Deep brain stimulation (DBS) is used to treat a variety of movement disorders. In current DBS therapy, the stimulation parameters are manually adjusted based on a subjective assessment of patient’s symptoms. State-of-the-art DBS research focuses on recording brain activity to create a patient-specific neuronal profile that correlates with the patient’s symptom-severity. The neuronal profile could then be used as feedback signal for an adaptive DBS system that automatically adjusts the stimulation. The Medtronic PerceptTM is the first commercially available, fully implanted neurostimulator with sensing technology. In this study, the neuronal activity in the form of local field potentials (LFPs) of eleven patients were recorded with Percept during both stimulation off- and on. To obtain a reliable neuronal profile from the LFPs, the signals should be free from electrocardiography (ECG) artefact and should be synchronized with externally recorded data that informs us about the patient’s symptom-severity. A template subtraction method and a method based on independent component analysis were developed to suppress ECG artefact. Both methods were compared to the ECG removal method of the Perceive Toolbox. Three methods of synchronization were explored: externally tapping, using the stimulation artefact, and by ECG cross-correlation. Results show the template subtraction method to most effectively suppress ECG artefacts while preserving LFP frequency content. To save effort but assure accuracy of the synchronization, the ECG cross-correlation method should be applied though validated by confirming accurate alignment of the stimulation artefact. The development and evaluation of the ECG artefact suppression- and external data synchronization methods contribute to research focused on finding a reliable feedback signal for adaptive DBS.