Computer-aided Pre-clinical Trials for Implantable Medical Devices: Test Automation Platform NSF Summer Undergraduate Fellowship in Sensor Technologies

Ensuring that medical devices, such as pacemakers and implantable cardioverter defibrillators (ICDs), deliver the appropriate therapy only when necessary is made difficult by complex software and variability conditions between patients. Because of patient condition variability, safety recalls have affected over 600,000 devices between 1990 and 2000 [1]. Of these recalled devices, 200,000 were recalled due to firmware issues [1]. The current standard for validation of these devices is a clinical trial. These trials test the new device against the current standard of care by comparing their performances on real patients. To prevent poorly performing devices from being used in clinical trials—in which millions of dollars are spent, four to six years are wasted, and patients’ lives are put at risk—computer-aided pre-clinical trials that use virtual heart models, rather than real patient hearts, to test ICD devices can be useful. These computeraided pre-clinical trials will be able to test ICDs over a large group of 11,000 synthetic patients. Measuring the ICD’s performance against these 11,000 synthetic patients exposes an ICD to a large range of patient variability, and provides insight into the performance of an ICD before a clinical trial. Due to the large size of the synthetic group, a test automation platform is needed. In this paper, we propose a test automation platform that is able to test real ICD devices over a wide range of heart conditions. The platform can send stored synthetic electrogram (EGM) signals (recordings of electric potential over time for heart tissue) to an ICD device, or an ICD algorithm on a PC, and monitor the performance of both the ICD device and the algorithm. In the following sections of this paper, the hardware and software designs for the platform will be discussed in detail along with results of the platform.