Wireless Neural Recording System Research Articles

Neural signal compression using a minimum Euclidean or Manhattan distance cluster-based deterministic compressed sensing matrix

Multichannel wireless neural signal recording systems are a prominent topic in biomedical research, but because of several limitations, such as power consumption, the device size, and enormous quantities of data, it is necessary to compress the recorded data. Compressed sensing theory can be employed to compress neural signals. However, a neural signal is usually not sparse in the time domain and contains a large number of similar non-zero points. In this article, we propose a new method for compressing not only a sparse signal but also a non-sparse signal that has identical points. First, several concepts about the identical items of the signal are introduced; thus, a method for constructing the Minimum Euclidean or Manhattan Distance Cluster-based (MDC) deterministic compressed sensing matrix is given. Moreover, the Restricted Isometry Property of the MDC matrix is supported. Third, three groups of real neural signals are used for validation. Six different random or deterministic sensing matrices under diverse reconstruction algorithms are used for the simulation. From the simulation results, it can be demonstrated that the MDC matrix can largely compress neural signals and also have a small reconstruction error. For a six-thousand-point signal, the compression rate can be up to 98%, whereas the reconstruction error is less than 0.1. In addition, from the simulation results, the MDC matrix is optimal for a signal that has an extended length. Finally, the MDC matrix can be constructed by zeros and ones; additionally, it has a simple construction structure that is highly practicable for the design of an implantable neural recording device.

Flexible, Polarization-Diverse UWB Antennas for Implantable Neural Recording Systems.

Implanted antennas for implant-to-air data communications must be composed of material compatible with biological tissues. We design single and dual-polarization antennas for wireless ultra-wideband neural recording systems using an inhomogeneous multi-layer model of the human head. Antennas made from flexible materials are more easily adapted to implantation; we investigate both flexible and rigid materials and examine performance trade-offs. The proposed antennas are designed to operate in a frequency range of 2-11 GHz (having S11 below -10 dB) covering both the 2.45 GHz (ISM) band and the 3.1-10.6 GHz UWB band. Measurements confirm simulation results showing flexible antennas have little performance degradation due to bending effects (in terms of impedance matching). Our miniaturized flexible antennas are 12 mm×12 mm and 10 mm×9 mm for single- and dual-polarizations, respectively. Finally, a comparison is made of four implantable antennas covering the 2-11 GHz range: 1) rigid, single polarization, 2) rigid, dual polarization, 3) flexible, single polarization and 4) flexible, dual polarization. In all cases a rigid antenna is used outside the body, with an appropriate polarization. Several advantages were confirmed for dual polarization antennas: 1) smaller size, 2) lower sensitivity to angular misalignments, and 3) higher fidelity.

A wireless neural recording system with a precision motorized microdrive for freely behaving animals.

The brain is composed of many different types of neurons. Therefore, analysis of brain activity with single-cell resolution could provide fundamental insights into brain mechanisms. However, the electrical signal of an individual neuron is very small, and precise isolation of single neuronal activity from moving subjects is still challenging. To measure single-unit signals in actively behaving states, establishment of technologies that enable fine control of electrode positioning and strict spike sorting is essential. To further apply such a single-cell recording approach to small brain areas in naturally behaving animals in large spaces or during social interaction, we developed a compact wireless recording system with a motorized microdrive. Wireless control of electrode placement facilitates the exploration of single neuronal activity without affecting animal behaviors. Because the system is equipped with a newly developed data-encoding program, the recorded data are readily compressed almost to theoretical limits and securely transmitted to a host computer. Brain activity can thereby be stably monitored in real time and further analyzed using online or offline spike sorting. Our wireless recording approach using a precision motorized microdrive will become a powerful tool for studying brain mechanisms underlying natural or social behaviors.

An Adaptive Recovery Method in Compressed Sensing of Extracellular Neural Recording

A novel adaptive recovery method in the emerging compressed sensing theory is described and applied to extracellular neural recordings in order to reduce data rate in wireless neural recording systems. To strike a balance between high compression ratio and high spike reconstruction quality, a novel method that employs a group-sparsity recovery algorithm, prior information about the input neural signal, learning prior supports of spikes, and a matched wavelet technique is introduced. Our simulation results, using four different sets of real extracellular recordings from four distinct neural sources, show that our proposed method is effective, viable, and outperforms the state-of-the-art compressed sensing-based methods, in particular, when the number of the measurement is two times of the sparsity.

A Wireless Multichannel Neural Recording system for Implantable Brain-Machine Interfaces

Event Abstract Back to Event A Wireless Multichannel Neural Recording system for Implantable Brain-Machine Interfaces Hiroshi Ando1, Kenichi Takizawa1, Takeshi Yoshida1, Kojiro Matsushita1, Masayuki Hirata1 and Takafumi Suzuki1* 1 Osaka University, National Institute of Information and Communications Technology, Japan Simultaneous recording of neural activity at large scale, in the long-term, and with bio-safety can provide essential data. These data can be used to advance technology for brain–machine interfaces in clinical application, and to understand brain function. Therefore, we present a new multichannel neural recording system that can record up to 4096-channel (ch) electrocorticogram data by multiple connections of customized application-specific integrated circuits (ASICs). Recorded data sampled at a rate of 1kS/s are multiplexed with time division via an integrated multiplex board, and in total 51.2 Mbps raw data for 4096 ch are generated. This system has an ultra wideband (UWB) wireless unit for transmitting the recorded neural signals. From preliminary experiments with a human body-equivalent liquid phantom, we confirmed 4096-ch UWB wireless data transmission at 128 Mbps for distances below 20 mm. Keywords: Multichannel neural recording, Implantable Brain-Machine Interfaces, brain-machine interfaces, application-specific integrated circuits, ultra wideband Conference: 2015 International Workshop on Clinical Brain-Machine Interfaces (CBMI2015), Tokyo, Japan, 13 Mar - 15 Mar, 2015. Presentation Type: Poster 1-3 Topic: Clinical Brain-Machine Interfaces Citation: Ando H, Takizawa K, Yoshida T, Matsushita K, Hirata M and Suzuki T (2015). A Wireless Multichannel Neural Recording system for Implantable Brain-Machine Interfaces. Conference Abstract: 2015 International Workshop on Clinical Brain-Machine Interfaces (CBMI2015). doi: 10.3389/conf.fnhum.2015.218.00014 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Apr 2015; Published Online: 29 Apr 2015. * Correspondence: Dr. Takafumi Suzuki, Osaka University, National Institute of Information and Communications Technology, Suita City, Osaka, Japan, t.suzuki@nict.go.jp Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Hiroshi Ando Kenichi Takizawa Takeshi Yoshida Kojiro Matsushita Masayuki Hirata Takafumi Suzuki Google Hiroshi Ando Kenichi Takizawa Takeshi Yoshida Kojiro Matsushita Masayuki Hirata Takafumi Suzuki Google Scholar Hiroshi Ando Kenichi Takizawa Takeshi Yoshida Kojiro Matsushita Masayuki Hirata Takafumi Suzuki PubMed Hiroshi Ando Kenichi Takizawa Takeshi Yoshida Kojiro Matsushita Masayuki Hirata Takafumi Suzuki Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

A low-cost, open-source, wireless electrophysiology system.

Many experiments in neuroscience require or would benefit tremendously from a wireless neural recording system. However, commercially available wireless systems are expensive, have moderate to high noise and are often not customizable. Academic wireless systems present impressive capabilities, but are not available for other labs to use. To overcome these limitations, we have developed an ultra-low noise 8 channel wireless electrophysiological data acquisition system using standard, commercially available components. The system is capable of recording many types of neurological signals, including EEG, ECoG, LFP and unit activity. With a diameter of just 25 mm and height of 9 mm, including a CR2032 Lithium coin cell battery, it is designed to fit into a small recording chamber while minimizing the overall implant height (Fig. 1 and 3). Using widely available parts we were able to keep the material cost of our system under $100 dollars. The complete design, including schematic, PCB layout, bill of materials and source code, will be released through an open source license, allowing other labs to modify the design to fit their needs. We have also developed a driver to acquire data using the BCI2000 software system. Feedback from the community will allow us to improve the design and create a more useful neuroscience research tool.

A dual slope charge sampling analog front-end for a wireless neural recording system.

This paper presents a novel dual slope charge sampling (DSCS) analog front-end (AFE) architecture, which amplifies neural signals by taking advantage of the charge sampling concept for analog signal conditioning, such as amplification and filtering. The presented DSCS-AFE achieves amplification, filtering, and sampling in a simultaneous fashion, while consuming very small amount of power. The output of the DSCS-AFE produces a pulse width modulated (PWM) signal that is proportional to the input voltage amplitude. A circular shift register (CSR) utilizes time division multiplexing (TDM) of the PWM pulses to create a pseudo-digital TDM-PWM signal that can feed a wireless transmitter. The 8-channel system-on-a-chip was fabricated in a 0.35-μm CMOS process, occupying 2.4 × 2.1 mm(2) and consuming 255 μW from a 1.8V supply. Measured input-referred noise for the entire system, including the FPGA in order to recover PWM signal is 6.50 μV(rms) in the 288 Hz~10 kHz range. For each channel, sampling rate is 31.25 kHz, and power consumption is 31.8 μW.

A 100-Channel Hermetically Sealed Implantable Device for Chronic Wireless Neurosensing Applications

A 100-channel fully implantable wireless broadband neural recording system was developed. It features 100 parallel broadband (0.1 Hz-7.8 kHz) neural recording channels, a medical grade 200 mAh Li-ion battery recharged inductively at 150 kHz , and data telemetry using 3.2 GHz to 3.8 GHz FSK modulated wireless link for 48 Mbps Manchester encoded data. All active electronics are hermetically sealed in a titanium enclosure with a sapphire window for electromagnetic transparency. A custom, high-density configuration of 100 individual hermetic feedthrough pins enable connection to an intracortical neural recording microelectrode array. A 100 MHz bandwidth custom receiver was built to remotely receive the FSK signal and achieved -77.7 dBm sensitivity with 10(-8) BER at 48 Mbps data rate. ESD testing on all the electronic inputs and outputs has proven that the implantable device satisfies the HBM Class-1B ESD Standard. In addition, the evaluation of the worst-case charge density delivered to the tissue from each I/O pin verifies the patient safety of the device in the event of failure. Finally, the functionality and reliability of the complete device has been tested on-bench and further validated chronically in ongoing freely moving swine and monkey animal trials for more than one year to date.

CMOS implementation of a low-power BPSK demodulator for wireless implantable neural command transmission

A new BPSK demodulator was presented. By using a clock multiplier with very simple circuit structure to replace the analog multiplier in the traditional BPSK demodulator, the circuit structure of the demodulator became simpler and hence its power consumption became lower. Simpler structure and lower power will make the designed demodulator more suitable for use in an internal single chip design for a wireless implantable neural recording system. The proposed BPSK demodulator was implemented by Global Foundries 0.35 μm CMOS technology with a 3.3 V power supply. The designed chip area is only 0.07 mm2 and the power consumption is 0.5 mW. The test results show that it can work correctly.

Integrated Wireless Neural Recording and Electrode Positioning System

Abstract In neurophysiological research, the recording of brain activity in animals is fundamental. Conventional wire-based technologies allow such recordings only in movement-restraint animals. Head-mounted wireless recording technologies allow investigating a broader spectrum of behaviors and have the potential to improve animal welfare and mark an important step towards implantable neuroprosthetic devices. We developed a lightweight, head-mountable neural recording system, which allows bidirectional communication for remote signal acquisition on the one hand and remote pre-amp gain adjustments and microelectrode position adjustments, on the other hand.

Brains gone wild

Analyzing brain signals from freely moving rodents in the wild is possible using a wireless neural recording system.

A low-noise clockless simultaneous 32-channel wireless neural recording system with adjustable resolution

We present a 32-channel wireless implantable neural recording (WINeR-5) system-on-a-chip (SoC) that operates based on time division multiplexing (TDM) of pulse width modulated (PWM) samples, similar to a single-slope analog to digital converter (ADC) that is made wireless. By transmitting a TDM---PWM signal, we have relaxed the need for wide bandwidth and accurate timing between transmitter and receiver units, which is necessary in wideband digital wireless links. The WINeR-5 system uses FSK modulation scheme with RF carrier at 898/926 MHz. The baseband TDM---PWM signal bandwidth is 18 MHz, which is also the bandwidth of the receiver baseband low-pass filter. Further, by moving the digitization circuitry outside the body, we have reduced the size, complexity, and power consumption of the implantable unit. A clockless asynchronous design has been utilized to manage TDM switching times such that no switching occurs during sensitive PWM onsets. Control over sampling rate, dynamic range, and resolution provides the user with tradeoffs that can optimize the system performance for the intended application. The SoC has been implemented in a 0.5-μm standard CMOS process, measuring 3.3 × 3 mm2 and consuming 5.6 mW at ±1.5 V when all channels are active. Measured input referred noise for the entire system, including the receiver at 1 m distance, is 4.9 μVrms in 1 Hz---8.8 kHz range. Functionality of the WINeR-5 system has also been demonstrated in acute in vivo experiments.

Wireless Transmission of Neural Signals Using Entropy and Mutual Information Compression

Two of the most critical tasks when designing a portable wireless neural recording system are to limit power consumption and to efficiently use the limited bandwidth. It is known that for most wireless devices the majority of power is consumed by the wireless transmitter and it often represents the bottleneck of the overall design. This paper compares two compression techniques that take advantage of the sparseness of the neural spikes in neural recordings using an information theoretic formalism to enhance the well-established vector quantization (VQ) algorithm. The two discriminative VQ algorithms are applied to neuronal recordings proving their ability to accurately reconstruct action potential (AP) regions of the neuronal signal while compressing background activity without using thresholds. The two operational modes presented offer distinct characteristics to lossy compression. The first approach requires no preprocessing or prior knowledge of the signal while the second requires a training set of spikes to obtain AP templates. The compression algorithms are implemented on an on-board digital signal processor (DSP) and results show that power consumption is decreased while the bandwidth is more efficiently utilized. The compression algorithms have been tested in real time on a hardware platform (PICO DSP ) enhanced with the DSP which runs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range from 70:1 and 40:1 depending on the signal to noise ratio (SNR) of the input signal. The spike sorting accuracy in the reconstructed data is 95% compatible to the original neural data.

Embedded Neural Recording With TinyOS-Based Wireless-Enabled Processor Modules

To create a wireless neural recording system that can benefit from the continuous advancements being made in embedded microcontroller and communications technologies, an embedded-system-based architecture for wireless neural recording has been designed, fabricated, and tested. The system consists of commercial-off-the-shelf wireless-enabled processor modules (motes) for communicating the neural signals, and a back-end database server and client application for archiving and browsing the neural signals. A neural-signal-acquisition application has been developed to enable the mote to either acquire neural signals at a rate of 4000 12-bit samples per second, or detect and transmit spike heights and widths sampled at a rate of 16670 12-bit samples per second on a single channel. The motes acquire neural signals via a custom low-noise neural-signal amplifier with adjustable gain and high-pass corner frequency that has been designed, and fabricated in a 1.5-microm CMOS process. In addition to browsing acquired neural data, the client application enables the user to remotely toggle modes of operation (real-time or spike-only), as well as amplifier gain and high-pass corner frequency.

A combined wireless neural stimulating and recording system for study of pain processing

Clinical studies have shown that spinal or cortical neurostimulation could significantly improve pain relief. The currently available stimulators, however, are used only to generate specific electrical signals without the knowledge of physiologically responses caused from the stimulation. We thus propose a new system that can adaptively generate the optimized stimulating signals base on the correlated neuron activities. This new method could significantly improve the efficiency of neurostimulation for pain relief. We have developed an integrated wireless recording and stimulating system to transmit the neuronal signals and to activate the stimulator over the wireless link. A wearable prototype has been developed consisting of amplifiers, wireless modules and a microcontroller remotely controlled by a Labview program in a computer to generate desired stimulating pulses. The components were assembled on a board with a size of 2.5 cm × 5 cm to be carried by a rat. To validate our system, lumbar spinal cord dorsal horn neuron activities of anesthetized rats have been recorded in responses to various types of peripheral graded mechanical stimuli. The stimulation at the periaqueductal gray and anterior cingulate cortex with different combinations of electrical parameters showed a comparable inhibition of spinal cord dorsal horns activities in response to the mechanical stimuli. The Labview program was also used to monitor the neuronal activities and automatically activate the stimulator with designated pulses. Our wireless system has provided an opportunity for further study of pain processing with closed-loop stimulation paradigm in a potential new pain relief method.

A Low-Power Integrated Circuit for a Wireless 100-Electrode Neural Recording System

Recent work in field of neuroprosthetics has demonstrated that by observing the simultaneous activity of many neurons in specific regions of the brain, it is possible to produce control signals that allow animals or humans to drive cursors or prosthetic limbs directly through thoughts. As neuroprosthetic devices transition from experimental to clinical use, there is a need for fully-implantable amplification and telemetry electronics in close proximity to the recording sites. To address these needs, we developed a prototype integrated circuit for wireless neural recording from a 100-channel microelectrode array. The design of both the system-level architecture and the individual circuits were driven by severe power constraints for small implantable devices; chronically heating tissue by only a few degrees Celsius leads to cell death. Due to the high data rate produced by 100 neural signals, the system must perform data reduction as well. We use a combination of a low-power ADC and an array of "spike detectors" to reduce the transmitted data rate while preserving critical information. The complete system receives power and commands (at 6.5 kb/s) wirelessly over a 2.64-MHz inductive link and transmits neural data back at a data rate of 330 kb/s using a fully-integrated 433-MHz FSK transmitter. The 4.7times5.9 mm2 chip was fabricated in a 0.5-mum 3M2P CMOS process and consumes 13.5 mW of power. While cross-chip interference limits performance in single-chip operation, a two-chip system was used to record neural signals from a Utah Electrode Array in cat cortex and transmit the digitized signals wirelessly to a receiver

A TinyOS-Enabled MICA2-Based Wireless Neural Interface

Existing approaches used to develop compact low-power multichannel wireless neural recording systems range from creating custom-integrated circuits to assembling commercial-off-the-shelf (COTS) PC-based components. Custom-integrated-circuit designs yield extremely compact and low-power devices at the expense of high development and upgrade costs and turn-around times, while assembling COTS-PC-technology yields high performance at the expense of large system size and increased power consumption. To achieve a balance between implementing an ultra-compact custom-fabricated neural transceiver and assembling COTS-PC-technology, an overlay of a neural interface upon the TinyOS-based MICA2 platform is described. The system amplifies, digitally encodes, and transmits neural signals real-time at a rate of 9.6 kbps, while consuming less than 66 mW of power. The neural signals are received and forwarded to a client PC over a serial connection. This data rate can be divided for recording on up to 6 channels, with a resolution of 8 bits/sample. This work demonstrates the strengths and limitations of the TinyOS-based sensor technology as a foundation for chronic remote biological monitoring applications and, thus, provides an opportunity to create a system that can leverage from the frequent networking and communications advancements being made by the global TinyOS-development community.

A wireless implantable multichannel digital neural recording system for a micromachined sieve electrode

This paper reports the development of an implantable, fully integrated, multichannel peripheral neural recording system, which is powered and controlled using an RF telemetry link. The system allows recording of /spl plusmn/500 /spl mu/V neural signals from axons regenerated through a micromachined silicon sieve electrode. These signals are amplified using on-chip 100 Hz to 3.1 kHz bandlimited amplifiers, multiplexed, and digitized with a low-power (<2 mW), moderate speed (8 /spl mu/s/b) current-mode 8-b analog-to-digital converter (ADC). The digitized signal is transmitted to the outside world using a passive RF telemetry link. The circuit is implemented using a bipolar CMOS process. The signal processing CMOS circuitry dissipates only 10 mW of power from a 5-V supply while operating at 2 MHz and consumes 4/spl times/4 mm/sup 2/ of area. The overall circuit including the RF interface circuitry contains over 5000 transistors, dissipates 90 mW of power, and consumes 4/spl times/6 mm/sup 2/ of area.