Deep Brain Stimulation (DBS) is a well-established invasive therapeutic approach for Parkinson’s disease (PD). However, the mechanisms of DBS remain unclear. A transition from the established open-loop paradigm to closed-loop DBS holds promise for enhancing therapeutic outcomes and optimising device efficiency. This transition requires identifying reliable biomarkers for the closed-loop algorithm. Recent studies suggest that biomarkers associated with harmonics of stimulation frequency may offer viable options for adaptive DBS (aDBS) and provide mechanistic insights. Previously subharmonic biomarkers have been avoided, often dismissed as artefactual. This is partly due to there being no clear physiological/non-physiological differentiating factor when considering steady signals during short time periods. To advance sense-stimulation therapies and aDBS, it is imperative to identify artefact-free frequency bands for effective biomarker monitoring. Here, we present a framework for discerning artefacts at the half harmonic of stimulation frequency.