Energy efficiency optimization in large-scale multichannel electrical neuromodulation

Abstract

Electrical neuromodulation is an evolving therapeutic approach used to treat neurological conditions such as Parkinson’s disease, epilepsy, and vision loss. Early systems, such as cardiac pacemakers and deep brain stimulators, typically utilized low-channel-count stimulation. Recent technological progress has enabled large-scale multichannel systems supporting hundreds or thousands of electrodes.

As channel counts increase, power consumption becomes a critical constraint for the scalability of implantable neurostimulators. While small systems often rely on implanted batteries, the substantial power demands of large-scale systems make battery-powered operation impractical. Wireless power transfer (e.g. inductive coupling) offers an alternative, but is fundamentally limited in the amount of power that can be safely delivered. Consequently, optimizing energy efficiency in large-scale multichannel neurostimulators is essential for maximizing channel count within the available power budget.

While prior studies evaluated pulse shaping mainly from a neurophysiological perspective, this thesis is the first to systematically analyze the relationship between pulse shape, physiological effectiveness, and circuit-level power consumption to identify optimal stimulation strategies. The results challenge existing perspectives by demonstrating that rectangular pulses lead to fewer circuit-level losses, making them competitive compared to non-rectangular alternatives. Although non-rectangular pulses can reduce neural activation thresholds, when circuit losses are included, they require 14-51% more energy than rectangular pulses. This suggests that rectangular pulses may be preferable for practical neurostimulator implementations.

A second contribution is the introduction of a quantitative framework to capture the impact of channel-to-channel variability on power efficiency. Due to inherent variations in electrode impedance and required stimulation amplitudes, individual channels have different power requirements. Conventional power management techniques often neglect this variability, resulting in low energy efficiency. Although several strategies have been proposed to enhance efficiency, a quantification of their efficacy is lacking in the literature. This thesis introduces a systematic methodology to analyze power losses in multichannel neurostimulation systems, enabling consistent benchmarking of existing strategies and providing a foundation for new application-specific approaches. Applying this methodology to previously published experimental data demonstrates that the effectiveness of power management strategies varies across applications, underscoring the necessity for application-specific optimization.

Building on these insights, the thesis proposes an advanced power-management approach designed specifically for the varying power needs of individual stimulation channels. This strategy incorporates a channel-specific regulating rectifier optimized for current-mode stimulation, capable of dynamically adjusting its output voltage without compliance monitoring. The rectifier quickly adapts to changing load conditions, enabling efficient time-division multiplexing and improved scalability in multichannel neurostimulation systems. It achieves a median efficiency of 84% on a dataset of intracortical visual stimulation, representing a 74% improvement over conventional fixed supplies and 6% compared to an 8-rail stepped supply.

In conclusion, this thesis offers critical insights into enhancing energy efficiency in multichannel electrical stimulation, contributing to advancing next-generation large-scale neurostimulator technologies. A key observation is the interdependence of multiple system-level factors, emphasizing the importance of a holistic optimization approach. Additionally, the findings highlight that optimal pulse width for minimizing activation energy varies significantly with pulse shape, underscoring the necessity of co-optimizing stimulation parameters for both physiological effectiveness and energy efficiency. The methods developed provide new perspectives on energy-efficient stimulator designs, and the proposed power-management approach shows promising results for efficient channel-specific voltage regulation and reduced output losses.