Epileptic seizure prediction could help patients stay safe and provide them with opportunities to prevent seizures in advance. Seizures can be discriminated by monitoring the counts of population spikes and we proposed a spike detection front-end for this application. The proposed discrete-time system amplifies, detects and digitises the spiking with ultra-low power and high precision with memristor as a trimming device. In this paper, we utilised the measurement methodology for the discrete-time system that combines periodic steady-state analysis and transient simulation in order to complete the performance metrics and examine its behaviour under sources of uncertainty: noise, process corner and mismatch.