Fuzzy unordered rule induction algorithm based classification for reliable communication using wearable computing devices in healthcare

Wireless sensor nodes that can be strategically located across the human body to create a network for various types of healthcare applications such as a network is known as wearable computing devices (WCDs). Robust treatment is provided to the patient in this network, to maintain stable patient status. The coordination in the effective route needs to be improved. Patient care should be maintained in WCD and communicated more in a reliable manner. In general data from such a network is vulnerable to attacks/misbehavior. Hence it is warranted to detect and introduce methods for sustaining the reliability of the network. Data classification methods by selecting classification algorithms, fuzzy unordered rule induction algorithm (FURIA) have been introduced in this research as a possible solution to address the problem. An attempt has also been made to detect faulty measurements while collecting data from the WCD and the data has been securely transmitted through fuzzy logic technique. The main objective of this research is to introduce alarming techniques when the patient goes critical. The proposed FURIA based classification and linear regression algorithm outperforms existing methods.