Circuits And Methods For Artifact Elimination

Disclosed are apparatus and methods that provide the ability to electrical stimulate a physical system, and actively eliminate interference with signal acquisition (artifacts) that arises from the stimulation. The technique implemented in the circuits and methods for eliminating interference connects a discharge path to a physical interface to the system to remove charge that is built-up during stimulation. By placing the discharge path in a feedback loop that includes a recording preamplifier and AC-coupling circuitry, the physical interface is brought back to its pre-stimulation offset voltage. The disclosed apparatus and methods may be used with piezoelectric transducers, ultrasound devices, optical diodes, and polarizable and non-polarizable electrodes. The disclosed apparatus can be employed in implantable devices, in vitro or in vivo setups with vertebrate and invertebrate neural tissue, muscle fibers, pancreatic islet cells, osteoblasts, osteoclasts, bacteria, algae, fungi, protists, and plants.Georgia Tech Research Corporatio

Wired, wireless and wearable bioinstrumentation for high-precision recording of bioelectrical signals in bidirectional neural interfaces

It is widely accepted by the scientific community that bioelectrical signals, which can be used for the identification of neurophysiological biomarkers indicative of a diseased or pathological state, could direct patient treatment towards more effective therapeutic strategies. However, the design and realisation of an instrument that can precisely record weak bioelectrical signals in the presence of strong interference stemming from a noisy clinical environment is one of the most difficult challenges associated with the strategy of monitoring bioelectrical signals for diagnostic purposes. Moreover, since patients often have to cope with the problem of limited mobility being connected to bulky and mains-powered instruments, there is a growing demand for small-sized, high-performance and ambulatory biopotential acquisition systems in the Intensive Care Unit (ICU) and in High-dependency wards. Furthermore, electrical stimulation of specific target brain regions has been shown to alleviate symptoms of neurological disorders, such as Parkinson’s disease, essential tremor, dystonia, epilepsy etc. In recent years, the traditional practice of continuously stimulating the brain using static stimulation parameters has shifted to the use of disease biomarkers to determine the intensity and timing of stimulation. The main motivation behind closed-loop stimulation is minimization of treatment side effects by providing only the necessary stimulation required within a certain period of time, as determined from a guiding biomarker. Hence, it is clear that high-quality recording of local field potentials (LFPs) or electrocorticographic (ECoG) signals during deep brain stimulation (DBS) is necessary to investigate the instantaneous brain response to stimulation, minimize time delays for closed-loop neurostimulation and maximise the available neural data. To our knowledge, there are no commercial, small, battery-powered, wearable and wireless recording-only instruments that claim the capability of recording ECoG signals, which are of particular importance in closed-loop DBS and epilepsy DBS. In addition, existing recording systems lack the ability to provide artefact-free high-frequency (> 100 Hz) LFP recordings during DBS in real time primarily because of the contamination of the neural signals of interest by the stimulation artefacts. To address the problem of limited mobility often encountered by patients in the clinic and to provide a wide variety of high-precision sensor data to a closed-loop neurostimulation platform, a low-noise (8 nV/√Hz), eight-channel, battery-powered, wearable and wireless multi-instrument (55 × 80 mm2) was designed and developed. The performance of the realised instrument was assessed by conducting both ex vivo and in vivo experiments. The combination of desirable features and capabilities of this instrument, namely its small size (~one business card), its enhanced recording capabilities, its increased processing capabilities, its manufacturability (since it was designed using discrete off-the-shelf components), the wide bandwidth it offers (0.5 – 500 Hz) and the plurality of bioelectrical signals it can precisely record, render it a versatile tool to be utilized in a wide range of applications and environments. Moreover, in order to offer the capability of sensing and stimulating via the same electrode, novel real-time artefact suppression methods that could be used in bidirectional (recording and stimulation) system architectures are proposed and validated. More specifically, a novel, low-noise and versatile analog front-end (AFE), which uses a high-order (8th) analog Chebyshev notch filter to suppress the artefacts originating from the stimulation frequency, is presented. After defining the system requirements for concurrent LFP recording and DBS artefact suppression, the performance of the realised AFE is assessed by conducting both in vitro and in vivo experiments using unipolar and bipolar DBS (monophasic pulses, amplitude ranging from 3 to 6 V peak-to-peak, frequency 140 Hz and pulse width 100 µs). Under both in vitro and in vivo experimental conditions, the proposed AFE provided real-time, low-noise and artefact-free LFP recordings (in the frequency range 0.5 – 250 Hz) during stimulation. Finally, a family of tunable hardware filter designs and a novel method for real-time artefact suppression that enables wide-bandwidth biosignal recordings during stimulation are also presented. This work paves the way for the development of miniaturized research tools for closed-loop neuromodulation that use a wide variety of bioelectrical signals as control signals.Open Acces

A High TCMRR, Inherently Charge Balanced Bidirectional Front-End for Multichannel Closed-Loop Neuromodulation

This paper describes a multichannel bidirectional front-end for implantable closed-loop neuromodulation. Stimulation artefacts are reduced by way of a 4-channel H-bridge current source sharing stimulator front-end that minimizes residual charge drops in the electrodes via topology-inherent charge balancing. A 4-channel chopper front-end is capable of multichannel recording in the presence of artefacts as a result of its high total common-mode rejection ratio (TCMRR) that accounts for CMRR degradation due to electrode mismatch. Experimental verification of a prototype fabricated in a standard 180 nm process shows a stimulator front-end with 0.059% charge balance and 0.275 nA DC current error. The recording front-end consumes 3.24 µW, tolerates common-mode interference up to 1 Vpp and shows a TCMRR > 66 dB for 500 mVpp inputs.Ministerio de Economía y Competitividad TEC2016-80923-POffice of Naval Research (USA) N00014111031

A power efficient neural spike recording channel with data bandwidth reduction

This paper presents a mixed-signal neural spike recording channel which features, as an added value, a simple and low-power data compression mechanism. The channel uses a band-limited differential low noise amplifier and a binary search data converter, together with other digital and analog blocks for control, programming and spike characterization. The channel offers a self-calibration operation mode and it can be configured both for signal tracking (to raw digitize the acquired neural waveform) and feature extraction (to build a first-order PWL approximation of the spikes). The prototype has been fabricated in a standard CMOS 0.13μm and occupies 400μm×400μm. The overall power consumption of the channel during signal tracking is 2.8μW and increases to 3.0μW average when the feature extraction operation mode is programmed.Ministerio de Ciencia e Innovación TEC2009-08447Junta de Andalucía TIC-0281

A Low-Power Wireless Multichannel Microsystem for Reliable Neural Recording.

This thesis reports on the development of a reliable, single-chip, multichannel wireless biotelemetry microsystem intended for extracellular neural recording from awake, mobile, and small animal models. The inherently conflicting requirements of low power and reliability are addressed in the proposed microsystem at architectural and circuit levels. Through employing the preliminary microsystems in various in-vivo experiments, the system requirements for reliable neural recording are identified and addressed at architectural level through the analytical tool: signal path co-optimization. The 2.85mm×3.84mm, mixed-signal ASIC integrates a low-noise front-end, programmable digital controller, an RF modulator, and an RF power amplifier (PA) at the ISM band of 433MHz on a single-chip; and is fabricated using a 0.5µm double-poly triple-metal n-well standard CMOS process. The proposed microsystem, incorporating the ASIC, is a 9-channel (8-neural, 1-audio) user programmable reliable wireless neural telemetry microsystem with a weight of 2.2g (including two 1.5V batteries) and size of 2.2×1.1×0.5cm3. The electrical characteristics of this microsystem are extensively characterized via benchtop tests. The transmitter consumes 5mW and has a measured total input referred voltage noise of 4.74µVrms, 6.47µVrms, and 8.27µVrms at transmission distances of 3m, 10m, and 20m, respectively. The measured inter-channel crosstalk is less than 3.5% and battery life is about an hour. To compare the wireless neural telemetry systems, a figure of merit (FoM) is defined as the reciprocal of the power spent on broadcasting one channel over one meter distance. The proposed microsystem’s FoM is an order of magnitude larger compared to all other research and commercial systems. The proposed biotelemetry system has been successfully used in two in-vivo neural recording experiments: i) from a freely roaming South-American cockroach, and ii) from an awake and mobile rat.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91542/1/aborna_1.pd

A novel fully differential biopotential amplifier with DC suppression

Fully differential amplifiers yield large differential gains and also high common mode rejection ratio (CMRR), provided they do not include any unmatched grounded component. In biopotential measurements, however, the admissible gain of amplification stages located before dc suppression is usually limited by electrode offset voltage, which can saturate amplifier outputs. The standard solution is to first convert the differential input voltage to a single-ended voltage and then implement any other required functions, such as dc suppression and dc level restoring. This approach, however, yields a limited CMRR and may result in a relatively large equivalent input noise. This paper describes a novel fully differential biopotential amplifier based on a fully differential dc-suppression circuit that does not rely on any matched passive components, yet provides large CMRR and fast recovery from dc level transients. The proposed solution is particularly convenient for low supply voltage systems. An example implementation, based on standard low-power op amps and a single 5-V power supply, accepts input offset voltages up to /spl plusmn/500 mV, yields a CMRR of 102dB at 50 Hz, and provides, in accordance with the AAMI EC38 standard, a reset behavior for recovering from overloads or artifactsPeer Reviewe

Low Power Circuits for Smart Flexible ECG Sensors

Cardiovascular diseases (CVDs) are the world leading cause of death. In-home heart condition monitoring effectively reduced the CVD patient hospitalization rate. Flexible electrocardiogram (ECG) sensor provides an affordable, convenient and comfortable in-home monitoring solution. The three critical building blocks of the ECG sensor i.e., analog frontend (AFE), QRS detector, and cardiac arrhythmia classifier (CAC), are studied in this research. A fully differential difference amplifier (FDDA) based AFE that employs DC-coupled input stage increases the input impedance and improves CMRR. A parasitic capacitor reuse technique is proposed to improve the noise/area efficiency and CMRR. An on-body DC bias scheme is introduced to deal with the input DC offset. Implemented in 0.35m CMOS process with an area of 0.405mm2, the proposed AFE consumes 0.9W at 1.8V and shows excellent noise effective factor of 2.55, and CMRR of 76dB. Experiment shows the proposed AFE not only picks up clean ECG signal with electrodes placed as close as 2cm under both resting and walking conditions, but also obtains the distinct -wave after eye blink from EEG recording. A personalized QRS detection algorithm is proposed to achieve an average positive prediction rate of 99.39% and sensitivity rate of 99.21%. The user-specific template avoids the complicate models and parameters used in existing algorithms while covers most situations for practical applications. The detection is based on the comparison of the correlation coefficient of the user-specific template with the ECG segment under detection. The proposed one-target clustering reduced the required loops. A continuous-in-time discrete-in-amplitude (CTDA) artificial neural network (ANN) based CAC is proposed for the smart ECG sensor. The proposed CAC achieves over 98% classification accuracy for 4 types of beats defined by AAMI (Association for the Advancement of Medical Instrumentation). The CTDA scheme significantly reduces the input sample numbers and simplifies the sample representation to one bit. Thus, the number of arithmetic operations and the ANN structure are greatly simplified. The proposed CAC is verified by FPGA and implemented in 0.18m CMOS process. Simulation results show it can operate at clock frequencies from 10KHz to 50MHz. Average power for the patient with 75bpm heart rate is 13.34W

A 32-Channel Time-Multiplexed Artifact-Aware Neural Recording System

This paper presents a low-power, low-noise microsystem for the recording of neural local field potentials or intracranial electroencephalographic signals. It features 32 time-multiplexed channels at the electrode interface and offers the possibility to spatially delta encode data to take advantage of the large correlation of signals captured from nearby channels. The circuit also implements a mixed-signal voltage-triggered auto-ranging algorithm which allows to attenuate large interferers in digital domain while preserving neural information. This effectively increases the system dynamic range and avoids the onset of saturation. A prototype, fabricated in a standard 180 nm CMOS process, has been experimentally verified in-vitro with cellular cultures of primary cortical neurons from mice. The system shows an integrated input-referred noise in the 0.5–200 Hz band of 1.4 µVrms for a spot noise of about 85 nV / √Hz. The system draws 1.5 µW per channel from 1.2 V supply and obtains 71 dB + 26 dB dynamic range when the artifact-aware auto-ranging mechanism is enabled, without penalising other critical specifications such as crosstalk between channels or common-mode and power supply rejection ratios

Low-Noise Micro-Power Amplifiers for Biosignal Acquisition

There are many different types of biopotential signals, such as action potentials (APs), local field potentials (LFPs), electromyography (EMG), electrocardiogram (ECG), electroencephalogram (EEG), etc. Nerve action potentials play an important role for the analysis of human cognition, such as perception, memory, language, emotions, and motor control. EMGs provide vital information about the patients which allow clinicians to diagnose and treat many neuromuscular diseases, which could result in muscle paralysis, motor problems, etc. EEGs is critical in diagnosing epilepsy, sleep disorders, as well as brain tumors. Biopotential signals are very weak, which requires the biopotential amplifier to exhibit low input-referred noise. For example, EEGs have amplitudes from 1 μV [microvolt] to 100 μV [microvolt] with much of the energy in the sub-Hz [hertz] to 100 Hz [hertz] band. APs have amplitudes up to 500 μV [microvolt] with much of the energy in the 100 Hz [hertz] to 7 kHz [hertz] band. In wearable/implantable systems, the low-power operation of the biopotential amplifier is critical to avoid thermal damage to surrounding tissues, preserve long battery life, and enable wirelessly-delivered or harvested energy supply. For an ideal thermal-noise-limited amplifier, the amplifier power is inversely proportional to the input-referred noise of the amplifier. Therefore, there is a noise-power trade-off which must be well-balanced by the designers. In this work I propose novel amplifier topologies, which are able to significantly improve the noise-power efficiency by increasing the effective transconductance at a given current. In order to reject the DC offsets generated at the tissue-electrode interface, energy-efficient techniques are employed to create a low-frequency high-pass cutoff. The noise contribution of the high-pass cutoff circuitry is minimized by using power-efficient configurations, and optimizing the biasing and dimension of the devices. Sufficient common-mode rejection ratio (CMRR) and power supply rejection ratio (PSRR) are achieved to suppress common-mode interferences and power supply noises. Our design are fabricated in standard CMOS processes. The amplifiers’ performance are measured on the bench, and also demonstrated with biopotential recordings