Integrated Residual Current Monitor Using Fiber Optics for Medical Devices Maintenance

In this work, a condition-based maintenance (CBM) method for medical devices is presented using a residual current monitor to estimate the condition of medical equipment (ME). Based on comparative data from two patient monitors (PMon)s during the single fault condition (SFC), the characteristics of each device would be used as a reference on how a device can be monitored by modeling using machine learning. In this study, support vector regression (SVR) is used to obtain multivariable linear equations. By using statistical features, the urgency of preventive maintenance (PM) would be determined. This will answer the main challenges faced by scheduling with PM for medical devices that are increasingly used in hospitals to avoid electrical hazards. The monitoring mechanism will be proposed using fiber optics (FO) which allows real-time integrated monitoring. To illustrate the effectiveness of the method, a diagram block model of residual current monitor (RCM) is designed to describe the relationship of FO communication structure. A diagnostic result is also presented with a sequence of phases; High (H) and Low (L) during SFC in a total of 2,000 sampling data using a National Instrument (NI) myDAQ to record datasets. The results presented in this work show the potential use of the residual current device (RCD) to perform CBM from two different PMons individually with the same threshold score of 0.9 with accuracy above 78%. This will simplify the initial check of MEs in hospitals and maximize patient safety protection from the dangers of electric shock.