As systems become increasingly complex and costly, potential failure mechanisms and indicators are numerous and difficult to identify, while the cost of loss is very expensive - human lives, replacement units, and impacts to national security. In order to ensure the safety and long-term reliability of vehicles, structures, and devices attention must be directed toward the assessment and management of system health. System health is the key component that links data, information, and knowledge to action. Integrated Systems Health Management (ISHM) doctrine calls for comprehensive real-time health assessment and management of systems where the distillation of raw data into information takes place within sensors and actuators. This thesis develops novel field programmable health assessment capability for sensors and actuators in ISHM. Health assessment and feature extraction algorithms are implemented on a sensor or actuator through the Embedded Routine Manager (ERM) API. Algorithms are described using Health Electronic Datasheets (HEDS) to provide more flexible run-time operation. Interfacing is accomplished through IEEE Standard 1451 for Smart Sensors and Actuators, connecting ISHM with the instrumentation network of the future. These key elements are validated using exemplar algorithms to detect noise, spike, and flat-line events onboard the ISHM enabled Methane Thruster Testbed Project (MTTP) at NASA Stennis Space Center in Mississippi
