Technologies Of Physiological Parameters Monitoring And Signals Reconstruction Based On Pulse Waves

China has stepped into an aging society gradually due to the increasing proportion of aging population. Problems related also emerge continuously and the health problem is one of the keys. Since cardiovascular related disease turns common and its prevalence goes high, continuous physiological parameters monitoring, which is a prevention and auxiliary treatment method, has becomes more and more important these days. Although there have been all kinds of devices which could monitor parameters such as pulse, blood pressure and electrocardiogram, their portability differs a lot and still needs improving. Therefore, we focus on the physiological parameters monitoring and signals rebuilding based on pulse waves as well as the design and realization of portable monitoring system in order to improve the portability and solve the problem mentioned above. Main work is carried out as follows.First, we complete both software programming and hardware design and realize the monitoring system. The system could be divided into several modules, including pulse waves sampling, electrocardiogram acquisition, signals pre-processing, post-processing, and sending-receiving. In this way, we could monitor the parameters e.g., heart rate and blood pressure. Meanwhile we also realize the pulse waves and electrocardiogram reconstruction. This system is more portable compared with most existing systems.Second, we propose a novel pulse wave fitting algorithm based on the possibility density function of Alpha-stable distribution. Simulations demonstrate the advantages of the proposed algorithm over existing methods with goodness of fit and mean square error. It also lowers the fitting errors caused by existing methods. Furthermore, we also propose a pulse wave reconstruction method using this algorithm and ARMA model. The errors in time and amplitude estimation of wave peaks validate the improvement of proposed reconstruction method. We measure heart rate and blood pressure using reconstructed pulse waves.Third, we propose a new electrocardiogram reconstruction algorithm using pulse waves. We firstly employ B-spline to acquire sufficient signal characters and KPCA to lower the dimension and calculation complexity in order to satisfy the needs in portable device design, and then use neural network to reconstruct electrocardiogram. Simulations verify the advantage of proposed algorithm by PRD between original and reconstructed signals.