An ultrasound powering TX ASIC for brain implants with autonomous on-chip standing-wave peak tracking for RX power (PDL) regulation is presented. With a proposed adiabatic power-sensing scheme, the TX consumes 43μW for power tracking, and the system achieves a settling time of <90ms while using the standing-wave peak-tracking FSM. The TX can achieve PDL improvement of up to 2.7× with a power-tracking accuracy of 82%.

The development of neurostimulation devices for visual and somatosensory prostheses is rapidly gaining momentum, where scaling the number of stimulation channels is crucial to improve treatment efficacy. To this end, optimizing power efficiency is critical, particularly in wirelessly powered systems. Although current-mode stimulation is generally preferred for safety reasons, it is often associated with significant power overhead losses in the output driver. This challenge becomes even more pronounced in multichannel configurations, where the required load voltage varies unpredictably across channels and over time. Compliance monitor circuits have been used to scale the output driver voltage supply, which in turn reduces losses and improves power efficiency. However, existing implementations lead to increased area and power overhead while lacking the ability to adapt rapidly to dynamic load conditions. This work presents a stimulator architecture that enables autonomous output supply scaling per channel, minimizing power dissipation across a wide range of currents and impedances without requiring explicit compliance monitoring. A two-channel prototype fabricated in 0:18 μm CMOS was validated with both linear loads and electrodes. The proposed strategy achieves outputdriver efficiencies above 80 % for stimulation currents of 30 k to 95 μA and load impedances from 30 k to 70 k, showing up to 4.3 times improvement compared to a fixed-voltage supply. Furthermore, the circuit shows rapid adaptation to changes in the required output voltage, enabling 100 μs stimulation pulses with a 1 μs inter-pulse delay. This feature allows time-division multiplexing across electrodes with varying load conditions, which could be further explored to increase the number of electrodes served per stimulation channel and thereby enhance scalability.

This paper presents a fully-integrated single-input dual-output power management unit operating both in volt age/current modes for powering mm-scale wireless neural im plants. The chip operates in voltage mode most of the time, using an active full-wave rectifier to regulate a low-voltage, high load output with high power efficiency and low output ripple (<32 mV_pp). It switches to current mode rectification when gen erating a high-voltage, low-load output. This dual-mode operation allows for flexible power distribution and configurable voltage ratios between the two outputs. The selected 40.68 MHz operating frequency reduces the required capacitances for input impedance matching and output filtering, enabling on-chip integration; the only external component is the receiver coil. A novel resonance breakup switch compatible with full-wave rectification ensures a smooth cold start-up of the chip without any external voltage supply. The chip was fabricated using 40-nm CMOS technology with an active area of 1.18 mm² and was tested in a wireless power link. Measurement results demonstrate that the chip can simultaneously regulate two outputs, V_LV = 1 V and V_HV = 2 V, with a tested maximum output power of 10 mW and 32.6 µW on V_LV and V_HV, respectively. At the optimal output power condition (P_LV = 4.4∼6.7 mW), the system achieves a peak power conversion efficiency of 85.87% and a peak end-to-end efficiency of 17.32% when regulating V_LV. The end-to-end efficiency drops by only 2.38% when regulating both outputs with R_LV = 225 Ω and R_HV = 400 kΩ.

Optical wireless power transfer (OWPT) has emerged as a promising technology for efficient wireless power transfer (WPT), offering advantages, such as directionality, suitability for far-field applications, and the ability to transfer power and data simultaneously. This comprehensive review classifies OWPT systems into laser power transfer (LPT) and light-emitting diodes (LED)-based OWPT. LPT uses the narrow divergence of laser beams for high-density, long-distance energy transfer, making it suitable for applications, such as satellites, autonomous drones, and electric vehicle charging. In contrast, LED-based OWPT offers a safer, more cost-effective solution for low-power applications, especially in the Internet of Things (IoT) domain. It offers advantages, such as lower power consumption and fewer safety restrictions compared to LPT. Innovations in LPT, such as high-intensity laser power beaming, distributed laser charging (DLC), adaptive DLC, simultaneous lightwave information and power transfer, and resonant beam charging are discussed. Also, recent advancements in LED-OWPT, including single-lens and double-lens systems, collimation techniques, and multi-LED arrays, are explored for their potential in powering IoT devices, wearable electronics, and smart infrastructure. First, we present a radar chart comparing various WPT techniques with respect to performance criteria. After reviewing the methods of LPT and LED-OWPT in detail, a comparison of these techniques is provided, evaluating their strengths, limitations, and application suitability. A concluding radar chart offers insights for optimizing OWPT systems tailored to specific applications. Future research directions are identified, emphasizing the need for further advancements in beam alignment, safety protocols, and hybrid systems to enhance OWPT’s scalability and practicality in real-world scenarios.

Miniaturization of next-generation active neural implants requires novel micro-packaging solutions that can maintain their long-term coating performance in the body. This work presents two thin-film coatings and evaluates their biostability and in vivo performance over a 7-month animal study. To evaluate the coatings on representative surfaces, two silicon microchips with different surface microtopography are used. Microchips are coated with either a ≈100 nm thick inorganic hafnium-based multilayer deposited via atomic layer deposition (ALD-ML), or a ≈6 µm thick hybrid organic–inorganic Parylene C and titanium-based ALD multilayer stack (ParC-ALD-ML). After 7 months of direct exposure to the body environment, the multilayer coatings are evaluated using optical and cross-sectional scanning electron microscopy. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is also used to evaluate the chemical stability and barrier performance of the layers after long-term exposure to body media. Results showed the excellent biostability of the 100 nm ALD-ML coating with no ionic penetration within the layer. For the ParC-ALD-ML, concurrent surface degradation and ion ingress are detected within the top ≈70 nm of the outer Parylene C layer. The results and evaluation techniques presented here can enable future material selection, packaging, and analysis, enhancing the functional stability of future chip-embedded neural implants.

Correction to: Nature Communicationshttps://doi.org/10.1038/s41467-024-55298-4, published online 02 January 2025 In this article the following sentence was omitted from the acknowledgements section, ‘This research was funded by the following projects: Project CANDO (Controlling Network Dynamics with Optogenetics), funded by UK EPSRC (grant ref: NS/A000026/1) and the Wellcome Trust (contract ref: 102037/Z/13/Z)’. The original article has been corrected.

Objectives: Current techniques in brain stimulation are still largely based on a phrenologic approach that a single brain target can treat a brain disorder. Nevertheless, meta-analyses of brain implants indicate an overall success rate of 50% improvement in 50% of patients, irrespective of the brain-related disorder. Thus, there is still a large margin for improvement. The goal of this manuscript is to 1) develop a general theoretical framework of brain functioning that is amenable to surgical neuromodulation, and 2) describe the engineering requirements of the next generation of implantable brain stimulators that follow from this theoretic model. Materials and Methods: A neuroscience and engineering literature review was performed to develop a universal theoretical model of brain functioning and dysfunctioning amenable to surgical neuromodulation. Results: Even though a single target can modulate an entire network, research in network science reveals that many brain disorders are the consequence of maladaptive interactions among multiple networks rather than a single network. Consequently, targeting the main connector hubs of those multiple interacting networks involved in a brain disorder is theoretically more beneficial. We, thus, envision next-generation network implants that will rely on distributed, multisite neuromodulation targeting correlated and anticorrelated interacting brain networks, juxtaposing alternative implant configurations, and finally providing solid recommendations for the realization of such implants. In doing so, this study pinpoints the potential shortcomings of other similar efforts in the field, which somehow fall short of the requirements. Conclusion: The concept of network stimulation holds great promise as a universal approach for treating neurologic and psychiatric disorders.

State-of-the-art intracortical neural recording and stimulation systems rely on subdural implants tethered to a cranial implant which itself has a wireless power and data link to the outside world [1] (Fig. 6.2.1). However, this tethered configuration poses challenges such as scarring and potential damage to the surrounding tissue due to strain and micromotions, making this approach unsuitable for chronical implants [2]. Consequently, there is growing interest in wireless connections between cranial and subdural implants. This paper focuses on wireless powering between implants, traversing the dura and cerebrospinal fluid (CSF) tissue layers over distances of 0.5 to 1cm (transdural powering). With modern burr-hole craniotomy, the hole drilled in the skull is 6mm in diameter, limiting the available size for the TX. Moreover, the power dissipation of the TX must be low to keep tissue heating below 1°C [3]. RF and optical modalities suffer from higher attenuation in tissue compared to ultrasound (0.6dB/cm/MHz) [4]. Furthermore, for transdural powering, power losses from reflections at medium interfaces (e.g., skull) are avoided, making ultrasound (US) a prime candidate for efficient in-body wireless power transfer. US is also preferable to inductive powering since US beam steering up to large angles (>45°) is needed to maximize power delivery and compensate for brain micromotions of up to ±4mm [5] and misalignment during surgery. However, prior art US driving systems either use single-phase transducer driving [6, 7], incapable of beam steering, or use class D drivers with low power transfer efficiency (PTE) [8, 9]. A phased array with increased driving efficiency was presented in [10], but it cannot perform beam steering without grating lobes that can be eliminated with miniature transducers with a pitch close to λ/2. To facilitate direct integration between CMOS and the transducer array, the CMOS driving units should also be pitch matched [8, 9].

The key challenges in designing a multi-channel biosignal acquisition system for an ambulatory or invasive medical application with a high channel count are reducing the power consumption, area consumption and the outgoing wire count. This article proposes a spread-spectrum modulated biosignal acquisition system using a shared amplifier and an analog-to-digital converter (ADC). We propose a design method to optimize a recording system for a given application based on the required SNR performance, number of inputs, and area. The proposed method is tested and validated on real pre-recorded atrial electrograms and achieves an average percentage root-mean-square difference (PRD) performance of 2.65% and 3.02% for sinus rhythm (SR) and atrial fibrillation (AF), respectively by using pseudo-random binary-sequence (PRBS) codes with a code-length of 511, for 16 inputs. We implement a 4-input spread-spectrum analog front-end in a 0.18 μ m CMOS process to demonstrate the proposed approach. The analog front-end consists of a shared amplifier, a 2nd order Σ Δ ADC sampled at 7.8 MHz, used for digitization, and an on-chip 7-bit PRBS generator. It achieves a number-of-inputs to outgoing-wire ratio of 4:1 while consuming 23 μ A/input including biasing from a 1.8 V power supply and 0.067 mm ² in area.