Deep brain stimulation (DBS) for Parkinson’s disease, essential tremor and epilepsy is an established palliative treatment. DBS uses electrical neuromodulation to suppress symptoms. Most current systems provide a continuous pattern of fixed stimulation, with clinical follow-ups to refine settings constrained to normal office hours. An issue with this management strategy is that the impact of stimulation on circadian, i.e. sleep-wake, rhythms is not fully considered; either in the device design or in the clinical follow-up. Since devices can be implanted in brain targets that couple into the reticular activating network, impact on wakefulness and sleep can be significant. This issue will likely grow as new targets are explored, with the potential to create entraining signals that are uncoupled from environmental influences. To address this issue, we have designed a new brain-machine-interface for DBS that combines a slow-adaptive circadian-based stimulation pattern with a fast-acting pathway for responsive stimulation, demonstrated here for seizure management. In preparation for first-in-human research trials to explore the utility of multi-timescale automated adaptive algorithms, design and prototyping was carried out in line with ISO risk management standards, ensuring patient safety. The ultimate aim is to account for chronobiology within the algorithms embedded in brain-machine-interfaces and in neuromodulation technology more broadly.
There is growing interest in using adaptive neuro-modulation to provide a more personalized therapy experience that might improve patient outcomes. This paper describes the design of the ‘DyNeuMo Mk-1’, a fully-implantable, motion-adaptive research stimulator that titrates stimulation based on the patient’s movement state (e.g. posture, activity, shock, free-fall). The design leverages off-the-shelf consumer technology that provides inertial sensing with low-power, high reliability and modest cost. We used a three-axis accelerometer and its embedded digital motion processor to enable real-time stimulation adaption based on configurable motion parameters. The algorithm configurability and expanded stimulation parameter space allows for a number of applications to be explored in both central and peripheral applications. The implantable system was designed, prototyped and verified using ISO 13485 design controls, including ISO 14971 risk management techniques to ensure patient safety, while enabling novel algorithms. With the design controls in place, first-in-human research trials are now being prepared to explore the utility of automated motion-adaptive algorithms. The design highlights how consumer electronics technology can be leveraged for efficient and reliable medical device development. The implantable system automatically provides activity- and posture-based responsive stimulation which can be configured by the clinician to optimize therapy. Intended applications include adaptive stimulation for movement disorders, synchronizing stimulation with circadian patterns, and reacting to transient inertial events such as shocks for urinary incontinence.
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