Search Results (7)

Wireless microsystems for neural signal recording have emerged as a solution to overcome the limitations of tethered systems, which restrict the mobility of subjects and introduce noise interference. However, existing microsystems often face data throughput, signal processing, and long-distance wireless transmission challenges. This study presents a high-performance wireless microsystem capable of 32-channel, 30 kHz real-time recording, featuring Field Programmable Gate Array (FPGA)-based signal processing to reduce transmission load. The microsystem is integrated with platinum nanoparticles/poly (3,4-ethylenedioxythiophene) polystyrene sulfonate-enhanced microelectrode arrays for improved signal quality. A custom NeuroWireless platform was developed for seamless data reception and storage. Experimental validation in rats demonstrated the microsystem’s ability to detect spikes and local field potentials from the hippocampal CA1 and CA2 subregions. Comparative analysis of the neural signals revealed distinct activity patterns between these subregions. The wireless microsystem achieves high accuracy and throughput over distances up to 30 m, demonstrating its resilience and potential for neuroscience research. This work provides a compact, adaptable solution for multi-channel neural signal detection and offers a foundation for future applications in brain–computer interfaces. Full article

We present in this paper a low-noise, low-power CMOS operational transconductance amplifier designed for the preconditioning stage of implantable neural recording microsystems. The proposed single-stage amplifier utilizes a combination of recently published techniques, including cross-coupled devices in a recycling folded-cascode topology with positive feedback, to achieve high DC voltage gain and unity-gain bandwidth while minimizing power consumption. A mixed N-type and P-type MOSFET input stage enhances input common-mode performance. Designed and implemented in a 0.18-µm CMOS process with a 1.8 V supply, post-layout simulations demonstrate an open-loop voltage gain of 97.23 dB, a 2.91 MHz unity-gain bandwidth (with a 1 pF load), and an input-referred noise of 4.75 μV_rms. The total power dissipation, including bias circuitry, is 5.43 μW, and the amplifier occupies a chip area of 0.0055 mm². Integrated into a conventional neural recording amplifier configuration, the proposed amplifier achieves a simulated input-referred noise of 5.73 µV_rms over a 1 Hz to 10 kHz bandwidth with a power consumption of 5.6 µW. This performance makes it suitable for amplifying both action potential and local field potential signals. The amplifier provides an output voltage swing of 0.976 V_pp with a total harmonic distortion of −62.68 dB at 1 kHz. Full article

This paper presents a design and optimization method utilizing inductive coupling coils for wireless power transfer in implantable neural recording microsystems, aiming at maximizing power transfer efficiency, which is essential for reducing externally transmitted power and ensuring biological tissue safety. The modeling of inductive coupling is simplified by combining semi-empirical formulations with theoretical models. By introducing the optimal resonant load transformation, the coil optimization is decoupled from an actual load impedance. The complete design optimization process of the coil parameters is given, which takes the maximum theoretical power transfer efficiency as the objective function. When the actual load changes, only the load transformation network needs to be updated instead of rerunning the entire optimization process. Planar spiral coils are designed to power neural recording implants given the challenges of limited implantable space, stringent low-profile restrictions, high-power transmission requirements and biocompatibility. The modeling calculation, electromagnetic simulation and measurement results are compared. The operating frequency of the designed inductive coupling is 13.56 MHz, the outer diameter of the implanted coil is 10 mm and the working distance between the external coil and the implanted coil is 10 mm. The measured power transfer efficiency is 70%, which is close to the maximum theoretical transfer efficiency of 71.9%, confirming the effectiveness of this method. Full article

As the basic tools for neuroscience research, invasive neural recording devices can obtain high-resolution neuronal activity signals through electrodes connected to the subject’s brain. Existing wireless neural recording devices are large in size or need external large-scale equipment for wireless power supply, which limits their application. Here, we developed an ultra-low-noise, low power and miniaturized dual-channel wireless neural recording microsystem. With the full-differential front-end structure of the dual operational amplifiers (op-amps), the noise level and power consumption are notably reduced. The hierarchical microassembly technology, which integrates wafer-level packaged op-amps and the miniaturized Bluetooth module, dramatically reduces the size of the wireless neural recording microsystem. The microsystem shows a less than 100 nV/$\sqrt{\mathrm{Hz}}$ ultra-low noise level, about 10 mW low power consumption, and 9 × 7 × 5 mm${}^3$ small size. The neural recording ability was then demonstrated in saline and a chronic rat model. Because of its miniaturization, it can be applied to freely behaving small animals, such as rats. Its features of ultra-low noise and high bandwidth are conducive to low-amplitude neural signal recording, which may help advance neuroscientific discovery. Full article

We have developed a prototype cortical neural sensing microsystem for brain implantable neuroengineering applications. Its key feature is that both the transmission of broadband, multichannel neural data and power required for the embedded microelectronics are provided by optical fiber access. The fiber-optic system is aimed at enabling neural recording from rodents and primates by converting cortical signals to a digital stream of infrared light pulses. In the full microsystem whose performance is summarized in this paper, an analog-to-digital converter and a low power digital controller IC have been integrated with a low threshold, semiconductor laser to extract the digitized neural signals optically from the implantable unit. The microsystem also acquires electrical power and synchronization clocks via optical fibers from an external laser by using a highly efficient photovoltaic cell on board. The implantable unit employs a flexible polymer substrate to integrate analog and digital microelectronics and on-chip optoelectronic components, while adapting to the anatomical and physiological constraints of the environment. A low power analog CMOS chip, which includes preamplifier and multiplexing circuitry, is directly flip-chip bonded to the microelectrode array to form the cortical neurosensor device. Full article

This paper presents the design and implementation of an integrated wireless microsystem platform that provides the possibility to support versatile implantable neural sensing devices in free laboratory rats. Inductive coupled coils with low dropout regulator design allows true long-term recording without limitation of battery capacity. A 16-channel analog front end chip located on the headstage is designed for high channel account neural signal conditioning with low current consumption and noise. Two types of implantable electrodes including grid electrode and 3D probe array are also presented for brain surface recording and 3D biopotential acquisition in the implanted target volume of tissue. The overall system consumes less than 20 mA with small form factor, 3.9 × 3.9 cm² mainboard and 1.8 × 3.4 cm² headstage, is packaged into a backpack for rats. Practical in vivo recordings including auditory response, brain resection tissue and PZT-induced seizures recording demonstrate the correct function of the proposed microsystem. Presented achievements addressed the aforementioned properties by combining MEMS neural sensors, low-power circuit designs and commercial chips into system-level integration. Full article

The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field. Full article