Response of Lock-In Detection-Based Optically Pumped Magnetometers to High Bandwidth Magnetic Signals

Detection of magnetic fields generated by deep brain stimulation (DBS) using optically pumped magnetometers (OPMs) operating in the spin-exchange relaxation-free (SERF) regime holds significant promise. High bandwidth DBS signals are particularly valuable for understanding current OPM limitations and developing predictive strategies to overcome them. This primary study investigates the response of commercially available SERF-OPMs (QZFM Gen-2, QuSpin Inc.) with their limited 135 Hz bandwidth and open-loop operation when exposed to magnetic DBS signals emitted by a commercially available DBS lead and generated by a DBS implantable pulse generator (IPG), which are characterized by short-duration rectangular pulses. Such magnetic fields emitted from a real DBS lead were measured using OPMs across a range of DBS pulse repetition frequencies from 2 to 255 Hz. A versatile 304-channel superconducting quantum interference device (SQUID) vector magnetometer system was employed in the Berlin Magnetically Shielded Room-2.1 for reference measurements. Our findings identified peaks at several spectral frequencies in addition to those relevant to the DBS signal, including the known DBS repetition frequency and its spectral harmonics peaks. These additional peaks are attributed to the interaction between the lock-in detection-based OPM's 923 Hz modulating field, supplied by the OPM's on-sensor coils, and the DBS repetition frequency. These peaks were successfully reconstructed by developing an OPM lock-in model and applying this model to signal characteristics provided by SQUID reference measurements. This letter identifies and clarifies the origin of various spectral peaks observed when using bandlimited OPMs for high bandwidth signal detection. This understanding allows magnetometer users of this particular sensor technology to differentiate between artificially introduced signal components and the DBS signal components. These findings are essential for improving the application utility of OPM-based detection for DBS and contribute to the advancement and understanding of OPM technology and address its current limitations.