DyNeuMo Mk-2: An Investigational Circadian-Locked Neuromodulator with Responsive Stimulation for Applied Chronobiology

Abstract

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.

Keywords: Activity recognition; Adaptive control; Brain stimulation; Chronobiology; Circadian rhythm; Closed loop systems; Digital filters; Neural implants; Safety management.

Fig. 1

Overview of the DyNeuMo Mk-2 program. Left: Target applications considered for the user requirements and risk management. Middle: Technology stack sub-components required for system integration. Right: Dual-mode control policies, which are the focus of this research tool. Adapted from [13].

Fig. 2

Top: system block diagram for the DyNeuMo Mk-2 supplementing the baseline functionality provided by the predicate Picostim with the addition of the slow- and fast-adapting algorithms. (Acronyms: API is an application programming interface, MICS is the Medical Information and Communication band) Bottom: actual physical components for the DyNeuMo research system. Note that the research tool is upgradeable through the firmware and software versions, while mechanical components are largely reused. The USB connector between the patient programmer and tablet is for in-clinic programming. Research subjects use the handheld controller for at-home recharge and manual adjustments. Adapted from [14].

Fig. 3

Screen shot of the algorithm configuration tab illustrating how the circadian table is configured for a 24-hour cycle. Note that the fast-adaptive algorithms are also included in the same module. Stimulation programs are mapped to classified states and time-based epochs.

Fig. 4

Initiation of stimulation due to a transient shock, that ceases after a programmed time of inactivity. The rapid response time of 12.6 ms helps support time-critical interventions. Figure reproduced from [14].

Fig. 5

Demonstration of stimulation modulation based on real-time seizure detection. Top: input signal from pre-recorded human seizure from the anterior nucleus of the thalamus. Middle panels: Tuned band-pass filter (1–20 Hz, 4th order), and rectified/low-passed output to extract the envelope. Bottom: stimulation increases (from 0.5 to 3 mA) in response to a detected seizure for a pre-set period of 15 s in this example, upon crossing a clinician-adjustable threshold (Θ).