Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> This active probe can be used for the long-term recording of extracellular neural biopotentials and as a basis for closed-loop neural prostheses. The probe incorporates on-chip circuitry for amplifying, multiplexing, and buffering neural signals recorded from ten recording electrodes spaced 100-/spl mu/m apart. It requires only three leads and operates from a single 5-V supply. On-chip self-test circuitry for testing electrode impedance levels is provided. The on-chip circuitry is fabricated in a die area of 1.3 mm/SUP 2/ using 6-/spl mu/m LOCOS enhancement-depletion NMOS technology, and dissipates 5 mW of power. The probe is 4.7 mm long and 15 /spl mu/m thick, and has a shank which tapers from 160 /spl mu/m near the base to less than 15 /spl mu/m near the tip. <s> BIB001 </s> Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> This paper discusses certain important issues involved in the design of a nerve signal preamplifier for implantable neuroprostheses. Since the electroneurogram signal measured from cuff electrodes is typically on the order of 1 /spl mu/V, a very low-noise interface is essential. We present the argument for the use of BiCMOS technology in this application and then describe the design and evaluation of a complete preamplifier fabricated in a 0.8-/spl mu/m double-metal double-poly process. The preamplifier has a nominal voltage gain of 100, a bandwidth of 15 kHz, and a measured equivalent input-referred noise voltage spectral density of 3.3 nV//spl radic/Hz at 1 kHz. The total input-referred rms noise voltage in a bandwidth 1 Hz-10 kHz is 290 nV, the power consumption is 1.3 mW from /spl plusmn/2.5-V power supplies, and the active area is 0.3 mm/sup 2/. <s> BIB002 </s> Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> Neural prosthetic systems have the potential to restore lost functionality to amputees or patients suffering from neurological injury or disease. Current systems have primarily been designed for immobile patients, such as tetraplegics functioning in a rather static, carefully tailored environment. However, an active patient such as amputee in a normal dynamic, everyday environment may be quite different in terms of the neural control of movement. In order to study motor control in a more unconstrained natural setting, we seek to develop an animal model of freely moving humans. Therefore, we have developed and tested HermesC-INI3, a system for recording and wirelessly transmitting neural data from electrode arrays implanted in rhesus macaques who are freely moving. This system is based on the integrated neural interface (INI3) microchip which amplifies, digitizes, and transmits neural data across a ~ 900 MHz wireless channel. The wireless transmission has a range of ~ 4 m in free space. All together this device consumes 15.8 mA and 63.2 mW. On a single 2 A-hr battery pack, this device runs contiguously for approximately six days. The smaller size and power consumption of the custom IC allows for a smaller package (51 times 38 times 38 mm3) than previous primate systems. The HermesC-INI3 system was used to record and telemeter one channel of broadband neural data at 15.7 kSps from a monkey performing routine daily activities in the home cage. <s> BIB003 </s> Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> HermesD is a high-rate, low-power wireless transmission system to aid research in neural prosthetic systems for motor disabilities and basic motor neuroscience. It is the third generation of our "Hermes systems" aimed at recording and transmitting neural activity from brain-implanted electrode arrays. This system supports the simultaneous transmission of 32 channels of broadband data sampled at 30 ks/s, 12 b/sample, using frequency-shift keying modulation on a carrier frequency adjustable from 3.7 to 4.1 GHz, with a link range extending over 20 m. The channel rate is 24 Mb/s and the bit stream includes synchronization and error detection mechanisms. The power consumption, approximately 142 mW, is low enough to allow the system to operate continuously for 33 h, using two 3.6-V/1200-mAh Li-SOCl2 batteries. The transmitter was designed using off-the-shelf components and is assembled in a stack of three 28 mm ? 28-mm boards that fit in a 38 mm ? 38 mm ? 51-mm aluminum enclosure, a significant size reduction over the initial version of HermesD. A 7-dBi circularly polarized patch antenna is used as the transmitter antenna, while on the receiver side, a 13-dBi circular horn antenna is employed. The advantages of using circularly polarized waves are analyzed and confirmed by indoor measurements. The receiver is a stand-alone device composed of several submodules and is interfaced to a computer for data acquisition and processing. It is based on the superheterodyne architecture and includes automatic frequency control that keeps it optimally tuned to the transmitter frequency. The HermesD communications performance is shown through bit-error rate measurements and eye-diagram plots. The sensitivity of the receiver is -83 dBm for a bit-error probability of 10-9. Experimental recordings from a rhesus monkey conducting multiple tasks show a signal quality comparable to commercial acquisition systems, both in the low-frequency (local field potentials) and upper-frequency bands (action potentials) of the neural signals. This system can be easily scaled up in terms of the number of channels and data rate to accommodate future generations of Hermes systems. <s> BIB004 </s> Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> This paper presents a portable, embedded, microcontroller-based system for bidirectional communication (recording and stimulation) between an electrode, implanted in the peripheral nervous system, and a host computer. The device is able to record and digitize spontaneous and/or evoked neural activities and store them in data files on a PC. In addition, the system has the capability of providing electrical stimulation of peripheral nerves, injecting biphasic current pulses with programmable duration, intensity, and frequency. The recording system provides a highly selective band-pass filter from 800 Hz to 3 kHz, with a gain of 56 dB. The amplification range can be further extended to 96 dB with a variable gain amplifier. The proposed acquisition/stimulation circuitry has been successfully tested through in vivo measurements, implanting a tf-LIFE electrode in the sciatic nerve of a rat. Once implanted, the device showed an input referred noise of 0.83 μVrms, was capable of recording signals below 10 μ V, and generated muscle responses to injected stimuli. The results demonstrate the capability of processing and transmitting neural signals with very low distortion and with a power consumption lower than 1 W. A graphic, user-friendly interface has been developed to facilitate the configuration of the entire system, providing the possibility to activate stimulation and monitor recordings in real time. <s> BIB005 </s> Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> OBJECT ::: A brain-machine interface (BMI) offers patients with severe motor disabilities greater independence by controlling external devices such as prosthetic arms. Among the available signal sources for the BMI, electrocorticography (ECoG) provides a clinically feasible signal with long-term stability and low clinical risk. Although ECoG signals have been used to infer arm movements, no study has examined its use to control a prosthetic arm in real time. The authors present an integrated BMI system for the control of a prosthetic hand using ECoG signals in a patient who had suffered a stroke. This system used the power modulations of the ECoG signal that are characteristic during movements of the patient's hand and enabled control of the prosthetic hand with movements that mimicked the patient's hand movements. ::: ::: ::: METHODS ::: A poststroke patient with subdural electrodes placed over his sensorimotor cortex performed 3 types of simple hand movements following a sound cue (calibration period). Time-frequency analysis was performed with the ECoG signals to select 3 frequency bands (1-8, 25-40, and 80-150 Hz) that revealed characteristic power modulation during the movements. Using these selected features, 2 classifiers (decoders) were trained to predict the movement state--that is, whether the patient was moving his hand or not--and the movement type based on a linear support vector machine. The decoding accuracy was compared among the 3 frequency bands to identify the most informative features. With the trained decoders, novel ECoG signals were decoded online while the patient performed the same task without cues (free-run period). According to the results of the real-time decoding, the prosthetic hand mimicked the patient's hand movements. ::: ::: ::: RESULTS ::: Offline cross-validation analysis of the ECoG data measured during the calibration period revealed that the state and movement type of the patient's hand were predicted with an accuracy of 79.6% (chance 50%) and 68.3% (chance 33.3%), respectively. Using the trained decoders, the onset of the hand movement was detected within 0.37 ± 0.29 seconds of the actual movement. At the detected onset timing, the type of movement was inferred with an accuracy of 69.2%. In the free-run period, the patient's hand movements were faithfully mimicked by the prosthetic hand in real time. ::: ::: ::: CONCLUSIONS ::: The present integrated BMI system successfully decoded the hand movements of a poststroke patient and controlled a prosthetic hand in real time. This success paves the way for the restoration of the patient's motor function using a prosthetic arm controlled by a BMI using ECoG signals. <s> BIB006 </s> Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> A functional electrical stimulation system in primates that is controlled by recordings made from microelectrodes permanently implanted in the brain can be used to control the intensity of stimulation of muscles that are temporarily paralysed by pharmacological motor nerve blockade, thereby restoring voluntary control of the affected muscles; this is a major advance towards similar restoration of hand function in human patients with spinal cord injury. <s> BIB007 </s> Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> A power and area efficient sensor interface consumes 6.4 mW from 1.2 V while occupying 5 mm × 5 mm in 0.13 μm CMOS. The interface offers simultaneous access to 96 channels of broadband neural data acquired from cortical microelectrodes as part of a head-mounted wireless recording system, enabling basic neuroscience as well as neuroprosthetics research. Signals are conditioned with a front-end achieving 2.2 μVrms input-referred noise in a 10 kHz bandwidth before conversion at 31.25 kSa/s by 10-bit SAR ADCs with 60.3 dB SNDR and 42 fJ/conv-step. Switched-capacitor filtering provides a well-controlled frequency response and utilizes windowed integrator sampling to mitigate noise aliasing, enhancing noise/power efficiency. <s> BIB008 </s> Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> Summary Background Paralysis or amputation of an arm results in the loss of the ability to orient the hand and grasp, manipulate, and carry objects, functions that are essential for activities of daily living. Brain–machine interfaces could provide a solution to restoring many of these lost functions. We therefore tested whether an individual with tetraplegia could rapidly achieve neurological control of a high-performance prosthetic limb using this type of an interface. Methods We implanted two 96-channel intracortical microelectrodes in the motor cortex of a 52-year-old individual with tetraplegia. Brain–machine-interface training was done for 13 weeks with the goal of controlling an anthropomorphic prosthetic limb with seven degrees of freedom (three-dimensional translation, three-dimensional orientation, one-dimensional grasping). The participant's ability to control the prosthetic limb was assessed with clinical measures of upper limb function. This study is registered with ClinicalTrials.gov, NCT01364480. Findings The participant was able to move the prosthetic limb freely in the three-dimensional workspace on the second day of training. After 13 weeks, robust seven-dimensional movements were performed routinely. Mean success rate on target-based reaching tasks was 91·6% (SD 4·4) versus median chance level 6·2% (95% CI 2·0–15·3). Improvements were seen in completion time (decreased from a mean of 148 s [SD 60] to 112 s [6]) and path efficiency (increased from 0·30 [0·04] to 0·38 [0·02]). The participant was also able to use the prosthetic limb to do skilful and coordinated reach and grasp movements that resulted in clinically significant gains in tests of upper limb function. No adverse events were reported. Interpretation With continued development of neuroprosthetic limbs, individuals with long-term paralysis could recover the natural and intuitive command signals for hand placement, orientation, and reaching, allowing them to perform activities of daily living. Funding Defense Advanced Research Projects Agency, National Institutes of Health, Department of Veterans Affairs, and UPMC Rehabilitation Institute. <s> BIB009 </s> Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> Objective. Neural interface technology suitable for clinical translation has the potential to significantly impact the lives of amputees, spinal cord injury victims and those living with severe neuromotor disease. Such systems must be chronically safe, durable and effective. Approach. We have designed and implemented a neural interface microsystem, housed in a compact, subcutaneous and hermetically sealed titanium enclosure. The implanted device interfaces the brain with a 510k-approved, 100-element silicon-based microelectrode array via a custom hermetic feedthrough design. Full spectrum neural signals were amplified (0.1?Hz to 7.8?kHz, 200? gain) and multiplexed by a custom application specific integrated circuit, digitized and then packaged for transmission. The neural data (24 Mbps) were transmitted by a wireless data link carried on a frequency-shift-key-modulated signal at 3.2 and 3.8?GHz to a receiver 1?m away by design as a point-to-point communication link for human clinical use. The system was powered by an embedded medical grade rechargeable Li-ion battery for 7?h continuous operation between recharge via an inductive transcutaneous wireless power link at 2?MHz. Main results. Device verification and early validation were performed in both swine and non-human primate freely-moving animal models and showed that the wireless implant was electrically stable, effective in capturing and delivering broadband neural data, and safe for over one year of testing. In addition, we have used the multichannel data from these mobile animal models to demonstrate the ability to decode neural population dynamics associated with motor activity. Significance. We have developed an implanted wireless broadband neural recording device evaluated in non-human primate and swine. The use of this new implantable neural interface technology can provide insight into how to advance human neuroprostheses beyond the present early clinical trials. Further, such tools enable mobile patient use, have the potential for wider diagnosis of neurological conditions and will advance brain research. <s> BIB010 </s> Implantable neurotechnologies: a review of integrated circuit neural amplifiers <s> Application of neural amplifiers for CNS Neuroprosthesis <s> 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. <s> BIB011
CNS-based neuroprostheses, or brain-machine interfaces (BMIs), are systems whereby neural electrical activities are decoded and used to control robotic limbs BIB005 BIB001 BIB002 or to stimulate muscles for restoring limb function BIB007 . Hochberg et al.  developed a BMI in which a tetraplegic patient used his thoughts to move a computer cursor to perform simple controls with a robotic hand. This technology has steadily matured. For example, Hochberg et al. and Collinger et al. BIB009  allowed tetraplegic patients to finely control a robotic hand based on cortical signals representing the patient's intended movement or thoughts. This paradigm can be combined with functional electrical stimulation. For example, Miller et al. BIB007 used a BMI interface to drive stimulation of hand muscles to restore compromised grasping ability in a macaque model. The above-reported BMI interfaces have all used neural recording amplifiers to acquire, amplify and digitize neural signals for decoding thought. Currently, all reported BMI experiments with human patients BIB009 BIB007   BIB006 require the subjects tethered percutaneously to a bench-top computer for neural signal acquisition and decoding. Although many of the miniature and lightweight wireless recording systems ICs BIB010 BIB003 BIB008 BIB004 120, 136, BIB011 discussed in the earlier sections of this review would simplify the BMI interface, major regulatory approvals (FCC, FDA, IEC) are needed before these devices can be safely applied to human use (especially for implantable applications).