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Objective . Neural interfaces and other implantable micro-devices that use polymer-encapsulated integrated circuits will only be allowed in medical devices when their lifetimes can be estimated from experimental data. An apparatus has been developed and tested that allows hundreds of insulated samples (interdigitated combs) to be aged under accelerated conditions of high temperature and voltage stress. Occasionally, aging is paused while the sample’s impedance is measured; the impedance spectrogram may show degradation as it progresses before failure.  Approach . The design was based on practical considerations which are reviewed. A  Solartron Modulab  provides the frequency response analyser and the femtoammeter. The apparatus can accommodate batches of samples at several temperatures and with different aging voltage waveforms. It is important to understand features of the spectra that are not due to comb–comb leakage, but come from other places (for example substrate-solution leakage); some have been observed and investigated using SPICE.  Main results . The design is described in detail and test results show that it is capable of making measurements over long periods, at least up to 67 °C. Despite the size of the apparatus, background capacitance is about 1 pF and comb–comb capacitances of about 30 pF can be measured down to 10 mHz, an impedance of about 100 GΩ. An important discovery was the advantage of grounding the bathing solution, primarily in that it raises the measurement ceiling. Observation and SPICE simulation shows that leakage from the substrate to the bathing solution can give phase lags  >90°, in contrast to comb–comb leakage which reduces phase lag to  <90°.  Significance . The value of this paper is that it will facilitate research into the endurance of small implanted devices because, given a description of a proven apparatus, researchers can start building their own apparatus relatively quickly and with confidence.

Apparatus to investigate the insulation impedance and accelerated life-testing of neural interfaces