Objective. 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 mismatches 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. Approach. The methodology uses distributions of stimulation amplitudes and electrode impedances to calculate power losses in multichannel systems. Experimental data from prior 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. Main Results. Variability in output conditions results in low power efficiency in multichannel stimulation systems across all applications. Stepped voltage scaling demonstrates substantial efficiency improvements, achieving an increase of 43% to 100%, particularly in high-channel-count applications with significant variability in tissue impedance. In contrast, global scaling proved effective only in systems with fewer channels and minimal inter-channel variation. Significance. The findings highlight the importance of tailoring power management strategies to specific applications to optimize efficiency while minimizing system complexity. The proposed methodology provides a framework for evaluating trade-offs between efficiency and system complexity, facilitating the design of more scalable and power-efficient neurostimulation systems.

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.

Responsive neuromodulation is increasingly being used to treat patients with neuropsychiatric diseases. Yet, inefficient bridges between traditional and new materials and technological innovations impede advancements in neurostimulation tools. Signaling in the brain is accomplished predominantly by ion flux rather than the movement of electrons. However, the status quo for the acquisition of neural signals is using materials, such as noble metals, that can only interact with electrons. As a result, ions accumulate at the biotic/abiotic interface, creating a double-layer capacitance that increases impedance and negatively impacts the efficiency of neural interrogation. Alternative materials, such as conducting polymers, allow ion penetration in the matrix, creating a volumetric capacitor (two orders of magnitude larger than an area-dependent capacitor) that lowers the impedance and increases the spatiotemporal resolution of the recording/stimulation. On the other hand, the increased development and integration capabilities of CMOS-based back-end electronics have enabled the creation of increasingly powerful and energy-efficient microchips. These include stimulation and recording systems-on-a-chip (SoCs) with up to tens of thousands of channels, fully integrated circuitry for stimulation, signal conditioning, digitation, wireless power and data telemetry, and on-chip signal processing. Here, we aim to compile information on the best component for each building block and try to strengthen the vision that bridges the gap among various materials and technologies in an effort to advance neurostimulation tools and promote a solution-centric way of considering their complex problems.

Developing neuroprosthetic bioelectronic devices requires wirelessly-powered implantable stimulator systems with hundreds to thousands of output channels. Power efficiency optimization is crucial for scaling up the number of output channels. Current-mode electrical stimulation is favored for safety but is power-inefficient in conventional designs, particularly in multichannel stimulators. An adaptive voltage supply can improve power efficiency, but implementing channel-specific voltage supplies in large-scale systems is challenging. Conventional power management suffers from losses and low efficiency due to multiple conversion stages. This work proposes a multichannel current-mode stimulator with a parallel, adaptive ac/dc power management strategy using single-stage phase-controlled converters to prevent cascaded losses. This allows for generating channel-specific supply voltages within a small area for high power efficiency and high-density electrical stimulation. The proposed circuit was designed and simulated using TSMC 180 nm technology and demonstrates an improvement in the power efficiency of up to 45% with respect to a conventional power-management strategy using a fixed supply voltage.

Electrical stimulation is proven to be an effective way of neuromodulation in bioelectronic medicine (e.g. cochlear implants, deep brain stimulators, etc.), delivering localized treatment by the means of electrical pulses. To increase the stimulation efficiency and neural-type selectivity, there is an increasing interest to employ non-rectangular stimulation waveforms [1-4]. Even though delivering and storing digital data at the stimulator provides the highest flexibility for generating stimulation waveforms, state-of-the-art approaches suffer either from poor resolution or the requirement of high data bandwidth for wirelessly powered implants [2]. Using Analog waveform generators is an alternative approach at the cost of extra implementation complexity for each type of waveform [3]. To fulfill the same goals as employing arbitrary waveforms for stimulation, we propose to shape the typical rectangular waveform using a programmable first-order low-pass filter, mimicking the natural filtering characteristic of the neural membrane. Using bio-realistic modeling, we show that such a pre-filtered waveform requires less or equal energy for the activation of neurons when compared with other energy-efficient waveforms (e.g. Gaussian). Notably, this comes at the low cost of only one extra programmable parameter (i.e., the filter’s corner frequency), on top of the typical duration and amplitude parameters. The basic concept of this work is driven by the fact that the natural low-pass characteristic of the neuron’s membrane limits the energy transfer efficiency from the stimulator to the cell. Thus, it is proposed to pre-filter the high-frequency components of the stimulus [4]. The method is validated for a Hodgkin-Huxley (HH) axon-cable model using NEURON v8.0 software. The required activation energy is simulated for rectangular, Gaussian, half-sine, triangular, ramp-up, and ramp-down waveforms, all with pulse durations of 10-1000µs, and low-pass filtered with cut-off frequencies of 0.5-50kHz. Simulations show a 51.5% reduction in the required activation energy for the shortest rectangular pulse (i.e., 10-μs pulse width) after filtering at 5kHz. It is also shown that the minimum required activation energy can be decreased by 11.04%, 9.49%, 8.28%, 1.81%, 0.17%, and 0% when an appropriate pre-filter is applied to the rectangular, ramp-down, ramp-up, half-sine, triangular, and Gaussian waveforms, respectively. Finally, a perspective usage of this method to improve the selectivity of electrical stimulation is drawn.

This work proposes a guideline for designing more energy-efficient electrical stimulators by analyzing the frequency spectrum of the stimuli. It is shown that the natural low-pass characteristic of the neuron’s membrane limits the energy transfer efficiency from the stimulator to the cell. Thus, to improve the transfer efficiency, it is proposed to pre-filter the high-frequency components of the stimulus. The method is validated for a Hodgkin-Huxley (HH) axon cable model using NEURON v8.0 software. To this end, the required activation energy is simulated for rectangular pulses with durations between 10 µs and 5 ms, which are low-pass filtered with cut-off frequencies of 0.5-50 kHz. Simulations show a 51.5% reduction in the required activation energy for the shortest pulse width (i.e., 10 µs) after filtering at 5 kHz. It is also shown that the minimum required activation energy can be decreased by 11.04% when an appropriate pre-filter is applied. Finally, we draw a perspective for future use of this method to improve the selectivity of electrical stimulation.

In neuromodulation applications, conventional current mode stimulation is often preferred over its voltage mode equivalent due to its good control of the injected charge. However, it comes at the cost of less energy-efficient output stages. To increase energy efficiency, recent studies have explored non-rectangular stimuli. The current work highlights the importance of an adaptive supply for an output stage with programmable non-rectangular stimuli and accordingly proposes a system-level architecture for multi-channel stimulators. In the proposed architecture, a multi-output DC/DC Converter (DDC) allows each channel to choose among the available supply levels (i.e., DDC outputs) independently and based on its instant voltage/current requirement. A system-level analysis is carried out in Matlab to calculate the possible energy savings of this solution, compared to the conventional approach with a fixed supply. The energy savings have been simulated for a variety of supply levels and waveform amplitudes, suggesting energy savings of up to 83% when employing 6 DDC outputs and the lowest current amplitude explored (250A), and as high as 26% for a full-scale amplitude (4 mA).

Power efficiency in electrical stimulator circuits is crucial for developing large-scale multichannel applications like bidirectional brain-computer interfaces and neuroprosthetic devices. Many state-of-the-art papers have suggested that some non-rectangular pulse shapes are more energy-efficient for exciting neural excitation than the conventional rectangular shape. However, additional losses in the stimulator circuit, which arise from employing such pulses, were not considered. In this work, we analyze the total energy efficiency of a stimulation system featuring non-rectangular stimuli, taking into account the losses in the stimulator circuit. To this end, activation current thresholds for different pulse shapes and durations in cortical neurons are modeled, and the energy required to generate the pulses from a constant voltage supply is calculated. The proposed calculation reveals an energy increase of 14%–51% for non-rectangular pulses compared to the conventional rectangular stimuli, instead of the decrease claimed in previous literature. This result indicates that a rectangular stimulation pulse is more power-efficient than the tested alternative shapes in large-scale multichannel electrical stimulation systems.