A Node Sleeping Method Based on Sparse Representation for Body Area Networks

Abstract

The invention discloses a body area network node dormancy method based on sparse representation, relates to the field of body area network, and comprises the following steps: firstly, determining the type of the physiological signal collected by the node, and classifying the database samples of the collected signal of the node as normal and pathological And mark it with a number, construct the training sample into an overcomplete dictionary D; secondly, find the sparse expression coefficient of the test sample; then, compare the size with the threshold τ to determine the effective sample and the invalid sample; finally, calculate the minimum residual of the effective sample y The difference min ri(y) determines the category to which the valid samples belong, and controls the dormant state of the node. The method can enable the nodes to filter out normal signals that do not need to be collected and make the nodes that collect normal signals enter a dormant state, prolong the dormancy time of the nodes, reduce the number of times the node transceiver works, reduce the amount of network data transmission, and reduce the energy consumption of the body area network.

Description

technical field [0001] The invention relates to the field of body area networks, in particular to a method for dormancy of body area network nodes based on sparse representation. Background technique [0002] Body area network is a network in which sensor nodes are placed on the surface of the human body or in the body, and the physiological data of various parts such as human body temperature, blood pressure, heart rate, and EEG are collected through the nodes. As the population aging trend in our country is becoming more and more serious, and there are more and more cardiovascular diseases, body area networks have been widely used in remote medical diagnosis, disease monitoring and prevention, and family care. The energy consumption of nodes in the body area network is mainly concentrated in the sending and receiving parts of the radio frequency module, so reducing the working time of the radio frequency module and increasing the sleep time of the radio frequency module is...

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Problems solved by technology

[0004] The energy of the node battery in the body area network is limited. Most of the data measured by the sensors in the existing body area network are normal signals, and these normal signals do not need to collect signals. For the body area network with strict energy requirements, the Indiscriminate sampling of physiological signals is undoubtedly a waste of energy

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