Active digital electrode with embedded motion-artifact removal boosted common-mode-rejection, and enhanced dynamic range for ambultory electroencephalogram

Abstract

Provided are active electrodes (AE) and methods for obtaining a neurological signal of a subject. The active electrode configured to be disposed of on the head of the subject and communicatively connected to one or more of another electrode and a backend. The active electrode includes a conductive element mounted to an AE board and disposed in contact with a skin of the subject, a second stage amplifier for amplifying the obtained signal, and a calibration module for calibrating coefficients. In some embodiments, the AE further includes a CMR boosting module for boosting CMR rejection. In some embodiments the AE includes an artifact removal module for removing motion artifacts.

Description

ACTIVE DIGITAL ELECTRODE WITH EMBEDDED MOTION-ARTIFACT REMOVAL BOOSTED COMMON-MODE-REJECTION, AND ENHANCED DYNAMIC RANGE FOR AMBULTORY ELECTROENCEPHALOGRAMTechnical Field

[0001] The embodiments disclosed herein relate to active electrodes, and, in particular, to active electrodes for ambulatory electroencephalogram (EEG) monitoring and methods of manufacture of the same.Background

[0002] Electrodes are important to obtaining data for a wide range of applications including medical applications such as for EEGs and electrocardiograms (ECGs).

[0003] An EEG is a non-invasive method for measuring brain neural activity with high spatial and temporal resolution. Its applications include monitoring and diagnosing various neurological disorders, such as epilepsy and sleep disorders, as well as enabling responsive brain-computer interfaces for rehabilitation. Traditional hospital-based EEG systems require extended patient stays, leading to higher healthcare expenses due to hospitalization costs, medical staff requirements (for electrode placement and equipment setup), and specialists needed for data interpretation. For instance, in Canada, waiting times for an EEG-based epilepsy test can extend up to 12 months. Hospitalization also brings inconvenience and discomfort, impacting patients’ quality of life and social interactions. Furthermore, intermittent hospital-based EEG monitoring may result in missed opportunities to capture vital data, potentially leading to delayed or inaccurate diagnoses and increased health complications and expenses.

[0004] This has motivated the development of outpatient wireless wearable EEG solutions, aiming to alleviate these challenges. These devices enable patients to undergo EEG monitoring in the comfort of their homes or during daily activities, reducing the economic burden of hospitalization and healthcare resources. Continuous monitoring also ensures that critical data points are not overlooked, enhancing diagnostic accuracy, and leading to more effective treatment plans. Additionally, wireless EEG solutions can advance remote healthcare practices, increasing access to specialized neurological care in underserved areas and promoting health equity and social inclusion. As such, these wearable solutions may be portable, unobtrusive, wireless, lightweight, easy to set up, and possess a long battery life. Most importantly, they should be capable of clinical-grade EEG recording, which involves a high signal-to-noise ratio (SNR) and resilience to interferences like motion artifacts.

[0005] Unfortunately, signals obtained by electrodes for EEGs may include noise (i.e., random variations on the signal due to sources with unpredictable behaviour), interference (i.e., the effect of other signals present in the recording environment), and artifacts (e.g., due to electrode movement), collectively referred to herein as non-neurological inputs, are often attributable tofactors other than the neurological data the electrode is intended to obtain. Non-neurological inputs may be attributable to ambulatory movements of the subject. For example, impedance and capacitance of the electrode-skin interface may vary as the subject engages in regular activities such as eating, talking, walking, etc. Non-neurological inputs may also be system aspects, attributable aspects of the system such as variation in conductive elements and wires. These non- neurological inputs can lead to false readings or interpretations of the data in the signal requiring costly redundant testing or resulting in inaccurate diagnosis or insufficient treatment.

[0006] The most crucial requirement and perhaps the most prevalent challenge in wearable ambulatory EEG devices, regardless of their application, is achieving high-quality signal recording, especially when subjects engage any physical activities (e.g., nodding, chewing, walking, standing up, etc.). For a high-quality recording in these situations, in addition to standard requirements (e.g., voltage gain >50dB, bandwidth of 0.1-300 Hz, input-referred noise <100nV / ^Hz), robustness against motion artifacts (caused by electrode movements relative to the skin) and various sources of interference (e.g., wire movements, powerline noise from surrounding electrical fixtures) becomes essential.

[0007] These interferences and artifacts often far exceed the EEG signals in magnitude, overwhelming the recording circuitry and resulting in a complete loss of signal. While most interferences (e.g., powerline) can be filtered, this is not the case for motion artifacts. Due to their random nature in terms of shape, pattern, and occurrence rate, they cannot be filtered out in time or frequency domains. Ensuring resilience to artifacts necessitates integrating mechanisms into the device that can continuously monitor relative motion between the electrode and the skin, estimate its impact on the recorded signal (i.e., the artifact), and subsequently remove the artifact from the signal without compromising its integrity, all while adding minimally to the power consumption.

[0008] In existing systems, the electrode may be as simple as a conductive element, known as a passive electrode or passive transducer, for obtaining the signal and communicatively connected to an often lengthy wire for providing the obtained signal to a central backend for further processing. These electrodes are susceptible to non-neurological inputs both at the electrode and in transmission over the wire, particularly due to the weak unamplified signals being transmitted. These non-neurological inputs will be amplified at the backend along with neurological signals, negatively affecting the quality (i.e., signal-to-noise ratio) and reliability of the signal. Additionally, these devices typically employ general-purpose microchips in the central unit for amplification and digitization, which are developed for generic instrumentation applications. This often leads to one or more of the following issues: excessive noise, high power consumption, insufficient input impedance, and poor common-mode rejection. Moreover, the centralized architecture limits scalability and flexibility in terms of electrode count and placement.

[0009] Some existing systems, such as those used in ECGs, filter out non-neurological aspects via digital signal processing at the backend. This digital signal processing may include artifact and noise removal based on keeping only expected signal components (pass filtering). This filtering relies on expected signals being predeterminable with the likelihood of any anomalies outside of expected signals being attributable to noise or interference. This presents a risk of filtering out desirable neurological anomalies crucial for a proper diagnosis. Unlike with ECG signals, with EEG signals this risk is substantial as certain significant signal anomalies attributable neurological data are unlikely to be predeterminable or may be mistaken for noise or interference. Therefore, pass filtering based on expected signals is often inconsistent with filtering EEG signals.

[0010] In some existing systems where active electrodes (i.e., electrodes with embedded electronics for amplification and / or digitization) are used, signal processing to remove artifacts or suppress interferences are performed only at the backend once the signal has been transmitted to the backend. In these systems, the raw recorded signal (comprising EEG and all accompanying interferences / artifacts) with an excessive dynamic range (DR) of 10pV-500mV is communicated to the central unit where various power-hungry pattern recognition and filtering operations are performed to recover signal from interferences / artifacts. Additionally, the extremely-wide DR requires signal quantization with, for example, >16 bits of resolution, resulting in a significant increase in system power consumption, further reducing battery life.

[0011] For example, in some existing systems, system and ambulatory effects are filtered out based on a response to a reference current applied to the skin near the contact surface. The response may provide a reference impedance change signal for removal from the obtained signal at the backend. This impedance change signal however is subject to its own noise, interference and transmission concerns and may contain aspects similar to neurological aspects of the obtained signal. As these aspects may be indistinguishable from aspects attributable to neurological aspects, this filtering risks false filtering of significant neurological data.

[0012] In some existing systems, the signal obtained at the electrode is amplified at the electrode. These electrodes are known as active electrodes (AE). Interference attributable to transmission of the signal to the backend, such as from the wire, in signals from AEs are suppressed proportional to the amplification gain due to the discrepancy in the amplitude of the obtained signal relative to the transmission aspects. However, this amplification also amplifies non-neurological components of the obtained signal such as motion artifacts. Transmitting these components that often have much larger amplitude than neurological components contribute to increased data transmission and filtering range and capacity requirements, and increased power consumption.

[0013] In some existing systems where active electrodes (i.e., electrodes with embedded electronics for amplification and / or digitization) are used, signal processing to remove artifacts or suppress interferences are performed only at the backend once the signal has been transmittedto the backend. In these systems, the raw recorded signal (comprising EEG and all accompanying interferences / artifacts) with an excessive dynamic range (DR) of 10pV-500mV is communicated to the central unit where various power-hungry pattern recognition and filtering operations are performed to recover signal from interferences / artifacts. Additionally, the extremely-wide DR requires signal quantization with for example >16 bits of resolution, resulting in a significant increase in system power consumption, further reducing battery life.

[0014] Some existing systems, system aspects may be removed by aggregating and averaging system aspects of multiple electrodes at the backend into a common mode signal and subtracting the common mode signal from the signal of each electrode. In existing systems, this common mode rejection (CMR) occurs after amplification, digitization, and / or transmission to the backend. These operations reduce the efficacy of the CMR by separating the CMR from the specific AE collecting the signal. They also contribute to increased data transmission and filtering range and capacity requirements, and increased power consumption.

[0015] In some existing systems, the signal obtained is digitized and serialized at the AE. While here too, transmissions aspects may be addressed, non-neurological aspects of the obtained signal are still digitized. This maintains the CMR efficacy difficulties, to increased data transmission and filtering range and capacity requirements, and increased power consumption described above. Furthermore, while scalability is improved, the presence of non-neurological components in the data limit the scalability due to data capacity concerns.

[0016] Accordingly, there is a need for wearable AEs specifically clinical-grade quality wearable AEs designed for ambulatory electroencephalogram (EEG) monitoring and systems and methods for manufacturing the same that overcome the difficulties described above.Summary

[0017] There is provided a first active electrode (AE) for obtaining a neurological signal of a subject, the first active electrode configured to be disposed of on the head of the subject and communicatively connected to one or more of a second active electrode and a backend. The first active electrode includes a conductive element mounted to an AE board and disposed in contact with a skin of the subject for obtaining an obtained signal comprising neurological data; an electrode tissue impedance (ETI) module configured to receive the obtained signal from the conductive element and generate a replica artifact signal based on the application of ETI coefficients to the obtained signal; a second stage amplifier that is configured to receive an alpha Vcm signal based on a Vcm signal from a common-mode (CM) board, wherein the alpha Vcm signal is configured such that, when passed through the second stage amplifier to generate an amplified alpha Vcm, the amplified alpha Vcm is substantially equivalent to the Vcm signal amplified by a gain of (1+alpha)*G; receive a second stage input signal based on the obtained signal, wherein the second stage input signal, when passed through the second stage amplifier,is substantially amplified by a gain -G; and amplify and combine the amplified alpha Vcm and the second stage input signal to generate an amplified and common-mode-rejection (CMR)-boosted signal; a CMR boosting module that is configured to receive the Vcm signal from the CM board and obtain the alpha Vcm signal via a calibration variable resistor, wherein calibrating the calibration variable resistor calibrates an alpha of the CMR boosting module, wherein the alpha is an AE-specific attenuation coefficient, and wherein the alpha corresponds to a maximum suppression of the Vcm at calibration; an artifact removal module configured to receive the amplified and CMR-boosted signal output from the second stage amplifier; receive the replica artifact signal from the ETI module; and subtract the replica artifact signal from the amplified and CMR-boosted signal and output an AE data signal to the backend; and a mode control switch configured to toggle between a measurement mode configuration and a calibration mode configuration, wherein in the calibration mode configuration the AE data signal is diverted to a calibration module. The calibration module is configured to, when communicatively connected to the artifact removal module by the mode control switch, receive the AE data signal; determine a correlation result calculated based on the AE data signal; adjust the ETI coefficients based on the correlation result to obtain updated ETI coefficients; provide the updated ETI coefficients to the ETI module; and calibrate the calibration variable resistor of the CMR boosting module based on the correlation result.

[0018] The conductive element may be a passive electrode.

[0019] The conductive element may be a comb electrode.

[0020] The ETI module may comprise a current digital to analogue (l-DAC) converter configured to inject current pulses to the skin of the subject.

[0021] The l-DAC converter may be further configured to correct a DC level at the conductive element.

[0022] The first AE further may further comprise a DCin correction module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

[0023] The ETI module may further comprise a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

[0024] The SAR ADC may be an 8-bit SAR ADC.

[0025] The ETI module may further comprise an artifact estimation module configured to generate the replica artifact signal.

[0026] The first AE may further comprise a first stage amplifier configured to generate the second stage input signal based on the obtained signal, the Vcm signal, and a gain G1 .

[0027] The first AE may further comprise a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR boosted signal within a range.

[0028] The first AE may further comprise a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

[0029] The SC notch filter may be a band stop filter.

[0030] The first AE may further comprise a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

[0031] The first AE may further comprise a digital reconstruction module configured to rebuild the digitized signal.

[0032] The calibration module may be further configured to calibrate the artifact estimation module.

[0033] The calibration module may be configured to calibrate based on a calibration interval.

[0034] The calibration interval may be periodic at a preset interval.

[0035] The calibration interval may be based on an activity level of the subject.

[0036] The calibration interval may be based on a placement of the AE.

[0037] The calibration mode and the calibration interval may be set via a program.

[0038] The calibration module may comprise a gain and delay control module configured to generate the updated ETI coefficients.

[0039] The calibration module may comprise a correlation module configured to generate the correlation result.

[0040] The first AE may comprise a feature extraction module configured to generate extracted features of the AE data signal.

[0041] The first AE may comprise a classifier module configured to process the extracted features.

[0042] The classifier module may comprise a support vector machine (SVM).

[0043] There is provided a first active electrode (AE) for obtaining a neurological signal of a subject, the first active electrode configured to be disposed of on the head of the subject and communicatively connected to one or more of a second active electrode and a backend. The first active electrode includes a conductive element mounted to an AE board and disposed in contact with a skin of the subject for obtaining an obtained signal comprising neurological data; an electrode tissue impedance (ETI) module configured to receive the obtained signal from the conductive element and generate a replica artifact signal based on the application of ETI coefficients to the obtained signal; a second stage amplifier configured to amplify the obtainedsignal and output an amplified and common-mode-rejection (CMR)-boosted signal; an artifact removal module configured to receive the amplified and CMR-boosted signal from the second stage amplifier; receive the replica artifact signal from the ETI module; and subtract the replica artifact signal from the amplified and CMR-boosted signal and output an AE data signal to the backend; a mode control switch configured to toggle between a measurement mode configuration and a calibration mode configuration, wherein in the calibration mode configuration the AE data signal is diverted to a calibration module; the calibration module configured to, when communicatively connected to the artifact removal module by the mode control switch: receive the AE data signal; determine a correlation result calculated based on the AE data signal; adjust the ETI coefficients based on the correlation result to obtain updated ETI coefficients; and provide the updated ETI coefficients to the ETI measurement module.

[0044] The conductive element may be a passive electrode.

[0045] The conductive element may be a comb electrode.

[0046] The ETI module may comprise a current digital to analogue (l-DAC) converter configured to inject current pulses to the skin of the subject.

[0047] The l-DAC converter may be further configured to correct a DC level at the conductive element.

[0048] The first AE further may comprise a DCin correction module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

[0049] The ETI module may further comprise a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

[0050] The SAR ADC may be an 8-bit SAR ADC.

[0051] The ETI module may further comprise an artifact estimation module configured to generate the replica artifact signal.

[0052] The first AE may further comprise a first stage amplifier configured to generate the second stage input signal based on the obtained signal, the Vcm signal, and a gain G1 .

[0053] The first AE may further comprise a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR boosted signal within a range.

[0054] The first AE may further comprise a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

[0055] The SC notch filter may be a band stop filter.

[0056] The first AE may further comprise a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

[0057] The first AE may further comprise a digital reconstruction module configured to rebuild the digitized signal.

[0058] The calibration module may be further configured to calibrate the artifact estimation module.

[0059] The calibration module may be configured to calibrate based on a calibration interval.

[0060] The calibration interval may be periodic at a preset interval.

[0061] The calibration interval may be based on an activity level of the subject.

[0062] The calibration interval may be based on a placement of the AE.

[0063] The calibration mode and the calibration interval may be set via a program.

[0064] The calibration module may comprise a gain and delay control module configured to generate the updated ETI coefficients.

[0065] The calibration module may comprise a correlation module configured to generate the correlation result.

[0066] The first AE may comprise a feature extraction module configured to generate extracted features of the AE data signal.

[0067] The first AE may comprise a classifier module configured to process the extracted features.

[0068] The classifier module may comprise a support vector machine (SVM).

[0069] There is also provided a first active electrode (AE) for obtaining a neurological signal of a subject, the first active electrode configured to be disposed of on the head of the subject and communicatively connected to one or more of a second active electrode and a backend. The first active electrode includes a conductive element mounted to an AE board and disposed in contact with a skin of the subject for obtaining an obtained signal comprising neurological data; a second stage amplifier configured to receive an alpha Vcm signal based on a Vcm signal from a commonmode (CM) board, wherein the alpha Vcm signal is configured such that, when passed through the second stage amplifier to generate an amplified alpha Vcm, the amplified alpha Vcm is substantially equivalent to the Vcm signal amplified by a gain of 1+alpha*G; receive a second stage input signal based on the obtained signal wherein the second stage input signal when passed through the second stage amplifier is substantially amplified by a gain -G; amplify and combine the amplified alpha Vcm signal and the second stage input signal to obtain an AE data signal; and output the AE data signal to the backend; a common-mode-rejection (CMR)-boosting module configured to receive the Vcm signal from the CM board and obtain the alpha Vcm signalvia a calibration variable resistor, wherein calibrating the calibration variable resistor calibrates an alpha of the CMR-boosting module, wherein the alpha is an AE-specific attenuation coefficient, and wherein the alpha corresponds to a maximum suppression of the Vcm at calibration; a mode control switch configured to toggle between a measurement mode configuration and a calibration mode configuration, wherein in the calibration mode configuration the AE data signal is diverted to a calibration module; the calibration module configured to, when communicatively connected to the second stage amplifier by the mode control switch: receive the AE data signal; determine a correlation result calculated based on the AE data signal; and calibrate the calibration variable resistor of the CMR-boosting module based on the correlation result.

[0070] The conductive element may be a passive electrode.

[0071] The conductive element may be a comb electrode.

[0072] The ETI module may comprise a current digital to analogue (l-DAC) converter configured to inject current pulses to the skin of the subject.

[0073] The l-DAC converter may be further configured to correct a DC level at the conductive element.

[0074] The first AE further may comprise a DCin correction module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

[0075] The ETI module may further comprise a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

[0076] The SAR ADC may be an 8-bit SAR ADC.

[0077] The ETI module may further comprise an artifact estimation module configured to generate the replica artifact signal.

[0078] The first AE may further comprise a first stage amplifier configured to generate the second stage input signal based on the obtained signal, the Vcm signal, and a gain G1 .

[0079] The first AE may further comprise a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR boosted signal within a range.

[0080] The first AE further may comprise a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

[0081] The SC notch filter may be a band stop filter.

[0082] The first AE further may comprise a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

[0083] The first AE may further comprise a digital reconstruction module configured to rebuild the digitized signal.

[0084] The calibration module may be further configured to calibrate the artifact estimation module.

[0085] In the calibration mode, the calibration module may be configured to calibrate based on a calibration interval.

[0086] The calibration interval may be periodic at a preset interval.

[0087] The calibration interval may be based on an activity level of the subject.

[0088] The calibration interval may be based on a placement of the AE.

[0089] The calibration mode and the calibration interval may be set via a program.

[0090] The calibration module may comprise a gain and delay control module configured to generate the updated ETI coefficients.

[0091] The calibration module may comprise a correlation module configured to generate the correlation result.

[0092] The first AE may comprise a feature extraction module configured to generate extracted features of the AE data signal.

[0093] The first AE may comprise a classifier module configured to process the extracted features.

[0094] The classifier module may comprise a support vector machine (SVM).

[0095] There is also provided a method of obtaining a neurological signal of a subject. The method includes obtaining, by a first active electrode (AE), an obtained signal comprising the neurological signal, wherein the first active electrode is configured to be disposed of on a head of a subject, and wherein the first active electrode is communicatively connected to one or more of a second active electrode and a backend; generating a replica artifact signal based on the application of electrode tissue impedance (ETI) coefficients to the obtained signal; generating an alpha Vcm signal based on a calibration variable resistor; generating an amplified alpha Vcm signal based on the alpha Vcm signal; amplifying and combining the amplified alpha Vcm signal and a second stage input signal to generate an amplified and common-mode-rejection (CMR)- boosted signal; subtracting the replica artifact signal from the amplified and CMR-boosted signal to generate an AE data signal; outputting the AE data signal to the backend; determining a correlation result based on the AE data signal; adjusting the ETI coefficients based on the correlation result to obtain updated ETI coefficients; and providing the updated ETI coefficients.

[0096] The first AE may include a conductive element.

[0097] The conductive element may include a passive electrode.

[0098] The conductive element may include a comb electrode.

[0099] The first AE may include a current digital to analogue (l-DAC) converter configured to inject current pulses to a skin of the subject.

[0100] The l-DAC converter may be further configured to correct a DC level at the conductive element.

[0101] The first AE may further comprise a DCin correction module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

[0102] The first AE may comprise an ETI module, wherein the ETI module further comprises a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

[0103] The SAR ADC may be an 8-bit SAR ADC.

[0104] The ETI module may further comprise an artifact estimation module configured to generate the replica artifact signal.

[0105] The first AE may further comprise a first stage amplifier configured to generate the second stage input signal based on the obtained signal, the Vcm signal, and a gain G1 .

[0106] The first AE may further comprise a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR boosted signal within a range.

[0107] The first AE may further comprise a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

[0108] The SC notch filter may be a band stop filter.

[0109] The first AE may further comprise a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

[0110] The first AE may further comprise a digital reconstruction module configured to rebuild the digitized signal.

[0111] The first AE may further comprise a calibration module configured in a calibration mode, wherein the calibration module is further configured to calibrate the artifact estimation module.

[0112] In the calibration mode, the calibration module may be configured to calibrate based on a calibration interval.

[0113] The calibration interval may be periodic at a preset interval.

[0114] The calibration interval may be based on an activity level of the subject.

[0115] The calibration interval may be based on a placement of the AE.

[0116] The calibration mode and the calibration interval may be set via a program.

[0117] The calibration module may comprise a gain and delay control module configured to generate the updated ETI coefficients.

[0118] The calibration module may comprise a correlation module configured to generate the correlation result.

[0119] The first AE may comprise a feature extraction module configured to generate extracted features of the AE data signal.

[0120] The first AE may comprise a classifier module configured to process the extracted features.

[0121] The classifier module may comprise a support vector machine (SVM).

[0122] There is also provided a method of obtaining a neurological signal of a subject. The method includes obtaining, by a first active electrode (AE), an obtained signal comprising the neurological signal, wherein the first active electrode is configured to be disposed of on the head of the subject, and wherein the first active electrode is communicatively connected to one or more of a second active electrode and a backend; generating a replica artifact signal based on the application of electrode tissue impedance (ETI) coefficients to the obtained signal; amplifying the obtained signal to output an amplified and common-mode-rejection (CMR)-boosted signal; subtracting the replica artifact signal from the amplified and CMR-boosted signal to generate an AE data signal; outputting the AE data signal to the backend; determining a correlation result based on the AE data signal; adjusting the ETI coefficients based on the correlation result to obtain updated ETI coefficients; and providing the updated ETI coefficients;

[0123] The first AE may include a conductive element.

[0124] The conductive element may include a passive electrode.

[0125] The conductive element may include a comb electrode.

[0126] The first AE may include a current digital to analogue (l-DAC) converter configured to inject current pulses to a skin of the subject.

[0127] The l-DAC converter may be further configured to correct a DC level at the conductive element.

[0128] The first AE may further comprise a DCin correction module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold andlower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

[0129] The first AE may comprise an ETI module, wherein the ETI module further comprises a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

[0130] The SAR ADC may be an 8-bit SAR ADC.

[0131] The ETI module may further comprise an artifact estimation module configured to generate the replica artifact signal.

[0132] The first AE may further comprise a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR boosted signal within a range.

[0133] The first AE may further comprise a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

[0134] The SC notch filter may be a band stop filter.

[0135] The first AE may further comprise a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

[0136] The first AE may further comprise a digital reconstruction module configured to rebuild the digitized signal.

[0137] The first AE may further comprise a calibration module configured in a calibration mode, wherein the calibration module is further configured to calibrate the artifact estimation module.

[0138] In the calibration mode, the calibration module may be configured to calibrate based on a calibration interval.

[0139] The calibration interval may be periodic at a preset interval.

[0140] The calibration interval may be based on an activity level of the subject.

[0141] The calibration interval may be based on a placement of the AE.

[0142] The calibration mode and the calibration interval may be set via a program.

[0143] The calibration module may comprise a gain and delay control module configured to generate the updated ETI coefficients.

[0144] The calibration module may comprise a correlation module configured to generate the correlation result.

[0145] The first AE may comprise a feature extraction module configured to generate extracted features of the AE data signal.

[0146] The first AE may comprise a classifier module configured to process the extracted features.

[0147] The classifier module may comprise a support vector machine (SVM).

[0148] There is also provided a method of obtaining a neurological signal of a subject. The method includes obtaining, by a first active electrode (AE), an obtained signal comprising the neurological signal, wherein the first active electrode is configured to be disposed of on the head of the subject, and wherein the first active electrode is communicatively connected to one or more of a second active electrode and a backend; generating an alpha Vcm signal based on a calibration variable resistor; generating an amplified alpha Vcm signal based on an alpha Vcm signal; amplifying and combining the amplified alpha Vcm signal and a second stage input signal to generate an AE data signal; outputting the AE data signal to the backend; determining a correlation result based on the AE data signal; and calibrating the calibration variable resistor based on the correlation result;

[0149] The first AE may include a conductive element.

[0150] The conductive element may include a passive electrode.

[0151] The conductive element may include a comb electrode.

[0152] The first AE may include a current digital to analogue (l-DAC) converter configured to inject current pulses to a skin of the subject.

[0153] The l-DAC converter may be further configured to correct a DC level at the conductive element.

[0154] The first AE may further comprise a DCin correction module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

[0155] The first AE may comprise an ETI module, wherein the ETI module further comprises a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

[0156] The SAR ADC may be an 8-bit SAR ADC.

[0157] The ETI module may further comprise an artifact estimation module configured to generate the replica artifact signal.

[0158] The first AE may further comprise a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR-boosted signal within a range.

[0159] The first AE may further comprise a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

[0160] The SC notch filter may be a band stop filter.

[0161] The first AE may further comprise a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

[0162] The first AE may further comprise a digital reconstruction module configured to rebuild the digitized signal.

[0163] The first AE may further comprise a calibration module configured in a calibration mode, wherein the calibration module is further configured to calibrate the artifact estimation module.

[0164] In the calibration mode, the calibration module may be configured to calibrate based on a calibration interval.

[0165] The calibration interval may be periodic at a preset interval.

[0166] The calibration interval may be based on an activity level of the subject.

[0167] The calibration interval may be based on a placement of the AE.

[0168] The calibration mode and the calibration interval may be set via a program.

[0169] The calibration module may comprise a gain and delay control module configured to generate the updated ETI coefficients.

[0170] The calibration module may comprise a correlation module configured to generate the correlation result.

[0171] The first AE may comprise a feature extraction module configured to generate extracted features of the AE data signal.

[0172] The first AE may comprise a classifier module configured to process the extracted features.

[0173] The classifier module may comprise a support vector machine (SVM).

[0174] Other aspects and features will become apparent to those ordinarily skilled in the art, upon review of the following description of some exemplary embodiments.Brief Description of the Drawings

[0175] The drawings included herewith are for illustrating various examples of articles, methods, and apparatuses of the present specification. In the drawings:

[0176] Figure 1 is a block diagram and schematic diagram of a wearable EEG system disposed on a user, according to an embodiment;

[0177] Figure 2 is a set of images of various components of the EEG system of Figure 1 ;

[0178] Figure 3 is an image of an active electrode integrated circuit (IC) of the EEG system ofFigure 1 , according to an embodiment;

[0179] Figure 4 is a schematic diagram of the active electrode IC of Figure 3;

[0180] Figure 5 is a schematic diagram of various components of the active electrode IC of Figure 3;

[0181] Figures 6A-6C are schematic diagrams of a common-mode-rejection (CMR) boosting module of the active electrode IC of Figure 3, according to an embodiment;

[0182] Figure 7 is a set of charts of measurement results showing performance of an active electrode of Figure 3, according to an embodiment;

[0183] Figure 8 is a comparison chart of embodiments of the EEG system of Figure 1 , according to various embodiments;

[0184] Figures 9A-9C are schematic diagrams and block diagrams of the EEG system of Figure 1 , according to various embodiments;

[0185] Figure 10 is a chart of power consumption breakdown of various EEG systems, according to an embodiment;

[0186] Figures 11A-11C are annotated block diagrams of CMR improvement in various EEG systems;

[0187] Figure 12 is an annotated block diagram of centralized backend CMR improvement in the EEG system of Figure 1 ;

[0188] Figure 13 is a flow diagram of a method of obtaining a neurological signal of a subject, according to an embodiment;

[0189] Figure 14 is a flow diagram of a method of obtaining a neurological signal of a subject, according to an embodiment; and

[0190] Figure 15 is a flow diagram of a method of obtaining a neurological signal of a subject, according to an embodiment.Detailed Description

[0191] Various apparatuses or processes will be described below to provide an example of each claimed embodiment. No embodiment described below limits any claimed embodiment and any claimed embodiment may cover processes or apparatuses that differ from those described below. The claimed embodiments are not limited to apparatuses or processes having all of the features of any one apparatus or process described below or to features common to multiple or all of the apparatuses described below.

[0192] While the above description provides examples of one or more compositions, apparatus, methods, or systems, it will be appreciated that other compositions, apparatus,methods, or systems may be within the scope of the claims as interpreted by one of skill in the art.

[0193] Provided herein are active electrodes and specifically digital active electrodes with common mode rejection boosting, dynamic range boosting, electrode tissue impedance measurement, motion artifact removal and calibration of the common mode rejection and artifact estimation at the active electrode. These AEs offer a substantial improvement over existing systems in accessibility to monitoring and diagnostic care for millions of patients with neurological disorders outside of hospital settings. Consequently, they reduce hospital stays over existing systems and enhance diagnostic efficiency through continuous remote monitoring.

[0194] Referring to Figure 1 , shown therein is a block diagram and schematic of a wearable EEG system 100 disposed on a user, according to an embodiment. Referring also to Figures 2 and 3, shown therein are annotated photographic images of components of the EEG system 100, according to an embodiment. The EEG system 100 includes a series of active electrodes (AEs) 101 (referred to generically as the AE 101 and collectively as the AEs 101), each housing an AE integrated circuit (IC) 102 as shown in Figure 1 , which integrates all the aforementioned features (i.e., common mode rejection boosting 104, dynamic range boosting 106, electrode tissue impedance measurement 108, motion artifact removal 110 and calibration of the common mode rejection and artifact estimation at the active electrode). The AE 101 comprises an AE board, such as AE board 201 shown in Figure 2. The AE board 201 hosts an AE IC 102 (shown in Figure 3), daisy-chained connectors 202a-202d, and a conductive pad 204, as shown in Figure 2.

[0195] The AE 101 is communicatively and electrically daisy chained together in series with one or more additional of the AE 101. The daisy chain is configured to be disposed on a head of user with the AEs 101 in contact with various locations on the head. The configuration of the daisy chain and disposition of each AE 101 may vary based on the user and application. In an example, the AEs 101 are disposed in a serpentine configuration, as shown. The daisy chain configuration beneficially allows the addition of any number of AEs 101 in any arbitrary configuration with a plurality of wires 105 (referred to generically as the wire 105 and collectively as the wires 105) connecting different AEs 101 and a backend 174. In an embodiment, the EEG system 100 comprises only six wires 105. In addition to the cost, weight, comfort, convenience, and mitigation of tangle and snagging risk benefits of less wires 105, minimizing additional wires 105 advantageously reduces transmission error and simplifies digital signal processing by minimizing the amount of noise introducing variables. It will be appreciated that the data, power, and signal processing benefits of the description below may further contribute to the scalability of this daisy chain.

[0196] Referring also to Figure 4, shown therein is a detailed block diagram of an AE IC 102, according to an embodiment.

[0197] Each AE IC 102 includes a conductive element, such as conductive element 103, also known as a passive electrode. As an example, a first AE IC 102 includes the conductive element 103, and a second AE IC communicatively and electrically daisy chained together in series with the first AE IC 102 includes a conductive element 107. The conductive element 103 is configured to contact the skin of the user at a contact surface. The contact provides a communicative connection with the skin for obtaining a neurological signal. The conductive element 103 may include a flat electrode 205a or a through hair / comb electrode 205b with protrusions for penetrating the hair as shown in Figure 2 (top middle and bottom middle, respectively).

[0198] The conductive element 103 is communicatively connected to an electrode tissue impedance (ETI) measurement module 401. The ETI measurement module 401 is configured to measure the impedance between the conductive element 103 and the skin at the contact point and estimate signal artifacts based on the impedance change at the electrode. It will be appreciated that impedance (Z), as referred to herein, is a complex number (Z=R+jX), which includes both the real (R) and imaginary (X) parts. The real part (R) represents resistance, and the imaginary part (X) represents reactance. The reactance could be positive (inductive) or negative (capacitive). It will be appreciated that the artifact estimation may be based on capacitance rather than or in addition to resistance.

[0199] The ETI measurement module 401 includes an ETI current digital to analogue (l-DAC) converter 402. The l-DAC 402 is configured to inject high-frequency current pulses of programmable magnitude and frequency to the skin, so that the resultant voltage can be recorded. In an example, the resultant voltage is recorded using the Gm3 amplifier, further described below and ETI is calculated accordingly using Ohm’s law.

[0200] Due to the non-Faradaic interface between the electrode and the skin, non-reversible oxidation / reduction may occur at the electrode-skin interface. This oxidation / reduction may lead to charge accumulation, which in long term, could damage the skin or the electrode. To address the effect of this charge accumulation, the l-DAC 402 simultaneously corrects the DC level at the recording electrode 103. For this correction, The l-DAC 402 applies an intentional imbalance between the sink and source sections of the current pulse to remove the offset at the input. An unbalanced current sink and source current will inject or draw charges to and / or from the electrode 101 which can change the voltage at the electrode site. This beneficially mitigates charge accumulation on the skin at the contact site minimizing tissue damage.

[0201] The AE IC 102 further includes a signal recording 304. The signal recording 304 represents the physical layout of components in the recording path of each AE 101. The signal recording 304 includes, for example, common-mode rejection boosting module 104, dynamic range boosting module 106, amplification stage A1 118, and amplification stage A2 120.

[0202] The AE IC 102 further includes a direct current DCin correction module 404. The unbalanced sink and source current is determined based on an output of the DCincorrection circuit.

[0203] The DCin correction module 404 includes a switched-capacitor averager (SC AVG) module 406. The SC AVG module 406 measures the DC voltage of the input at the electrode 103 to adjust the input offset. An embodiment of the SC AVG 406 is shown in Figure 5 (top middle).

[0204] The voltage measured by the SC AVG module 406 is compared to an upper voltage threshold (Vth-H2) and a lower voltage threshold (Vth-1.2). A DCinDAC control 408 of the DCincorrection module 404 is configured to control the l-DAC 402 based on the compared measured voltage.

[0205] Referring back to the ETI measurement module 401 , the module further includes an ETI capacitive-feedback amplifier 410 that is formed around a trans-conductance stage (Gms). The amplifier 410 is responsible for magnifying the high-frequency voltage at the electrode that is generated due to the high-frequency (e.g., 10kHz) current injection by the l-DAC 402. Due to the high frequency of this current, the resulting voltage, which is at the same frequency, will not interfere with the neurological signals that exist, for example, in the 0-500Hz frequency range. As such, adverse effects of the ETI measurement module 401 on the quality of recording neurological signals are avoided.

[0206] The ETI measurement module 401 further includes a switched-capacitor peak-to-peak detection module 412 (SC Pk-Pk Detection). An embodiment of the SC Pk-Pk Detection module 412 is shown in Figure 5 (top left). The SC Pk-Pk Detection module 412 receives the amplified ETI signal from the capacitive-feedback amplifier 410 and extracts the peak-to-peak value of the high-frequency voltage pulse, which is proportional to the magnitude of the ETI.

[0207] In some embodiments, the ETI measurement module 401 further includes a successive approximate register (SAR) analogue to digital converter (ADC) 414. The SAR ADC 414 digitizes, also known as quantizes, the signal from the SC Pk-Pk Detection module 412. It will be appreciated that in embodiments without the SAR ADC 414 the artifact estimation may be in the analogue domain. The SAR ADC 414 may be an 8 bit SAR ADC.

[0208] Digitizing the signal at the AE 101 enables daisy chaining the AEs 101 as well as in- AE feature extraction and signal processing, if required. The digitization also immunizes the signal from transmission noise from wires 105 and other AEs 101 by quantizing the data of the signal substantially beyond amplitude of any such noise. Digitization also enables serialization further enabling transmission of the signals of the multiple AEs 101 together but discreetly over a single wire 105 of the daisy chain.

[0209] The ETI measurement module 401 further includes an artifact estimation module 416. The artifact estimation module 416 is configured to generate an estimated artifact replica signal417. The artifact replica signal 417 is generated by applying a specific set of gain and delay values to the ETI magnitude that is present at the output of SC Pk-Pk Detection module 412. The process of applying gains and delays could be done in the analog or digital domains. In Figures 4 and 5, an example implementation in digital domain is shown, where an ADC, such as SAR ADC 414, is required for digitization of the signal prior to artifact estimation. The artifact replica signal 417 is an estimate signal including artifacts of the obtained signal attributable to the impedance changes at the surface of electrode 103. By estimating the artifacts based on multiple gain and delay pairs applied to the obtained signal, rather than for example a predetermined signal mapped to an impedance value of existing systems, the artifact replica signal 417 is specific to the obtained signal, AE 101 architecture and application, and environmental factors, at least at the time of the coefficients were calibrated as described below. Specifically, the delay coefficient enables the system to accommodate phase delays in the effects of impedance variation on the obtained signal. The gain coefficient and tap correspondence enable alignment of the artifact replica signal 417 in artifact amplitude and duration, respectively, as well. This specificity beneficially reduces the risk of unintended removal of artifacts and optimizes the removal of artifacts without the need for predetermined good signals, also known as gold signals, pass signals or bands, and expected signals.

[0210] The AE IC 102 further includes a motion removal and feature extraction module 170 comprising an artifact removal module 110 (motion removal module 110 in Figure 1). The artifact removal module 110 is configured to receive a boosted, notched, and digitized signal 420 from a digital reconstruction module 418, further described below. The artifact removal module 110 is further configured to receive the artifact replica signal 417 from the artifact estimation module 416 and to remove (i.e. subtract) the estimated artifacts from the boosted, notched, and digitized signal 420. This removal, also known as motion artifact removal (MAR) beneficially improves the quality of the neurological signal output from the AE 101 particularly by removing motion artifacts at the AE 101.

[0211] Referring back to Figure 1 , the EEG system 100 further includes a reference electrode 112. The reference electrode 112 may be a passive electrode. The reference electrode 112 is used to feed an average of all signals recorded from all AEs 101 (also known as the commonmode signal) back to the skin, which results in a significant improvement in rejecting the common noise / interferences in all AEs 101 , hence, improving the recording quality, as described further below.

[0212] The EEG system 100 further includes a CM module 114 also referred to as CM feedback board. The CM module 114 may be an IC on a PCB. The CM module 114 is communicatively connected to the reference electrode 112 that is configured to drive the skin with the CM signal (Vcm) that is generated through averaging the recorded signal from all AEs 101 asdescribed further below. Embodiments of the CM module 1 14 are shown in Figure 2 (top left) and a simplified conceptual presentation at the bottom portion of Figure 6C.

[0213] A common mode voltage Vcm 1 16 is estimated through capacitive averaging as described further below. The average of all the signals recorded from all AEs 101 contain no neurological component and is comprised of common unwanted interferences (e.g., power-line noise) that may have been coupled onto all AEs 101 and will be removed. Therefore, the CM feedback board 1 14 amplifies the Vcm 1 16 and then drives the skin with it. This will result in rejection of the majority of such common-mode interferences, which in turn leads to the signal obtained by the AEs 101 having a much higher quality.

[0214] Additionally, in each AE 101 , the Vcm 1 16 is used to perform further common-mode rejection (CMR), thus boosting the quality of recorded signal. This is done by amplifying the difference between the signal at each electrode 103 and the Vcm 1 16 inside each AE 101. As shown in Figure 1 , this is done in both amplification stages A1 1 18 and A2 120, in which Vcm 1 16 is fed to one input of the differential amplifier while the signal recorded from the electrode 103 is fed to the other input. A1 1 18 and A2 120 are implemented as capacitive-feedback amplifiers built around transconductance stages (Gmiand Gm2) as shown in Figure 4. Each gain of these amplifiers (Gi and G2) is set based on the ratio of feedback over input capacitors. Conducting CM calculation and rejection inside each AE 101 , instead of in a central backend unit as in existing systems, beneficially avoids transmission, synchronization, and delayed calibration issues of existing systems performing centralized CMR after transmission to the backend 174.

[0215] Referring back to Figure 4, the AE IC 102 includes a first-stage capacitive-feedback amplifier 1 18 that is built around a transconductance stage Gm1 and is communicatively connected to the conductive element 103 and receives the obtained signal 122 from the conductive element 103 (Veiectrode-i). The signal 122 at the conductive element 103 of each AE 101 (Veiectrode-i) is copied from the positive input of the Gm1 1 18 to its negative input due to the negative feedback around the Gm1 1 18. The negative terminal of the Gm1 118 is connected to the Vcm 1 16 through a capacitor Ccm 124, which is placed in each AE 101 to form the aforementioned capacitive averaging required for Vcm 1 16 calculation, as further described below.

[0216] The capacitive connection to Vcm 1 16 works both ways, meaning that the resulting Vcm 1 16 from averaging acts as a second input to the first-stage differential amplifier 1 18 at each AE 101 , resulting in the difference between Veiectrode-i 122 and Vcm 1 16 to be amplified resulting in G1*( Veiectrode-i - Vcm) 126 at the output, thus significantly improving CMR.

[0217] The AE 101 further includes a saturation detection module 448 communicatively connected to the output of the first stage amplifier A1 1 18. The saturation detection module 448 is configured to monitor the voltage at the output of the first stage amplifier A1 1 18 and detect saturation of the voltage. The saturation detection module 448 is further configured to adjust avariable capacitor 449 in the feedback path of the first stage amplifier A1 1 18. The variable capacitor 449 is configured to control the gain of the first stage amplifier A1 1 18. The saturation detection module 448 is further configured to adjust the variable capacitor 449 when saturation of the voltage is detected such that saturation of the voltage is prevented.

[0218] The AE 101 further includes a second stage closed-loop amplifier A2 120 built around Gm2. The amplifier 120 is communicatively connected to the first stage amplifier A1 1 18 and receives the amplified signal 126 (i.e., G1*( Velectrode-i - Vcm)) from it. The second stage amplifier A2 120 is further communicatively connected to the common mode board 1 14 and receives the common mode voltage signal Vcm 116 from the common mode board 1 14.

[0219] The Vcm 1 16 is passed through a common mode rejection (CMR) boosting module 104, further described below, prior to being received by the second stage closed-loop amplifier 120. The second stage amplifier 120 is configured to subtract a*Vcm from the main signal 126 (i.e., the output of first stage amplifier A1 1 18) and amplify the resultant signal by the gain G2 of the second stage amplifier A2 120. It will be appreciated that a is AE-specific and is obtained through calibration further described below and the gain G2 is set by the ratio of the capacitance of the input capacitor 421 (for example 40pF) over the capacitance of the feedback capacitor 422 (for example 5pF).

[0220] The common mode rejection (CMR) boosting 424 indicated in Figure 4 shows an embodiment of the CMR boosting module 104 described above. In this embodiment, (a+1)*Vcm 128 is subtracted from the main signal 126, which is Gi*(Veiectrode-i -Vcm) before being amplified by the gain of the second-stage amplifier 120 to result in G2*(Gi*(Veiectrode-i -Vcm)- (a+1)Vcm) 130. The CMR boosting module 104 is communicatively connected to the common mode board 114 and receives the Vcm 1 16 from the common mode board 1 14. The CMR boosting module 104 is configured to provide the Vcm 1 16 to the second stage amplifier A2 120 such that gain seen by the Vcm 1 16 is -(1 +a)G2. It will be appreciated that the gain seen by the amplified signal received by the second stage amplifier A2 120 from the first stage amplifier A1 1 18 is G2. In some embodiments, the boosting of the CMR boosting module 104 is calibrated by adjusting the resistance of a calibration variable resister of the CMR boosting module, such as calibration resister 426 shown in Figure 4. Figures 6A through 6C show the CMR boosting module 104 according to conceptual, simplified, and detailed embodiments. The capacitive averaging used for Vcm 1 16 generation is also shown in Figure 6C.

[0221] Boosting the CMR at the AE 101 , rather than for example, at the central backend, enables amplification of the input signal Veiectrode-i 122 and removal of noise and interference based on the reference signal 116 while avoiding amplification of the common mode aspects of the input signal Veiectrode-i 122. As any subtraction and amplification occurs using the same amplifier circuitry, the amplification of Vcm 1 16 and the Veiectrode-i 122 is perfectly matched and the introduction ofany residual errors due to component mismatch between different amplification circuitries as in existing systems is beneficially avoided.

[0222] It will be appreciated that variations between the common mode components of the reference signal 116 and the obtained signals 122 of each AE 101 can be minimized but not completely eliminated. For example, variations in composition and configuration in AEs 101 and the reference electrode 112 will remain due to manufacturing limitations and environmental inconsistencies particularly due to placement, contact site variations, and the effects motion varying by site cannot be fully avoided. Therefore, boosted CMR, the MAR described above, and other forms of digital signal processing, separately or in combination beneficially improve the quality of the neurological signal obtained by the EEG system 100.

[0223] The AE 101 further includes a dynamic range (DR) boosting module 106. The DR boosting module 106 is communicatively connected to the output of the second amplifier A2 120 and receives the CMR-boosted signal 130 via this connection. The DR boosting module 106 is configured to maintain the output level of the second stage amplifier 120 within a certain range.

[0224] The DR boosting module 106 includes a high voltage reference comparator Vth-Hi 428 and a low voltage reference comparator Vth-Li 430. Where the CMR boosted signal 130 is above or below the threshold voltages of the Vth-Hi and Vth-Li respectively, the DR boosting module 106 pushes the signal down and up (using the voltage-mode digital to analog converter (V-DAC) 432), respectively, to maintain the signal within the predetermined range. This shift (i.e. timing, direction, and extent) is provided to the digital reconstruction module 418, further described below for reconstruction purposes. Maintaining the signal in a predetermined range limits the dynamic range of the signals that needs to be quantized, significantly relaxing its design requirements, hence power consumption.

[0225] Then DR boosting module 106 further includes a Ctrl 450 for applying appropriate DC level shifting required for boosting the effective dynamic range. The Ctrl 450 is configured to take the outputs of the comparator Vth-Hi 428 and the comparator Vth-Li 430 and provide a 6-bit control signal to the V-DAC 432.

[0226] The AE 101 further includes a switched-capacitor (SC) notch filter 434. The SC notch filter 434 is communicatively connected to the second stage amplifier 120 and receives the CMR and DR boosted signal 132 via this connection. The SC notch filter 434 is configured to remove power-line noise such a noise at 60Hz in areas where 60 Hz is the standard power-line frequency. The SC notch filter 434 may be a band stop filter. An embodiment of the SC notch filter 434 is shown in Figure 5 (bottom, left).

[0227] In an embodiment, the AE 101 further includes a Noise Shaping (NS) SAR ADC 134. The NS SAR ADC 134 is communicatively connected to the SC notch filter 434 and receives thefiltered and boosted signal via this connection. The NS SAR ADC 134 is configured to digitize the received signal. The NS SAR ADC 134 comprises a decimation filter 302 (shown in Figure 3).

[0228] The AE 101 further includes a digital reconstruction module 418. The digital reconstruction module 418 is communicatively connected to the NS SAR ADC 134 and receives the digitized signal via this connection. The digital reconstruction module 418 is configured to rebuild the digitized signal.

[0229] The AE 101 further includes a calibration module 436. The calibration module 436 is configured to calibrate various other modules of the AE 101 such as the artifact estimation module 416 and the CMR boosting module 424.

[0230] The calibration module 436 is active when the AE 101 transitions from a measurement mode to a calibration mode. The mode of the system may be toggled via a mode switch. In some embodiments the mode switch is a physical switch, such as physical switch 438 configured to be toggled manually. In some embodiments, the mode switch is set to toggle between measurement mode and calibration mode periodically at a preset interval. For example, the electrode may calibrate every hour, 2 hours, day, and the like. The calibration interval may be based on the activity level of the subject. The calibration interval may further be based on the placement of the electrode. The calibration interval may be AE-specific with each electrode 103 having a different calibration interval. For example, where a specific electrode 103 is positioned in a location sensitive to being disturbed altering the effect of impedance change, calibration may be more frequent than with electrodes 103 expected to remain stable. The calibration mode and / or interval may be set via a program 440, for example a program uploaded to the calibration module 436. The calibration module 436 may be communicatively connected to the backend 174 and specifically a main control module of the backend 174 via program wire. The backend may upload the program for setting the calibration interval via the program wire.

[0231] It will be appreciated that the calibration module 436 may include a calibration mode for each module it is calibrating. For example, the calibration module 436 may include an ETI calibration mode dedicated to calibrating the ETI measurement module 401. The AE 101 may further include mode switches, programs, and calibration intervals similarly dedicated.

[0232] In calibration mode, the calibration module 436 is communicatively connected to the artifact removal module 110 by a mode control switch 438. The mode control switch 438, in calibration mode, is configured to direct the output of artifact removal module 110 to the calibration module 436. The mode control switch 438 may be a physical switch. The mode control switch 438 may be toggled by a subject or other user such as an aid or via a program such as a program 440 uploaded to the calibration module 436.

[0233] The calibration module 436 is configured to determine ETI gain and delay coefficients and provide them to the artifact estimation module 416. Determining the ETI gain and delaycoefficients is based on which gain and delay coefficients when applied to the digitized ETI signal 420 produces an estimated artifact signal 417 that is closest to null when the reconstructed digitized EEG signal 420 is subtracted from estimated artifact signal 417. It will be appreciated that while calibration in the digital domain is described, calibration may be conducted in the analogue domain rather than the digital domain such as where the artifact estimation and removal is performed prior to digitization of the signal.

[0234] Figure 5 in the dashed box shows a block diagram of the calibration module 436, according to an embodiment. The calibration module 436 includes gain & delay control module 502. The gain and delay control module 502 is configured to vary the gain and delay coefficients and provide the coefficients to the artifact estimation module 416. The 16-tap 8-bit shift register (SR) 504 creates 16 copies of the recorded ETI, delayed with 1 to 16 delay units, and the multiplexer (MUX) 506 chooses which copies are used for replica creation. The MUX 506 is controlled by the delay control signal 508. The copies that are selected are multiplied by gain values that are adjusted through the control loop described above. The gain and delay control module 502 varies the coefficients based on the correlation result from a correlation module 510, further described below. The gain and delay control of the module 502 may continue to vary the coefficients until the results of the correlation module 510 indicate that the optimal coefficients for the tap within the available coefficients have been obtained.

[0235] The calibration module 436 further includes a correlation module 510. In calibration mode, the correlation module 510 receives output signal 442 of the artifact removal module 110 and calculates a correlation result 444. The correlation result 444 indicates the effectiveness of the coefficients to estimate motion artifacts when applied to the digitized ETI signal output from the SAR ADC 134. The correlation module 510 is communicatively connected to the gain and delay control 502 for providing the correlation result 444 to the gain and delay control 502.

[0236] The calibration module 436 may further be configured to calibrate a calibration resistor of the CMR Boosting module 424, such as calibration resister 426. In calibration mode, a SC notch filter bypass switch, such as switch 446, is closed. Closing the switch 446 bypasses the SC notch filter 434 allowing powerline noise to remain in the reconstructed digitized EEG signal 420 and therefore also in the output 442 of the artifact removal module 110 upon which the calibration is based. This noise indicates a magnitude of the rejection of the second stage amplifier 120 due to the CMR boosting and therefore enables effective calibration of the CMR Boosting Module 104 coefficient a through adjusting the calibration resistor 426 (i.e. proper calibration of the value of the variable resistor selecting from the available resistance range such as 40-256kOhm).

[0237] In measurement mode the SC notch filter bypass switch 446 is disposed in the open position and the mode control switch 442 is toggled to direct the output of the artifact removal module 110 toward the backend 174.

[0238] In some embodiments, the AE 101 includes further signal processing modules such as a feature extraction module 136. In some embodiments, these modules are directed to specific EEG applications. For example, in an EEG system 100 configured to monitor for epilepsy, the AE 101 may include a feature extraction module 136 configured to receive the output of the artifact removal module 110 and extract features predetermined to correspond to epileptic EEG activity. Such signal processing modules could result in significant reduction in the volume of the data to be communicated to the central backend unit 174 (i.e., communicating the processing results rather than raw recordings), hence, proportionally reducing the overall system’s power consumption.

[0239] The AE 101 further includes an AE serial interface 138. The AE serial interface 138 is communicatively connected to a backend serial interface 140 via a data wire. The AE 101 outputs data 146 comprising the processed signal output from the artifact removal module 110 or any following modules across the data wire to the backend 174 and particularly to the serial interface 140 of the backend 174.

[0240] The AE 101 further includes a timing and bias generator 172, comprising timing control module 142 and bias generator module 148. The timing control module 142 is configured to generate digital control clocks for various components of the system such as components requiring digital control signals. Timing control is communicatively connected to the backend serial interface 140 via a global clock wire for receiving a global clock (global elk) signal 144.

[0241] The bias generator module 148 is configured to generate DC voltages for various components of the AE 101. The bias generator module is electrically connected to a ground (GND) 150 and operating voltage source (VDD) 152 of the backend 174. The GND 150 and VDD 152 may be GND 150 and VDD 152 of a battery of the backend 174, such as battery 160.

[0242] In some embodiments, the backend 174 of the EEG system 100 further includes a classifier module 154. The classifier module 154 may be an IC. The classifier module 154 is configured to receive the extracted features of the feature extraction module 136 from the data 146 received at the backend 174 and determine if the features indicate abnormal activity in the brain such as a seizure. The classifier module 154 may include a neuro-inspired multiplier-less boosted support vector machine (SVM) module 156 to perform computation with a very high efficiency, both in terms of silicon area and power consumption, compared to conventional computation schemes, for supporting the classification of the classifier module 154.

[0243] The EEG system 100 further includes a main control module 158. The main control module 158 receives the AE signal data 146 from the serial interface 140. It is expressly contemplated that main control module 158 may receive the AE signal data 146 via intervene modules such as the neuro-inspired multiplier-less boosted SVM module 156. The main control module 158 may provide the AE signal data 146 to a receiver such as a computer, cell phone, orother computing device for further processing or output. The main control module 158 may provide the AE signal data via a wireless board module 162 further described below.

[0244] The main control module 158 may further control the calibration module 436 of any or all ofthe AEs 101 through a program signal 164. The main control module 158 may further provide the serial interface 140 with a global clock signal for providing the global clock signal 144 to the timing control module 142 of any or all or the AEs 101.

[0245] The EEG system 100 may further include a wireless board module 162. The wireless board module 162 receives the AE signal data from the main control module 158 and communicates the AE signal data to a receiver 166 such as via Bluetooth or Bluetooth low energy (BLE). The communication may be set up and controlled by a low power field programable gate array (LP-FPGA) 168 of the wireless board module 162.

[0246] Referring to Figure 7, shown therein are charts of measurement results showing performance of an AE 101 , according to an embodiment. The charts indicate the efficacy of the AE 101 in DR boosting, CMR boosting, energy efficiency, and artifact detection and removal.

[0247] Referring to Figure 8, shown there is a comparison of embodiments of various existing wearable EEG systems 100 (1 through 4) to an embodiment system 0 of the present disclosure. System 1 is an EEG recording system with active electrodes. System 1 includes ETI to measure electrode impedance. In addition to other differences, however, processing based on this impedance is applied directly at the backed rather than via the artifact estimation at the AE 101 of the present disclosure, described herein. System 2 is an EEG recording system with active digital electrodes and ETI. However, among other differences, the processing based on the ETI is applied directly at the backend 174 rather than via the artifact estimation at the AE 101 of the present disclosure, described herein. System 3 is an EEG recording system that employs frequency modulated (FM)-ADC. While system 3 is resilient to the motion effects, i.e., has no means for artifact removal, the high working frequency of the frequency modulation requires a high amount of power in each channel. This increases the power consumption by a factor of 13.7 over system 0. System 4 is an EEG recording system with removal of DC offset as its only strategy against motion artifacts.

[0248] Referring to Figures 9A through 9C, shown therein are schematics and block diagrams of various existing EEG recording systems indicating performance areas addressed by the present disclosure, according to various embodiments. Figure 9A shows an EEG system 900a according to an embodiment. The EEG system 900a comprises a plurality of passive electrodes 902a configured to provide an obtained signal to a central backend 904a. The passive electrodes 902a provide the obtained signal to the central backend 904a via data wires 906a. The central backend 904a comprises a plurality of amplifiers 908a configured to receive and amplify the obtained signal. The central backend 904a further comprises a plurality of ADC modules 910aconfigured to digitize the obtained and amplified signal for processing by a digital signal processor (DSP) 912a. The DSP 912a may include artifact and noise removal. In such embodiment, the electrodes 902a are susceptible to non-neurological inputs both at the electrode and in transmission over the wires 906a, particularly due to the weak unamplified signals being transmitted. These non-neurological inputs will be amplified at the backend 904a along with neurological signals, negatively affecting the quality (i.e., signal-to-noise ratio) and reliability of the signal.

[0249] Figure 9B shows an EEG system 900b according to another embodiment. The EEG system 900b comprises a plurality of active electrodes 914b, each active electrode 914b comprising a passive electrodes 902b configured to obtain a signal, and further comprising an amplifier 908b configured to amplify the obtained signal. The active electrodes 914b are configured to provide the obtained and amplified signal to a central backend 904b. The central backend 904b comprises a plurality of ADC modules 910b and a DSP 912b that operate substantially similar to the ADC modules 910a and the DSP 912a, respectively. In such embodiment, the DSP 912b performs signal processing to remove artifacts or suppress interferences at the backend 904b once the obtained signal has been transmitted to the backend 904b. In such embodiment, interference attributable to transmission of the obtained signal to the backend 904b, such as from the wires 906b, in signals from the AEs 914b are suppressed proportional to the amplification gain due to the discrepancy in the amplitude of the obtained signal relative to the transmission aspects. However, this amplification also amplifies non- neurological components of the obtained signal such as motion artifacts.

[0250] Figure 9C shows an EEG system 900c according to another embodiment. The EEG system 900c comprises a plurality of active electrodes 914c. The active electrodes 914c each comprise a passive electrode 902c, an amplifier 908c, an ADC module 910c, and a serial interface (SI) module 914c. The passive electrode 902c, the amplifier 914c, and the ADC module 910c operate substantially similar to the passive electrode 902b, the amplifier 914b, and the ADC module 910b, respectively. The SI module 914c is configured to serialize the obtained signal from each active electrode 914c and provide the serialized signal to the central backend 906c via a wire 906c of each active electrode 914c. In such embodiment, the obtained signal is digitized and serialized at the active electrode 914c. Accordingly, non-neurological aspects of the obtained signal are digitized. This maintains the CMR efficacy difficulties, to increased data transmission and filtering range and capacity requirements, and increased power consumption. Furthermore, the presence of non-neurological components in the data limit the scalability due to data capacity concerns.

[0251] Referring to Figure 10, shown therein is a chart illustrating power consumption breakdown of existing EEG recording systems, according to an embodiment. The breakdown clearly shows the importance and impact of improving the energy efficiency of the analog front-end (i.e., the AEs) and the AE-to-backend communication as the two most power consumer modules. The above described is directed to improving energy efficiency of these aspects.

[0252] Referring to Figures 1 1A and 1 1 B, shown therein are annotated block diagrams of CMR improvement in a centralized EEG recording system through analog and digital differentiation, respectively. Like numerals denote like references with respect to Figures 9A-9C.

[0253] Referring to Figure 12, shown therein is an annotated block diagram of centralized backend CMR improvement according to an embodiment. Figure 12 as compared with Figures 6A through 6C illustrating CMR at the AE, illustrates that during amplification of the obtained signal (VEEG-i+Vcivi), centralized CMR results in amplification of the Vcm component of the obtained signal along with the neurological component (i.e., VEEG- , which is not the case in the presented CMR at the AE.

[0254] Referring to Figure 13, shown there is a flow diagram of a method 1300 of obtaining a neurological signal from a subject. The method 1300 may be performed by the system 100 of Figure 1.

[0255] At 1302, the method 1300 includes obtaining, by a first active electrode, an obtained signal comprising a neurological signal of a subject. The first active electrode, such as the AE 101 , is configured to be disposed of on the head of the subject. The first active electrode is further configured to be communicatively connected to one or more additional AEs 101 and a backend.

[0256] At 1304, the method 1300 includes generating a replica artifact signal based on the application of electrode tissue impedance (ETI) coefficients to the obtained signal. The replica artifact signal is generated by the ETI measurement module 401 .

[0257] At 1306, the method 1300 includes generating an alpha Vcm signal based on a calibration variable resistor. The alpha Vcm signal is generated by the CM module 1 14 based on the calibration variable resistor of the CMR boosting module 424.

[0258] At 1308, the method 1300 includes generating an amplified alpha Vcm signal based on the alpha Vcm signal. The amplified alpha Vcm signal is generated by the second stage amplifier 120.

[0259] At 1310, the method 1300 includes amplifying and combining the amplified alpha Vcm signal and a second stage input signal to generate an amplified and common-mode-rejection (CMR)-boosted signal, The amplified and CMR-boosted signal is generated by the second stage amplifier 120.

[0260] At 1312, the method 1300 includes subtracting the replica artifact signal from the amplified and CMR-boosted signal to generate an AE data signal. The AE data signal is generated by the artifact removal module 1 10.

[0261] At 1314, the method 1300 includes outputting the AE data signal to the backend. The AE data signal is output by the artifact removal module 110.

[0262] At 1316, the method 1300 includes determining a correlation result based on the AE data signal. The correlation result is determined by the calibration module 436.

[0263] At 1318, the method 1300 includes adjusting the ETI coefficients based on the correlation result to obtain updated ETI coefficients. The updated ETI coefficients are obtained by the calibration module 436.

[0264] At 1320, the method 1300 includes providing the updated ETI coefficients. The updated ETI coefficients are provided to the ETI measurement module 401 .

[0265] Referring to Figure 14, shown there is a flow diagram of a method 1400 of obtaining a neurological signal from a subject, according to an embodiment. The method 1400 may be performed by the system 100 of Figure 1 .

[0266] At 1402, the method 1400 includes obtaining, by a first active electrode, an obtained signal comprising a neurological signal of a subject. The first active electrode, such as the AE 101 , is configured to be disposed of on the head of the subject. The first active electrode is further configured to be communicatively connected to one or more additional AEs 101 and a backend.

[0267] At 1404, the method 1400 includes generating a replica artifact signal based on the application of electrode tissue impedance (ETI) coefficients to the obtained signal. The replica artifact signal is generated by the ETI measurement module 401 .

[0268] At 1406, the method 1400 includes amplifying the obtained signal to output an amplified and common-mode-rejection (CMR)-boosted signal. The amplified and CMR-boosted signal is generated by the second stage amplifier 120.

[0269] At 1408, the method 1400 includes subtracting the replica artifact signal from the amplified and CMR-boosted signal to generate an AE data signal. The AE data signal is generated by the artifact removal module 110.

[0270] At 1410, the method 1400 includes outputting the AE data signal to the backend. The AE data signal is output by the artifact removal module 110.

[0271] At 1412, the method 1400 includes determining a correlation result based on the AE data signal. The correlation result is determined by the calibration module 436.

[0272] At 1414, the method 1400 includes adjusting the ETI coefficients based on the correlation result to obtain updated ETI coefficients. The updated ETI coefficients are obtained by the calibration module 436.

[0273] At 1416, the method 1400 includes providing the updated ETI coefficients. The updated ETI coefficients are provided to the ETI measurement module 401 .

[0274] Referring to Figure 15, shown there is a flow diagram of a method 1500 of obtaining a neurological signal from a subject, according to an embodiment. The method 1500 may be performed by the system 100 of Figure 1 .

[0275] At 1502, the method 1500 includes obtaining, by a first active electrode, an obtained signal comprising a neurological signal of a subject. The first active electrode, such as the AE 101 , is configured to be disposed of on the head of the subject. The first active electrode is further configured to be communicatively connected to one or more additional AEs 101 and a backend.

[0276] At 1504, the method 1500 includes generating an alpha Vcm signal based on a calibration variable resistor. The alpha Vcm signal is generated by the second stage amplifier 120 based on the calibration resistor 426.

[0277] At 1506, the method 1500 includes generating an amplified alpha Vcm signal based on an alpha Vcm signal. The amplified alpha Vcm signal is generated by the second stage amplifier 120.

[0278] At 1508, the method 1500 includes amplifying and combining the amplified alpha Vcm signal and a second stage input signal to generate an AE data signal. The AE data signal is generated by the second stage amplifier 120.

[0279] At 1510, the method 1500 includes outputting the AE data signal to the backend. The AE data signal is output by the artifact removal module 110.

[0280] At 1512, the method 1500 includes determining a correlation result based on the AE data signal. The correlation result is determined by the calibration module 436.

[0281] At 1514, the method 1500 includes calibrating the calibration variable resistor based on the correlation result. The calibration variable resistor is calibrated by the calibration module 436.

[0282] While the above description provides examples of one or more apparatus, methods, or systems, it will be appreciated that other apparatus, methods, or systems may be within the scope of the claims as interpreted by one of skill in the art.

Claims

Claims:1 . A first active electrode (AE) for obtaining a neurological signal of a subject, the first active electrode configured to be disposed of on the head of the subject and communicatively connected to one or more of a second active electrode and a backend, the first active electrode comprising: a conductive element mounted to an AE board and disposed in contact with a skin of the subject for obtaining an obtained signal comprising neurological data; an electrode tissue impedance (ETI) module configured to receive the obtained signal from the conductive element and generate a replica artifact signal based on the application of ETI coefficients to the obtained signal; a second stage amplifier configured to: receive an alpha Vcm signal based on a Vcm signal from a common-mode (CM) board, wherein the alpha Vcm signal is configured such that, when passed through the second stage amplifier to generate an amplified alpha Vcm, the amplified alpha Vcm is substantially equivalent to the Vcm signal amplified by a gain of (1+alpha)*G; receive a second stage input signal based on the obtained signal, wherein the second stage input signal, when passed through the second stage amplifier, is substantially amplified by a gain -G; and amplify and combine the amplified alpha Vcm and the second stage input signal to generate an amplified and common-mode-rejection (CMR)-boosted signal; a CMR boosting module configured to receive the Vcm signal from the CM board and obtain the alpha Vcm signal via a calibration variable resistor, wherein calibrating the calibration variable resistor calibrates an alpha of the CMR boosting module, wherein the alpha is an AE-specific attenuation coefficient, and wherein the alpha corresponds to a maximum suppression of the Vcm at calibration; an artifact removal module configured to: receive the amplified and CMR-boosted signal output from the second stage amplifier; receive the replica artifact signal from the ETI module; andsubtract the replica artifact signal from the amplified and CMR-boosted signal and output an AE data signal to the backend; a mode control switch configured to toggle between a measurement mode configuration and a calibration mode configuration, wherein in the calibration mode configuration the AE data signal is diverted to a calibration module; the calibration module configured to, when communicatively connected to the artifact removal module by the mode control switch: receive the AE data signal; determine a correlation result calculated based on the AE data signal; adjust the ETI coefficients based on the correlation result to obtain updated ETI coefficients; provide the updated ETI coefficients to the ETI module; and calibrate the calibration variable resistor of the CMR boosting module based on the correlation result.

2. The first AE of claim 1 , wherein the conductive element is a passive electrode.

3. The first AE of claim 1 , wherein the conductive element is a comb electrode.

4. The first AE of claim 1 , wherein the ETI module comprises a current digital to analogue (I-DAC) converter configured to inject current pulses to the skin of the subject.

5. The first AE of claim 4, wherein the l-DAC converter is further configured to correct a DC level at the conductive element.

6. The first AE of claim 1 , wherein the first AE further comprises a DCincorrection module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

7. The first AE of claim 1 , wherein the ETI module further comprises a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

8. The first AE of claim 7, wherein the SAR ADC is an 8-bit SAR ADC.

9. The first AE of claim 1 , wherein the ETI module further comprises an artifact estimation module configured to generate the replica artifact signal.

10. The first AE of claim 1 , wherein the first AE further comprises a first stage amplifier configured to generate the second stage input signal based on the obtained signal, the Vcm signal, and a gain G1.

11. The first AE of claim 1 , wherein the first AE further comprises a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR boosted signal within a range.

12. The first AE of claim 1 , wherein the first AE further comprises a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

13. The first AE of claim 12, wherein the SC notch filter is a band stop filter.

14. The first AE of claim 1 , wherein the first AE further comprises a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

15. The first AE of claim 14, wherein the first AE further comprises a digital reconstruction module configured to rebuild the digitized signal.

16. The first AE of claim 1 , wherein the calibration module is further configured to calibrate the artifact estimation module.

17. The first AE of claim 1 , wherein in the calibration mode, the calibration module is configured to calibrate based on a calibration interval.

18. The first AE of claim 17, wherein the calibration interval is periodic at a preset interval.

19. The first AE of claim 17, wherein the calibration interval is based on an activity level of the subject.

20. The first AE of claim 17, wherein the calibration interval is based on a placement of the AE.21 . The first AE of claim 17, wherein the calibration mode and the calibration interval are set via a program.

22. The first AE of claim 1 , wherein the calibration module comprises a gain and delay control module configured to generate the updated ETI coefficients.

23. The first AE of claim 1 , wherein the calibration module comprises a correlation module configured to generate the correlation result.

24. The first AE of claim 1 , wherein the first AE comprises a feature extraction module configured to generate extracted features of the AE data signal.

25. The first AE of claim 24, wherein the first AE comprises a classifier module configured to process the extracted features.

26. The first AE of claim 25, wherein the classifier module comprises a support vector machine (SVM).

27. A first active electrode (AE) for obtaining a neurological signal of a subject, the first active electrode configured to be disposed of on the head of the subject and communicatively connected to one or more of a second active electrode and a backend, the first active electrode comprising: a conductive element mounted to an AE board and disposed in contact with a skin of the subject for obtaining an obtained signal comprising neurological data; an electrode tissue impedance (ETI) module configured to receive the obtained signal from the conductive element and generate a replica artifact signal based on the application of ETI coefficients to the obtained signal; a second stage amplifier configured to amplify the obtained signal and output an amplified and common-mode-rejection (CMR)-boosted signal; an artifact removal module configured to: receive the amplified and CMR-boosted signal from the second stage amplifier; receive the replica artifact signal from the ETI module; and subtract the replica artifact signal from the amplified and CMR-boosted signal and output an AE data signal to the backend; a mode control switch configured to toggle between a measurement mode configuration and a calibration mode configuration, wherein in the calibration mode configuration the AE data signal is diverted to a calibration module; the calibration module configured to, when communicatively connected to the artifact removal module by the mode control switch:receive the AE data signal; determine a correlation result calculated based on the AE data signal; adjust the ETI coefficients based on the correlation result to obtain updated ETI coefficients; and provide the updated ETI coefficients to the ETI measurement module.

28. The first AE of claim 27, wherein the conductive element is a passive electrode.

29. The first AE of claim 27, wherein the conductive element is a comb electrode.

30. The first AE of claim 27, wherein the ETI module comprises a current digital to analogue(l-DAC) converter configured to inject current pulses to the skin of the subject.31 . The first AE of claim 30, wherein the l-DAC converter is further configured to correct a DC level at the conductive element.

32. The first AE of claim 27, wherein the first AE further comprises a DCincorrection module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

33. The first AE of claim 27, wherein the ETI module further comprises a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

34. The first AE of claim 33, wherein the SAR ADC is an 8-bit SAR ADC.

35. The first AE of claim 27, wherein the ETI module further comprises an artifact estimation module configured to generate the replica artifact signal.

36. The first AE of claim 27, wherein the first AE further comprises a first stage amplifier configured to generate the second stage input signal based on the obtained signal, the Vcm signal, and a gain G1.

37. The first AE of claim 27, wherein the first AE further comprises a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR boosted signal within a range.

38. The first AE of claim 27, wherein the first AE further comprises a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

39. The first AE of claim 38, wherein the SC notch filter is a band stop filter.

40. The first AE of claim 27, wherein the first AE further comprises a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

41. The first AE of claim 40, wherein the first AE further comprises a digital reconstruction module configured to rebuild the digitized signal.

42. The first AE of claim 27, wherein the calibration module is further configured to calibrate the artifact estimation module.

43. The first AE of claim 27, wherein in the calibration mode, the calibration module is configured to calibrate based on a calibration interval.

44. The first AE of claim 43, wherein the calibration interval is periodic at a preset interval.

45. The first AE of claim 43, wherein the calibration interval is based on an activity level of the subject.

46. The first AE of claim 43, wherein the calibration interval is based on a placement of the AE.

47. The first AE of claim 43, wherein the calibration mode and the calibration interval are set via a program.

48. The first AE of claim 27, wherein the calibration module comprises a gain and delay control module configured to generate the updated ETI coefficients.

49. The first AE of claim 27, wherein the calibration module comprises a correlation module configured to generate the correlation result.

50. The first AE of claim 27, wherein the first AE comprises a feature extraction module configured to generate extracted features of the AE data signal.51 . The first AE of claim 50, wherein the first AE comprises a classifier module configured to process the extracted features.

52. The first AE of claim 51 , wherein the classifier module comprises a support vector machine (SVM).

53. A first active electrode (AE) for obtaining a neurological signal of a subject, the first active electrode configured to be disposed of on the head of the subject and communicatively connected to one or more of a second active electrode and a backend, the first active electrode comprising: a conductive element mounted to an AE board and disposed in contact with a skin of the subject for obtaining an obtained signal comprising neurological data; a second stage amplifier configured to: receive an alpha Vcm signal based on a Vcm signal from a common-mode (CM) board, wherein the alpha Vcm signal is configured such that, when passed through the second stage amplifier to generate an amplified alpha Vcm, the amplified alpha Vcm is substantially equivalent to the Vcm signal amplified by a gain of 1+alpha*G; receive a second stage input signal based on the obtained signal wherein the second stage input signal when passed through the second stage amplifier is substantially amplified by a gain -G; amplify and combine the amplified alpha Vcm signal and the second stage input signal to obtain an AE data signal; and output the AE data signal to the backend; a common-mode-rejection (CMR)-boosting module configured to receive the Vcm signal from the CM board and obtain the alpha Vcm signal via a calibration variable resistor, wherein calibrating the calibration variable resistor calibrates an alpha of the CMR- boosting module, wherein the alpha is an AE-specific attenuation coefficient, and wherein the alpha corresponds to a maximum suppression of the Vcm at calibration; a mode control switch configured to toggle between a measurement mode configuration and a calibration mode configuration, wherein in the calibration mode configuration the AE data signal is diverted to a calibration module; the calibration module configured to, when communicatively connected to the second stage amplifier by the mode control switch: receive the AE data signal;determine a correlation result calculated based on the AE data signal; and calibrate the calibration variable resistor of the CMR-boosting module based on the correlation result.

54. The first AE of claim 53, wherein the conductive element is a passive electrode.

55. The first AE of claim 53, wherein the conductive element is a comb electrode.

56. The first AE of claim 53, wherein the ETI module comprises a current digital to analogue(l-DAC) converter configured to inject current pulses to the skin of the subject.

57. The first AE of claim 56, wherein the l-DAC converter is further configured to correct a DC level at the conductive element.

58. The first AE of claim 53, wherein the first AE further comprises a DCincorrection module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

59. The first AE of claim 53, wherein the ETI module further comprises a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

60. The first AE of claim 59, wherein the SAR ADC is an 8-bit SAR ADC.61 . The first AE of claim 53, wherein the ETI module further comprises an artifact estimation module configured to generate the replica artifact signal.

62. The first AE of claim 53, wherein the first AE further comprises a first stage amplifier configured to generate the second stage input signal based on the obtained signal, the Vcm signal, and a gain G1.

63. The first AE of claim 53, wherein the first AE further comprises a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR boosted signal within a range.

64. The first AE of claim 53, wherein the first AE further comprises a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

65. The first AE of claim 64, wherein the SC notch filter is a band stop filter.

66. The first AE of claim 53, wherein the first AE further comprises a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

67. The first AE of claim 66, wherein the first AE further comprises a digital reconstruction module configured to rebuild the digitized signal.

68. The first AE of claim 53, wherein the calibration module is further configured to calibrate the artifact estimation module.

69. The first AE of claim 53, wherein in the calibration mode, the calibration module is configured to calibrate based on a calibration interval.

70. The first AE of claim 69, wherein the calibration interval is periodic at a preset interval.71 . The first AE of claim 69, wherein the calibration interval is based on an activity level of the subject.

72. The first AE of claim 69, wherein the calibration interval is based on a placement of the AE.

73. The first AE of claim 69, wherein the calibration mode and the calibration interval are set via a program.

74. The first AE of claim 53, wherein the calibration module comprises a gain and delay control module configured to generate the updated ETI coefficients.

75. The first AE of claim 53, wherein the calibration module comprises a correlation module configured to generate the correlation result.

76. The first AE of claim 53, wherein the first AE comprises a feature extraction module configured to generate extracted features of the AE data signal.

77. The first AE of claim 76, wherein the first AE comprises a classifier module configured to process the extracted features.

78. The first AE of claim 77, wherein the classifier module comprises a support vector machine (SVM).

79. A method of obtaining a neurological signal of a subject, the method comprising: obtaining, by a first active electrode (AE), an obtained signal comprising the neurological signal, wherein the first active electrode is configured to be disposed of on a head of asubject, and wherein the first active electrode is communicatively connected to one or more of a second active electrode and a backend; generating a replica artifact signal based on the application of electrode tissue impedance (ETI) coefficients to the obtained signal; generating an alpha Vcm signal based on a calibration variable resistor; generating an amplified alpha Vcm signal based on the alpha Vcm signal; amplifying and combining the amplified alpha Vcm signal and a second stage input signal to generate an amplified and common-mode-rejection (CMR)-boosted signal; subtracting the replica artifact signal from the amplified and CMR-boosted signal to generate an AE data signal; outputting the AE data signal to the backend; determining a correlation result based on the AE data signal; adjusting the ETI coefficients based on the correlation result to obtain updated ETI coefficients; and providing the updated ETI coefficients.

80. The method of claim 79, wherein the first AE includes a conductive element.81 . The method of claim 80, wherein the conductive element includes a passive electrode.

82. The method of claim 80, wherein the conductive element includes a comb electrode.

83. The method of claim 80, wherein the first AE includes a current digital to analogue (l-DAC) converter configured to inject current pulses to a skin of the subject.

84. The method of claim 83, wherein the l-DAC converter is further configured to correct a DC level at the conductive element.

85. The method of claim 84, wherein the first AE further comprises a DCincorrection module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

86. The method of claim 80, wherein the first AE comprises an ETI module, wherein the ETI module further comprises a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

87. The method of claim 86, wherein the SAR ADC is an 8-bit SAR ADC.

88. The method of claim 86, wherein the ETI module further comprises an artifact estimation module configured to generate the replica artifact signal.

89. The method of claim 80, wherein the first AE further comprises a first stage amplifier configured to generate the second stage input signal based on the obtained signal, the Vcm signal, and a gain G1.

90. The method of claim 80, wherein the first AE further comprises a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR boosted signal within a range.91 . The method of claim 80, wherein the first AE further comprises a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

92. The method of claim 91 , wherein the SC notch filter is a band stop filter.

93. The method of claim 80, wherein the first AE further comprises a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

94. The method of claim 93, wherein the first AE further comprises a digital reconstruction module configured to rebuild the digitized signal.

95. The method of claim 88, wherein the first AE further comprises a calibration module configured in a calibration mode, wherein the calibration module is further configured to calibrate the artifact estimation module.

96. The method of claim 95, wherein in the calibration mode, the calibration module is configured to calibrate based on a calibration interval.

97. The method of claim 96, wherein the calibration interval is periodic at a preset interval.

98. The method of claim 96, wherein the calibration interval is based on an activity level of the subject.

99. The method of claim 96, wherein the calibration interval is based on a placement of the AE.

100. The method of claim 96, wherein the calibration mode and the calibration interval are set via a program.

101. The method of claim 95, wherein the calibration module comprises a gain and delay control module configured to generate the updated ETI coefficients.

102. The method of claim 95, wherein the calibration module comprises a correlation module configured to generate the correlation result.

103. The method of claim 80, wherein the first AE comprises a feature extraction module configured to generate extracted features of the AE data signal.

104. The method of claim 103, wherein the first AE comprises a classifier module configured to process the extracted features.

105. The method of claim 104, wherein the classifier module comprises a support vector machine (SVM).

106. A method of obtaining a neurological signal of a subject, the method comprising: obtaining, by a first active electrode (AE), an obtained signal comprising the neurological signal, wherein the first active electrode is configured to be disposed of on the head of the subject, and wherein the first active electrode is communicatively connected to one or more of a second active electrode and a backend; generating a replica artifact signal based on the application of electrode tissue impedance (ETI) coefficients to the obtained signal; amplifying the obtained signal to output an amplified and common-mode-rejection (CMR)- boosted signal; subtracting the replica artifact signal from the amplified and CMR-boosted signal to generate an AE data signal; outputting the AE data signal to the backend; determining a correlation result based on the AE data signal; adjusting the ETI coefficients based on the correlation result to obtain updated ETI coefficients; andproviding the updated ETI coefficients;107. The method of claim 106, wherein the first AE includes a conductive element.

108. The method of claim 107, wherein the conductive element includes a passive electrode.

109. The method of claim 107, wherein the conductive element includes a comb electrode.

110. The method of claim 107, wherein the first AE includes a current digital to analogue (I-DAC) converter configured to inject current pulses to a skin of the subject.

111. The method of claim 110, wherein the l-DAC converter is further configured to correct a DC level at the conductive element.

112. The method of claim 111 , wherein the first AE further comprises a DCincorrection module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

113. The method of claim 107, wherein the first AE comprises an ETI module, wherein the ETI module further comprises a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

114. The method of claim 113, wherein the SAR ADC is an 8-bit SAR ADC.

115. The method of claim 107, wherein the ETI module further comprises an artifact estimation module configured to generate the replica artifact signal.

116. The method of claim 107, wherein the first AE further comprises a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR boosted signal within a range.

117. The method of claim 107, wherein the first AE further comprises a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

118. The method of claim 117, wherein the SC notch filter is a band stop filter.

119. The method of claim 107, wherein the first AE further comprises a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

120. The method of claim 119, wherein the first AE further comprises a digital reconstruction module configured to rebuild the digitized signal.

121. The method of claim 115, wherein the first AE further comprises a calibration module configured in a calibration mode, wherein the calibration module is further configured to calibrate the artifact estimation module.

122. The method of claim 121 , wherein in the calibration mode, the calibration module is configured to calibrate based on a calibration interval.

123. The method of claim 122, wherein the calibration interval is periodic at a preset interval.

124. The method of claim 122, wherein the calibration interval is based on an activity level of the subject.

125. The method of claim 122, wherein the calibration interval is based on a placement of the AE.

126. The method of claim 122, wherein the calibration mode and the calibration interval are set via a program.

127. The method of claim 121 , wherein the calibration module comprises a gain and delay control module configured to generate the updated ETI coefficients.

128. The method of claim 121 , wherein the calibration module comprises a correlation module configured to generate the correlation result.

129. The method of claim 107, wherein the first AE comprises a feature extraction module configured to generate extracted features of the AE data signal.

130. The method of claim 129, wherein the first AE comprises a classifier module configured to process the extracted features.

131. The method of claim 130, wherein the classifier module comprises a support vector machine (SVM).

132. A method of obtaining a neurological signal of a subject, the method comprising: obtaining, by a first active electrode (AE), an obtained signal comprising the neurological signal, wherein the first active electrode is configured to be disposed of on the head of the subject, and wherein the first active electrode is communicatively connected to one or more of a second active electrode and a backend;generating an alpha Vcm signal based on a calibration variable resistor; generating an amplified alpha Vcm signal based on an alpha Vcm signal; amplifying and combining the amplified alpha Vcm signal and a second stage input signal to generate an AE data signal; outputting the AE data signal to the backend; determining a correlation result based on the AE data signal; and calibrating the calibration variable resistor based on the correlation result;133. The method of claim 132, wherein the first AE includes a conductive element.

134. The method of claim 133, wherein the conductive element includes a passive electrode.

135. The method of claim 133, wherein the conductive element includes a comb electrode.

136. The method of claim 133, wherein the first AE includes a current digital to analogue (I-DAC) converter configured to inject current pulses to a skin of the subject.

137. The method of claim 136, wherein the l-DAC converter is further configured to correct a DC level at the conductive element.

138. The method of claim 137, wherein the first AE further comprises a DCincorrection module configured to measure a DC voltage at the conductive element, compare the DC voltage to an upper voltage threshold and lower voltage threshold to obtain a compared voltage, and control the l-DAC converter based on the compared voltage.

139. The method of claim 133, wherein the first AE comprises an ETI module, wherein the ETI module further comprises a successive approximate register (SAR) analogue to digital converter (ADC) configured to digitize the obtained signal.

140. The method of claim 139, wherein the SAR ADC is an 8-bit SAR ADC.

141. The method of claim 139, wherein the ETI module further comprises an artifact estimation module configured to generate the replica artifact signal.

142. The method of claim 133, wherein the first AE further comprises a dynamic range (DR) boosting module configured to maintain a magnitude of the amplified and CMR-boosted signal within a range.

143. The method of claim 133, wherein the first AE further comprises a switched-capacitor (SC) notch filter configured to remove power-line noise from the amplified and CMR boosted signal.

144. The method of claim 143, wherein the SC notch filter is a band stop filter.

145. The method of claim 133, wherein the first AE further comprises a noise shaping (NS) SAR ADC configured to digitize the amplified and CMR boosted signal and generate a digitized signal.

146. The method of claim 145, wherein the first AE further comprises a digital reconstruction module configured to rebuild the digitized signal.

147. The method of claim 141 , wherein the first AE further comprises a calibration module configured in a calibration mode, wherein the calibration module is further configured to calibrate the artifact estimation module.

148. The method of claim 147, wherein in the calibration mode, the calibration module is configured to calibrate based on a calibration interval.

149. The method of claim 148, wherein the calibration interval is periodic at a preset interval.

150. The method of claim 148, wherein the calibration interval is based on an activity level of the subject.

151. The method of claim 148, wherein the calibration interval is based on a placement of the AE.

152. The method of claim 148, wherein the calibration mode and the calibration interval are set via a program.

153. The method of claim 147, wherein the calibration module comprises a gain and delay control module configured to generate the updated ETI coefficients.

154. The method of claim 147, wherein the calibration module comprises a correlation module configured to generate the correlation result.

155. The method of claim 133, wherein the first AE comprises a feature extraction module configured to generate extracted features of the AE data signal.

156. The method of claim 155, wherein the first AE comprises a classifier module configured to process the extracted features.

157. The method of claim 156, wherein the classifier module comprises a support vector machine (SVM).

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