Data Fusion and Aggregation Methods for Pre-Processing Ambulatory Monitoring and Remote Sensor Data for Upload to Personal Electronic Health Records.
Bruce D. Moulton, Zenon Chaczko, Mark Karatovic - · UTS ePRESS (University of Technology Sydney) · 2009
Several countries including Australia are developing standards for personal electronic health records, and in many cases the standards provide ways for patients to upload data from their own sensor systems to their electronic health records. This article explores issues relating to the design of systems where electronic medical records are updated with data or meta-data from in-home or on-body health monitoring sensor systems. A prototype system was designed, implemented and subsequently evaluated in a way intended to further understanding regarding collection and transfer of sensor data to an electronic health record. A key issue that arose was the extent to which levels of confidence in the data may be affected by the type, quality, installation, maintenance and calibration of the sensors. This is in part because when health monitoring devices are used in hospitals, procedures exist for all of these activities, however, such procedures are usually not applied to in-home or ambulatory monitoring systems. Issues relating to the adoption of data aggregation or fusion techniques were also considered, a reason being that certain techniques involving aggregation of data from different sensors may be suitable for improving the degree of confidence in the extent to which the data from any particular sensor can be relied upon. One of the findings was that teams that are developing systems that might perform some data fusion at the node or prior to storage would benefit from the inclusion of clinical specialists at an early stage of the development process, because these specialists may in certain circumstances require disaggregated or un-fused data to inform clinical decisions.