A Low-Noise, Wireless, Frequency-Shaping Neural Recorder (original) (raw)
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Wireless Neural Recording With Single Low-Power Integrated Circuit
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2000
We present benchtop and in vivo experimental results from an integrated circuit designed for wireless implantable neural recording applications. The chip, which was fabricated in a commercially available 0.6-μm 2P3M BiCMOS process, contains 100 amplifiers, a 10-bit analog-to-digital converter (ADC), 100 threshold-based spike detectors, and a 902-928 MHz frequency-shift-keying (FSK) transmitter. Neural signals from a selected amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power/command receiving coil and a 100-nF capacitor.
A wireless microsystem with digital data compression for neural spike recording
Microelectronic Engineering, 2011
The paper describes a multi-channel neural spike recording system sensing and processing the action potentials (APs) detected by an electrode array implanted in the cortex of freely-behaving small laboratory animals. The core of the system is a custom integrated circuit (IC), with low-noise analog front-end interfaced to a 16 electrode array followed by a single 8-bit SAR ADC, a digital signal compression and a 400-MHz wireless transmission units. Data compression is implemented by detecting action potentials and storing up to 20 points per each spike waveform. The choice greatly improves data quality and allows single spike identification. The transmitter delivers a 1.25-Mbit/s data rate coded with a Manchestercoded frequency shift keying (MC-FSK) within a 3-MHz bandwidth. An overall power consumption of 17.2 mW makes possible to reach a transmission range larger than 20-m. The IC is mounted on a small and light printed circuit board. Two AAA batteries, set in a pack positioned on the back of the animal, power the system that can work continuously for more than 100 h.
A wireless neural interface for chronic recording
2008 IEEE Biomedical Circuits and Systems Conference, 2008
A primary goal of the Integrated Neural Interface Project (INIP) is to develop a wireless, implantable device capable of recording neural activity from 100 micromachined electrodes. The heart of this recording system is a low-power integrated circuit that amplifies 100 weak neural signals, detects spikes with programmable threshold-crossing circuits, and returns these data via digital radio telemetry. The chip receives power, clock, and command signals through a coil-to-coil inductive link. Here we report that the isolated integrated circuit successfully recorded and wirelessly transmitted digitized electrical activity from peripheral nerve and cortex at 15.7 kS/s. The chip also simultaneously performed accurate on-chip spike detection and wirelessly transmitted the spike threshold-crossing data. We also present preliminary successful results from full system integration and packaging.
2010
This paper reports a multi-channel neural spike recording system-on-chip (SoC) with digital data compression and wireless telemetry. The circuit (16 active channels plus 48 ”mute” lines) demonstrates the potentials of a 64-channel system made by a low-noise analog front-end, a single 8-bit SAR ADC, followed by digital signal compression and transmission units. The 400-MHz transmitter uses a Manchester-Coded Frequency Shift Keying (MC-FSK) with low modulation index. In this way a 1.25-Mbit/s data rate is delivered within a band of about 3MHz. Compression of the raw data is implemented by detecting the action potential (AP) spikes and storing up to 20 points for each waveform. The choice greatly improves data quality and allows single spike identification. The chip, fabricated in 0.35-μm CMOS AMS process, occupies a 3.1 × 2.7 mm2 area. A 4-m transmission range is reached with an overall power consumption of 16.6 mW. The figure translates into a power budget of 269 μW per channel for a complete 64-channel system, which favorably compares with the results in literature. The system performance has been verified in in-vivo neural recording experiments.
A 128Channel 6 mW Wireless Neural Recording IC With Spike Feature Extraction and UWB Transmitter
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2009
This paper reports a 128-channel neural recording integrated circuit (IC) with on-the-fly spike feature extraction and wireless telemetry. The chip consists of eight 16-channel front-end recording blocks, spike detection and feature extraction digital signal processor (DSP), ultra wideband (UWB) transmitter, and on-chip bias generators. Each recording channel has amplifiers with programmable gain and bandwidth to accommodate different types of biological signals. An analog-to-digital converter (ADC) shared by 16 amplifiers through time-multiplexing results in a balanced trade-off between the power consumption and chip area. A nonlinear energy operator (NEO) based spike detector is implemented for identifying spikes, which are further processed by a digital frequency-shaping filter. The computationally efficient spike detection and feature extraction algorithms attribute to an auspicious DSP implementation on-chip. UWB telemetry is designed to wirelessly transfer raw data from 128 recording channels at a data rate of 90 Mbit/s. The chip is realized in 0.35 m complementary metal-oxide-semiconductor (CMOS) process with an area of 8.8 7.2 mm 2 and consumes 6 mW by employing a sequential turn-on architecture that selectively powers off idle analog circuit blocks. The chip has been tested for electrical specifications and verified in an ex vivo biological environment.
Integrated low noise low power interface for neural bio-potentials recording and conditioning
Bioengineered and Bioinspired Systems II, 2005
The recent progress in both neurobiology and microelectronics suggests the creation of new, powerful tools to investigate the basic mechanisms of brain functionality. In particular, a lot of efforts are spent by scientific community to define new frameworks devoted to the analysis of in-vitro cultured neurons. One possible approach is recording their spiking activity to monitor the coordinated cellular behavior and get insights about neural plasticity. Due to the nature of neurons action-potentials, when considering the design of an integrated microelectronics-based recording system, a number of problems arise. First, one would desire to have a high number of recording sites (i.e. several hundreds): this poses constraints on silicon area and power consumption. In this regard, our aim is to integrate-through on-chip post-processing techniques-hundreds of bio-compatible micro-sensors together with CMOS standard-process low-power (i.e. some tenths of µW per channel) conditioning electronics. Each recording channel is provided with sampling electronics to insure synchronous recording so that, for example, cross-correlation between signals coming from different sites can be performed. Extra-cellular potentials are in the range of [50 − 150] µV , so a comparison in terms of noise-efficiency was carried out among different architectures and very low-noise pre-amplification electronics (i.e. less than 6.5 µV rms ) was designed. As spikes measurements are made with respect to the voltage of a reference electrode, we opted for an AC-coupled differential-input preamplifier provided with band-pass filtering capability. To achieve this, we implemented large time-constant (up to seconds) integrated components in the preamp feedback path. Thus, we got rid also of random slow-drifting DC-offsets and common mode signals. The paper will present our achievements in the design and implementation of a fully integrated bio-abio interface to record neural spiking activity. In particular, preliminary results will be reported.
Journal of Low Power Electronics and Applications, 2012
This paper reports a multi-channel neural spike recording system-on-chip with digital data compression and wireless telemetry. The circuit consists of 16 amplifiers, an analog time-division multiplexer, a single 8 bit analog-to-digital converter, a digital signal compression unit and a wireless transmitter. Although only 16 amplifiers are integrated in our current die version, the whole system is designed to work with 64, demonstrating the feasibility of a digital processing and narrowband wireless transmission of 64 neural recording channels. Compression of the raw data is achieved by detecting the action potentials (APs) and storing 20 samples for each spike waveform. This compression method retains sufficiently high data quality to allow for single neuron identification (spike sorting). The 400 MHz transmitter employs a Manchester-Coded Frequency Shift Keying (MC-FSK) modulator with low modulation index. In this way, a 1.25 Mbit/s data rate is delivered within a limited band of about 3 MHz. The chip is realized in a 0.35 µm AMS CMOS process featuring a 3 V power supply with an area of 3.1 × 2.7 mm 2. The achieved transmission range is over 10 m with an overall power consumption for 64 channels of 17.2 mW. This figure translates into a power budget of 269 µW per channel, in line with published results but allowing a larger transmission distance and more efficient bandwidth occupation of the wireless link. The integrated circuit was mounted on a small and light board to be used J. Low Power Electron. Appl. 2012, 2 212 during neuroscience experiments with freely-behaving rats. Powered by 2 AAA batteries, the system can continuously work for more than 100 hours allowing for long-lasting neural spike recordings.
Minimally-Invasive Neural Interface for Distributed Wireless Electrocorticogram Recording Systems
Sensors, 2018
This paper presents a minimally-invasive neural interface for distributed wireless electrocorticogram (ECoG) recording systems. The proposed interface equips all necessary components for ECoG recording, such as the high performance front-end integrated circuits, a fabricated flexible microelectrode array, and wireless communication inside a miniaturized custom-made platform. The multiple units of the interface systems can be deployed to cover a broad range of the target brain region and transmit signals via a built-in intra-skin communication (ISCOM) module. The core integrated circuit (IC) consists of 16-channel, low-power push-pull double-gated preamplifiers, in-channel successive approximation register analog-to-digital converters (SAR ADC) with a single-clocked bootstrapping switch and a time-delayed control unit, an ISCOM module for wireless data transfer through the skin instead of a power-hungry RF wireless transmitter, and a monolithic voltage/current reference generator to support the aforementioned analog and mixed-signal circuit blocks. The IC was fabricated using 250 nm CMOS processes in an area of 3.2 × 0.9 mm 2 and achieved the low-power operation of 2.5 µW per channel. Input-referred noise was measured as 5.62 µV rms for 10 Hz to 10 kHz and ENOB of 7.21 at 31.25 kS/s. The implemented system successfully recorded multi-channel neural activities in vivo from a primate and demonstrated modular expandability using the ISCOM with power consumption of 160 µW.
Wireless, In Vivo Neural Recording using a Custom Integrated Bioamplifier and the Pico System
2007 3rd International IEEE/EMBS Conference on Neural Engineering, 2007
This paper describes a wireless system for sampling multiple channels of neural activity based on a low-power, custom 80dB-gain integrated bioamplifier, Texas Instrument's MSP430 microprocessors, and Nordic Semiconductor's ultra low power, high bandwidth RF transmitter/receivers. The system's features are presented as well as results of spike potentials from a live subject.
A Low-Power Integrated Circuit for a Wireless 100-Electrode Neural Recording System
IEEE Journal of Solid-State Circuits, 2000
In the past decade, neuroscientists and clinicians have begun to use implantable MEMS multielectrode arrays (e.g., ) to observe the simultaneous activity of many neurons in the brain. By observing the action potentials, or "spikes," of many neurons in a localized region of the brain it is possible to gather enough information to predict hand trajectories in real time during reaching tasks . Recent experiments have shown that it is possible to develop neuroprosthetic devices -machines controlled directly by thoughts -if the activity of multiple neurons can be observed.