Variability-aware gradual aging for generating reliability figures of a neural measurement system

Systems for intracortical recording of neural activities underly strict reliability requirements. The system should operate without any dysfunction for at least one decade. Despite process variability also NBTI and CHC will introduce performance shifts, which need to be evaluated by the system designer. In order to estimate the lifetime the system, reliability figures need to be calculated. By reconfiguring netlists it is possible to combine Monte Carlo analysis and aging simulation. This method is used to determine reliability figures for a low noise amplifier as used within a typical neural measurement system. Results show the effect of degradation for various component performances and their according reliability figures.