive health care monitoring. However, the energy efficiency of the present devices still needs to be improved due to the high energy consumption during wireless communication. In this paper, a compressed sensing (CS) scheme for wireless PW signal acquisition is proposed. With the CS-based scheme, airtime over energy-hungry wireless links can be reduced and energy efficiency of the wireless biosensor can be improved. PW signal is sparse under the discrete cosine transform (DCT) basis. Therefore, the CS-based scheme can efficiently compress and recover the signal by the 1-bit sparse quasi-Toeplitz measurement matrix and the basis pursuit de-noising (BPDN) model. The efficiency improvement of node was evidenced by the practical experiments on a MICAz node. By using the proposed scheme, the average percentage root-mean-square difference (PRD) of 4.23%, energy saving of 35.15% and node prolonging of 54.20% can be achieved.