Fuzzy System to Authenticate Assisted Living Patients in Their Home Environment

Patient identity verification is a critical requirement for a remote patient monitoring environment. The health of the patient is monitored and crucial medical decisions are taken based on the physiological data collected from the patient using sensors and sent to distant health care centers or hospitals for real-time monitoring. Therefore it is of utmost importance to associate the received data with the correct patient as false verification of the patient’s identity could lead to a wrong diagnosis and have serious repercussions leading even to the loss of a patient’s life. In this study we propose a simple and robust remote authentication system for verifying the identity of assisted living patients being monitored in their home environment. We propose a biometric authentication that is based on the Electrocardiogram (ECG) data collected from the patient. It is a well established fact that ECG can be used to authenticate people. Moreover ECG data serves to not only monitor the health of the patient but also provides for continuous patient verification which is a very essential requirement for the security of the remote health monitoring system. We have implemented and tested the proposed fuzzy authentication scheme using the Mamdani model and present the results.