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Three-coil inductive power transfer is the state-of-the-art solution to power multiple miniaturised neural implants. However, the maximum delivered power is limited by the efficiency of the powering link and safety constrains. Here we propose a frequency-switching inductive link, where the passive resonator normally used in a three-coil link is replaced by an active resonator. It receives power from the external transmitter via a two-coil inductive link at the low frequency of 13.56 MHz. Then, it switches the operating frequency to the higher frequency of 433.92 MHz through a dedicated circuitry. Last, it transmits power to 1024 miniaturised implants via a three-coil inductive link using an array of 37 focusing resonators for a brain coverage of 163.84 mm 2 . Our simulations reported a power transfer efficiency of 0.013 % and a maximum power delivered to the load of 1970 μW under safety-constrains, which are respectively two orders of magnitude and more than six decades higher compared to an equivalent passive three-coil link. The frequency-switching inductive system is a scalable and highly versatile solution for wireless, miniaturised and large-scale neural interfaces.

Wireless, miniaturised and distributed neural interfaces are emerging neurotechnologies. Although extensive research efforts contribute to their technological advancement, the need for real-time systems enabling simultaneous wireless information and power transfer toward distributed neural implants remains crucial. Here we present a complete wearable system including a software for real-time image capturing, processing and digital data transfer; an hardware for high radiofrequency generation and modulation via amplitude shift keying; and a 3-coil inductive link adapt to operate with multiple miniaturised receivers. The system operates in real-time with a maximum frame rate of 20 Hz, reconstructing each frame with a matrix of 32 × 32 pixels. The device generates a carrier frequency of 433.92 MHz. It transmits the highest power of 32 dBm with a data rate of 6 Mbps and a variable modulation index as low as 8 %, thus potentially enabling wireless communication with 1024 miniaturised and distributed intracortical microstimulators. The system is primarily conceived as an external wearable device for distributed cortical visual prosthesis covering a visual field of 20 ° . At the same time, it is modular and versatile, being suitable for multiple applications requiring simultaneous wireless information and power transfer to large-scale neural interfaces.

During the past two decades, a number of two-terminal switching devices have been demonstrated in the literature. They typically exhibit hysteric behavior in the current-to-voltage characteristics. These devices have often been also referred to as memristive devices. Their capacity to switch and exhibit electrical hysteresis has made them well-suited for applications such as data storage, in-memory computing, and in-sensor computing or in-memory sensing. The aim of this perspective paper is to is twofold. Firstly, it seeks to provide a comprehensive examination of the existing research findings in the field and engage in a critical discussion regarding the potential for the development of new non-Von-Neumann computing machines that can seamlessly integrate sensing and computing within memory units. Secondly, this paper aims to demonstrate the practical application of such an innovative approach in the realm of cancer medicine. Specifically, it explores the modern concept of employing multiple cancer markers simultaneously to enhance the efficiency of diagnostic processes in cancer medicine.

Closed-loop neural implants based on continuous brain activity recording and intracortical microstimulation are extremely effective and promising devices to monitor and address many neurodegenerative diseases. The efficiency of these devices depends on the robustness of the designed circuits which rely on precise electrical equivalent models of the electrode/brain interface. This is true in the case of amplifiers for differential recording, voltage or current drivers for neurostimulation, and potentiostats for electrochemical bio-sensing. This is of paramount importance, especially for the next generation of wireless and ultra-miniaturised CMOS neural implants. Circuits are usually designed and optimized considering the electrode/brain impedance with a simple electrical equivalent model whose parameters are stationary over time. However, the electrode/brain interfacial impedance varies simultaneously in frequency and in time after implantation. The aim of this study is to monitor the impedance changes occurring on microelectrodes inserted in ex-vivo porcine brains to derive an opportune electrode/brain model describing the system and its evolution in time. In particular, impedance spectroscopy measurements have been performed for 144 hours to characterise the evolution of the electrochemical behaviour in two different setups analysing both the neural recording and the chronic stimulation scenarios. Then, different equivalent electrical circuit models have been proposed to describe the system. Results showed a decrease in the resistance to charge transfer, attributed to the interaction between biological material and the electrode surface. These findings are crucial to support circuit designers in the field of neural implants.

In neurostimulation, wireless power transfer is an efficient technology to overcome several limitations affecting medical devices currently used in clinical practice. Several methods were developed over the years for wireless power transfer. In this review article, we report and discuss the three most relevant methodologies for extremely miniaturised implantable neurostimulators: ultrasound coupling, inductive coupling and capacitive coupling. For each powering method, the discussion starts describing the physical working principle. In particular, we focus on the challenges given by the miniaturisation of the implanted integrated circuits and the related ad-hoc solutions for wireless power transfer. Then, we present recent developments and progresses in wireless power transfer for biomedical applications. Last, we compare each technique based on key performance indicators to highlight the most relevant and innovative solutions suitable for neurostimulation, with the gaze turned towards miniaturisation.