Analysis of Power Losses and the Efficacy of Power Minimization Strategies in Multichannel Electrical Stimulation Systems

TL;DR

This paper tackles the power bottleneck in large-scale multichannel neurostimulation by introducing a Monte Carlo-based framework that uses distributions of stimulation thresholds and electrode impedances to quantify power losses under fixed, global, and stepped supply strategies. By compiling 26 datasets across four neural stimulation modalities, the authors synthesize channel-load voltages $V_{ ext{load}}=I_{ ext{th}}Z$ and compute per-channel losses and efficiencies for each strategy. The results show stepped voltage supplies with multiple rails markedly improve efficiency, especially in high-channel-count applications with substantial inter-channel variability, while global scaling is advantageous for low-channel-count scenarios; fixed supplies perform worst. The methodology enables rigorous evaluation of efficiency–complexity trade-offs, guiding design decisions to support scalable, wirelessly powered neuroprosthetic systems while accounting for application-specific variability and time-evolving impedance.

Abstract

Neuroprosthetic devices require multichannel stimulator systems with an increasing number of channels. However, there are inherent power losses in typical multichannel stimulation circuits caused by a mismatch between the power supply voltage and the voltage required at each electrode to successfully stimulate tissue. This imposes a bottleneck towards high-channel-count devices, which is particularly severe in wirelessly-powered devices. Hence, advances in the power efficiency of stimulation systems are critical. To support these advances, this paper presents a methodology to identify and quantify power losses associated with different power supply scaling strategies in multichannel stimulation systems. The proposed methodology utilizes distributions of stimulation amplitudes and electrode impedances to calculate power losses in multichannel systems. Experimental data from previously published studies spanning various stimulation applications were analyzed to evaluate the performance of fixed, global, and stepped supply scaling methods, focusing on their impact on power dissipation and efficiency. Variability in output conditions results in low power efficiency in multichannel stimulation systems across all applications. Stepped voltage scaling demonstrated substantial efficiency improvements, achieving an increase of 67 % to 146 %, particularly in high-channel-count applications with significant variability in tissue impedance. Global scaling, by contrast, was more advantageous for systems with fewer channels. The findings highlight the importance of tailoring power management strategies to specific applications to optimize efficiency while minimizing system complexity. The proposed methodology offers a framework for evaluating efficiency-complexity trade-offs, advancing the design of scalable neurostimulation systems.

Figures (11)

• Figure 1: Illustration of the overhead losses in current-mode stimulation (CMS) in a bipolar electrode configuration. (a) Conventional output stage for CMS with a fixed voltage supply $V_{\textrm{DD}}$; (b) Example of the load voltage ($V_{\textrm{load}}$) as a result of the current pulses delivered to the tissue. The mismatch between the load voltage and supply voltage (indicated in the grey area) leads to power dissipation in the output driver; (c) Illustration of how a scaled voltage supply can reduce the power dissipation in the output driver and thus increase the power efficiency, for the example in (b).
• Figure 2: Illustration of the overhead losses for different voltage scaling strategies in the example of a system with five channels. Dashed, horizontal lines indicate the available voltage rails, and the colored bars the load voltage ($V_{\textrm{load}}$) of the specific channel, where the color indicates to which voltage rail the channel is connected. Grey rectangles indicate the overhead losses. (a) In the case of a fixed voltage supply, all channels share the same voltage supply. (b) In the case of ideal supply scaling, each channel has a specific voltage supply matched to its load voltage. Thus, the overhead losses are zero. (c) With a global supply scaling strategy, a shared supply voltage is scaled to the worst-case $V_{\textrm{load}}$ (channel 2 in the example), eliminating all overhead losses for that channel and reducing overhead losses in the other channels compared to the fixed voltage strategy. (d) A stepped voltage supply strategy with 4.0 rails. Multiple voltage rails are available, and each channel is connected to the nearest rail above its load voltage.
• Figure 3: Load (a) voltage and (b) power per channel distributions grouped by application.
• Figure 4: Load voltage and power distributions of the individual datasets. Markers indicate the median value and error bars the IQR.
• Figure 5: $V_{\rm fixed}$ for different channel yield settings across the different applications.