In this paper, we present a mathematical and simulational model of an ultrasound backscattering communication link for 1 mm3 mm-sized brain implants. The mathematical model and different simulations are validated by measurement. Furthermore, using a piezoelectric crystal and an ultrasound transducer in a water tank setup, two different ultrasound reflection-based modulation methods are presented and measurement results are discussed. We compare the model, simulation, and measurement to gain a better understanding of the channel response. The results shows the possibility of achieving a bandwidth of up to 140 kb/s using binary modulation and 280 kb/s with 4-level ASK.@en

In the domain of ultrasonically powered biomedical implants, there is an increasing interest in cm-scale ultrasonic receivers (RX). However, when a single-element transducer is used as the RX transducer, an uneven phase distribution across the RX area can significantly reduce the harvestable power. In this paper, we investigate the impact of lateral and angular misalignment on the acoustic field phase distribution across the RX surface. We show that, for a single-element RX transducer, lateral misalignment has minimal effect on the harvestable power, whereas even small angular misalignments can cause a considerable reduction, especially for larger RX sizes. We present a potential solution that consists of subdividing a large RX transducer (e.g. 20 × 20mm2) into smaller elements, which significantly improves power transfer efficiency by taking advantage of the smaller phase variation across the surface of each element. The trade-offs between achieving a minimum acceptable power transfer efficiency and managing the increased complexity in packaging and matching circuitry are also discussed. @en

Micromachined Ultrasonic Transducers (MUTs) are being explored as power converters in wirelessly powered biomedical implants. This paper investigates the role of mechanical support properties in piezoelectric MUTs (PMUTs) on their power conversion efficiency. For this purpose, a finite element model (FEM) of a PMUT array was developed and integrated with an equivalent circuit model (ECM). The study considered different mechanical support scenarios, from rigidly clamped to completely free. These were numerically analyzed and validated by impedance measurements and acoustic power transfer experiments on PMUT prototypes. The results show that reducing the mass of the mechanical support increases the Q factor, leading to a significant improvement in power conversion efficiency, with an efficiency increase factor of 5.6x from the clamped to the free case. This approach can potentially enhance overall power conversion efficiency, reduce the need for matching networks, and enable miniaturization in ultrasonically powered implants.@en

Aluminum Nitride (AlN) Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) are gaining interest for biomedical implant power due to biocompatibility and lowtemperature processing. However, due to the low piezoelectric coefficient of AlN PMUTs, storage capacitors are often used to accumulate ultrasonic power transferred over an extended time. The accumulated energy is then used to power a DC load, which leads to a long start-up time, and insufficient duty cycle for some applications. We present an ultrasonically powered system for biomedical implants capable of delivering mW-range instantaneous power to DC loads, without pre-storing it. The system features a 25 mm2 AlN PMUT, an inductive matching network, and an application-specific power management integrated circuit(ASIC). For an acoustic intensity of 360 mW/cm2 at the surface of the PMUT, an open-circuit voltage of 1.11 V and an aperture efficiency of 30.5 % are measured. Furthermore, by connecting a series-matching inductor to the PMUT, the highest-reported power delivered to the load (PDL) of 6.4 mW is measured over an optimal load of 7.6 Ω. Finally, together with the ASIC and at the intensity of 108 mW/cm2, our system delivers 1.04 mW DC power to a 3.3 kΩ load, which is over two orders of magnitude higher than the previously reported average DC power for AlN PMUTs. @en

Capacitive Micromachined Ultrasound Transducers (CMUTs) have many advantages compared to other ultrasonic transducer technologies, especially for implantable devices. However, they require a high bias voltage for efficient operation. To eliminate the need for an external bias voltage, a charge storage layer can be embedded in the dielectric. This study aims to compare the performance of Si 3 N 4 and Al 2 O 3 when used as a charge storage layer. By measuring the shift in the C-V curve, Si 3 N 4 exhibits a larger shift than Al 2 O 3 , indicating a better charge-trapping capability. When using the pre-charged CMUTs as power receivers, the Si 3 N 4 version harvested up to 80 mW -only a few mW more than the Al 2 O 3 - with an efficiency of about 50 %. Accelerated Lifetime Tests predict a lifetime of about 7.8 and 1.2 years for Si 3 N 4 and Al 2 O 3 respectively.@en

This paper presents a new communication method between micro-scale freely floating brain implants based on galvanic coupling (GC), called "Brain-Coupled Communication" (BCC). Since the transmission efficiency based on GC is highly dependent on the system’s geometry and the electromagnetic properties of the tissue, finite element models in COMSOL Multiphysics® are employed for characterizing the proposed method. Concurrent scaling of channel length (i.e., the distance between two implants), the inter-electrode distance (on a single implant), and electrode dimensions with a constant ratio down to 2 % of their typical values show an increase in the optimum frequency of the communication by 50 times (from 200 kHz to 10 MHz). This, in turn, yields a substantial increase in the channel bandwidth. The proposed method also shows excellent robustness against misalignment. Up to 60 ° of angular misalignment and 1 mm of lateral displacement result in a voltage-gain attenuation of less than 5 dB and 2 dB, respectively. Furthermore, a negligible shading effect between implants is observed by exploring multi-implant scenarios. Moreover, based on the conducted compliance study, no safety hazards were observed for the intended conditions. In conclusion, the proposed method exhibits a multitude of desirable qualities that position it as an excellent choice for establishing a network of freely floating brain implants.@en

This paper presents a novel multi-channel stimulation backend with a multi-bit delta-sigma control loop, which enables precise adjustment of the stimulation current through modulation of the supply voltage. This minimizes the overhead voltage of series circuitry to the stimulation load and avoids the associated energy loss. Additionally, to address the bandwidth limitations commonly encountered in battery-less implants, we propose incorporating amplitude and duration scaling of the arbitrary stimulation waveform. The waveform is programmable with 64 7-bit samples and 4 scaling factors per channel, resulting in a minimum of 68% data reduction per channel compared to using the waveform without scaling. The proposed circuits are designed and simulated in 180nm BCD technology occupying a total silicon area of 9mm2. The fully integrated backend has a minimum compliance voltage of 8.5V and features a switched-capacitor multi-output DC-DC converter (MODDC) with pulse-skipping capability, a CMOS-only high-voltage (HV) multiplexer, and a unique HV H-bridge. Programming a sine-wave stimulus with a 4mA amplitude and a duration of 256μs achieved a signal-to-noise ratio of 40dB within a 10kHz bandwidth. For the same waveform, power efficiencies of 94% and 68% were observed without and with MODDC, respectively. Additionally, when programming constant-current stimuli ranging from 0.26mA to 4mA, high efficiencies of 78-97% and 23-79.4% were achieved without and with MODDC, respectively.@en

This letter presents an ultrasonically powered dual-wavelength optogenetic device that targets simultaneous excitation and inhibition of neural activities, or in a broader sense, optical stimulation in two distinct wavelengths for targeting different populations of neurons. This can be applied to a variety of neurological disorders. The device features a load regulator circuit that shares the available power budget between two LEDs in a power-efficient and controlled way suppressing the need for adaptive matching and overvoltage protection circuits. Furthermore, the regulator circuit is capable of detecting power burst availability on the device and generating a control signal, accordingly. For 5.25 -mW acoustic power at the device's surface, the rectified voltage, and the total current load of the system are regulated to 2.79 V and 600A , respectively. The maximum chip and device efficiencies of 92.5% and 31.8% are measured, respectively. The total die area in 180- nm CMOS technology nose and the estimated system volume are 0.16/2 and 0.572/3 , respectively.@en

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.@en

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).@en

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. @en