In multi-user Wearable human physiological signal monitor system, optimizing detector circuit power consumption, size, interference, how to avoid the data collision each other when several detector transmit data to the Central Service System (CSS) simultaneously etc. are very important and difficult to solve problems. This paper put forward two methods to above questions. Firstly, plenty of single chip's inner resource is used to decrease power and size for ECG detector preprocessing circuit. With this method high precision could be get, power line interference and baseline shift could be restrained, and this ECG preprocessing circuit could automatic checkout whether sensor is off. Secondly, the paper expounds a new wireless network model according to the requisition of wearable wireless network. Improved a Time-Division Multiplexing Address anti-collision protocol, it is with inquiry priority based broadcast in call number. Experiments proved that above measures could optimize system's power, size, communication response time and accuracy. It is suitable to the multi-user working in small-scale, low cost, short range, low speed and special environment, needing more ease and more agile to build the network.
The heart rate variability (HRV) index can be used as a reference for the accessory diagnostic of the cardiovascular disease and the non-invasive monitoring in the recovery process. The complexity estimation is an important parameter for depicting the information quantities of the time sequence signals. The Kolmogorov Complexity of the HRV indexes among 106 samples from the normal human, patients with Hypertension and patients with coronary heart disease has been calculated in this work. The statistical analysis of the calculated results has been carried out. The results obtained can be used as the reference in the clinical diagnostics.
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