Patent Application
20090247894
The present invention generally relates to a medical apparatus, and more particularly, to a method and system for acquiring and processing brain electrical signals using an integrated, portable device.
Certain neurological disorders or conditions can be diagnosed by analyzing electrical signals from the brain using non-invasive tools, such as electroencephalography (EEG). A traditional brain wave recording system measures electrical potentials between electrodes placed on the scalp and generates a record of the electrical activity of the brain. Typically, such electrical activity may be shown as a set of analog waveforms or signals that must be interpreted by skilled neurophysiologists. This process can be time-consuming, expensive, technically demanding and subject to human error. Further, because results are not rapidly available, the traditional systems for analyzing brain electrical activity are not well suited for use in emergency rooms or other point-of-care settings.
Portable, easy-to-administer devices for recording and analyzing brain electrical activity would be beneficial in a number of clinical settings. For example, such devices would allow emergency response personnel to quickly evaluate patients with potential neurologic injury to allow rapid and proper initiation of therapy. For example, patients may present with a similar set of signs and symptoms when experiencing ischemic or hemorrhagic stoke. However, the proper therapies for ischemic and hemorrhagic disorders are vastly different, and improper or untimely differentiation between the two can be life-threatening. Therefore, a portable, rapidly-administered system for identifying these or many other neurologic conditions would be invaluable for rapid, on-site neurological evaluation.
Presently, portable brain wave recording systems may measure a subject's brain electrical impulses and convert them into digital data for transmission and downstream analysis. Such systems may additionally perform other steps in the external signal processing module, including further processing and analyzing the data, diagnosing the subject's condition, and displaying the resulting diagnosis. Results are typically displayed on a hand-held control distant from the patient. An exemplary system is disclosed in U.S. Pat. No. 6,052,619 and related U.S. application Ser. No. 10/045,799, both of which are incorporated herein by reference. Such a system generally features a headband with an array of electrodes configured to detect, amplify, and broadcast data, via radio or cellular phone, to a local receiver for analysis. Such a system may also record evoked potentials following administration of a stimulus. The system processes data using various tools, including traditional Fast Fourier Transform (FFT) analysis and power spectral density (PSD) analysis.
Alternate signal processing tools, such as Harmonic Signal Analysis, have been used advantageously in the analysis of brain electrical activity, and have been successfully applied to neurological evaluation. Such tools and systems are disclosed in U.S. Patent Publication No. 2007/0032737 A1 (application Ser. No. 11/195,001), incorporated herein by reference.
The inventor of the present invention has recognized the need for a portable, easy-to-use, low-cost, low-power system for acquiring and processing brain electrical signals and displaying a diagnosis in real-time. Inefficiencies in existing integrated circuit technologies are prohibitive to creating a single, integrated chip for acquiring and processing analog neuroelectric signals. This is because brain signal acquisition and processing requires very high precision, more power, and more physical space, and therefore, integrated circuits for processing brain electrical signals have not been developed. The current invention presents a novel system for neurological evaluation that integrates signal amplification, analog-to-digital conversion, and digital signal processing on a single, standalone chip, with all the components fabricated on the same die, and running on the same clock, at the same temperature, same parasitic capacitance, and same ground plane, which helps to reduce noise, power dissipation and allows high speed.
The present disclosure provides methods and systems for acquiring, processing, and analyzing brain electrical activity for evaluating the neurophysiological condition of the brain. Methods and systems for improving the acquisition and processing of analog bioelectric signals are disclosed. Advantages of the present invention may include, but are not limited to, reducing the size of the system, improving portability, facilitating integration, enabling high-speed, real-time processing, reducing noise contamination, enabling the acquisition and processing of submicrovolt signals, reducing production costs, and reducing complexity of system deployment.
One embodiment consistent with the principles of the invention is a system for acquiring and processing a subject's brain electrical activity using Bx™ technology. The neurological evaluation system includes at least one electrode, at least one analog amplifier channel, an analog-to-digital converter (ADC), a stimulus generator for eliciting evoked potentials, and a digital signal processor (DSP) to implement harmonic signal analysis-based signal processing. The at least one analog amplifier channel, ADC converter, and the digital signal processor are configured to reside in a single integrated physical circuit. For multi-channel applications, the system also comprises an analog multiplexer, which is included in the single integrated circuit
Other embodiments consistent with the principles of the invention include a method for determining the neurological state of a subject and a system for the same. The method includes the steps of providing an integrated device for measuring and processing brain electrical activity, attaching an electrode array to a patient, activating a stimulus generator, and detecting data relating to the subject's spontaneous brain electrical activity and evoked potentials generated in response to applied stimuli. The integrated device includes an analog module and a DSP module that performs, for example a harmonic signal analysis algorithm, to process the data representative of the acquired brain electrical impulses.
Additional embodiments consistent with the principles of the invention include methods for analyzing data relating to brain electrical signals and evoked potentials, and a system for the same. The method includes the steps of bit-level processing, artifact detecting, feature extracting, classifying, and displaying output.
Additional embodiments consistent with principles of the invention are set forth in the detailed description which follows or may be learned by practice of methods or use of systems or articles of manufacture disclosed herein. It is understood that both the foregoing general description and the following detailed description are exemplary and explanatory only, and are not restrictive of the invention as claimed.
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate several embodiments of the invention and together with the description, serve to explain the principles of the invention. In the drawings:
Reference is now made in detail to exemplary embodiments of the invention, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts.
In the following detailed description, reference is made to the accompanying drawings, which form a part hereof and in which is shown by way of illustration specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable one skilled in the art to practice and use the invention, and it is to be understood that other embodiments may be utilized and that electrical, logical, and structural changes may be made without departing form the spirit and scope of the present invention.
Further, as described in detail below, system 100 can include a number of components. For example, in one embodiment, system 100 can include a single-chip circuit system 200, henceforth referred to as chip 200, as described with respect to
Neurological evaluation system 100 can be a standalone system or can operate in conjunction with a mobile or stationary device to facilitate display or storage of data, and to signal healthcare personnel when therapeutic action is needed, thereby facilitating early recognition of alarm conditions. For example, system 100, operating in conjunction with a mobile or stationary telemetry or monitoring system, as may be available in hospitals, can cause the mobile or stationary system to trigger an alarm and/or notify medical personnel to respond to some neurological conditions. Mobile devices can include, but are not limited to, handheld devices and wireless devices distant from, and in communication with, system 100. Further, stationary devices can include, but are not limited to, desktop computers, printers and other peripherals that display or store the results of the neurological evaluation. The system may communicate wirelessly with the mobile or stationary devices, and in which case, the system 100 may also include a wireless output interface.
Further, system 100 can transmit data to another mobile or stationary device to facilitate more complex data processing or analysis. For example, system 100, operating in conjunction with a desktop computer, can send data to be further processed by the computer. Additionally, system 100 can be configured to interact with a printer or other system to print or store medical records, and therefore, may be configured to automatically generate medical records to be stored or used by attending medical personnel.
Referring again to
In an exemplary embodiment of system 100, output device 110 may be configured to communicate information or test results about patient 10 to other devices or personnel, such as an attending physician, an emergency response or medical technician, a computer, or a server. Information that is conveyed through output device 110 can include a variety of different data types, including, but not limited to, raw data, encoded data, signal waveforms, diagnostic results, intermediate analysis results, alarms, alarm conditions, usage settings, etc. In some exemplary embodiments, output device 110 may receive and display usage setting information, such as the name, age and/or other statistics pertaining to patient 10. Additionally or alternatively, output device 110 may be configured to display brain electrical activity waveforms of patient 10. Subsequently, output device 110 may display an indicator representing the condition of patient 10. This and other embodiments are within the scope of the present invention.
Output device 110 may present results in various forms, including, for example, auditory and visual forms. Visual results may be presented through any suitable visual display, such as a liquid crystal display (LCD) or a touch screen, but it will be understood by one skilled in the art that many other presentation devices exist and may be used in conjunction with embodiments of the present invention. For example, output device 110 may present results through automated speech.
Output device 110 may also be contained within the portion of system 100 that is attached to the forehead of patient 10, thereby allowing the device to be contained in a single unit and allowing medical personnel treating the patient 10 to see the results as they examine the patient or attend to other patient needs. The output device may be a visual display or an LED that lights up when immediate medical attention is required. Alternatively or additionally, output device 110 may be contained in a separate system or housing such as a remote monitor near a nurse's station, and may interface with system 100 wirelessly. In an exemplary embodiment, chip 200 may also contain a wireless power amplifier coupled directly to an antenna to transmit diagnostic results wirelessly to the output device or to a remote data storage system.
As shown, output device 110 can interface with digital signal processor 400. In such embodiments, output device 110 may present diagnostic results produced by processor 400. In other embodiments, output device 110 may alternatively or additionally interface with analog module 300. In such embodiments, output device 110 may display raw or quantized data prior to analysis.
As noted, neurological evaluation system 100 can include a power source 120 to enable the operation of all the components of system 100. Power source 120 can include any voltage or current source, including, but not limited to, a variety of batteries or alternating current sources. In some exemplary embodiments, power source 120 can include a relatively low-power and/or short-life battery selected to minimize size, weight, and/or cost. In some embodiments, power may be transferred to the system wirelessly using electromagnetic coupling with an external source, in which case, the power source 120 may include an antenna to receive RF emissions from the external source and a capacitor circuit to store the received power. The power requirements of system 100 is considerably reduced by including several important components within a single chip 200 and by configuring system 100 to perform custom signal processing.
As shown, power source 120 can reside external to chip 200, and an interface may be provided between power source 120 and electrical components within chip 200. In alternate embodiments, power source 120 may be included in chip 200 and may be directly connected to components within chip 200.
While analysis generally may include the step of acquiring a subject's base brain electrical activity over a period of time, analysis may further include the extraction of evoked potential (EP) signals. EP signals are transient signals that contribute to a subject's overall brain electrical activity. EP signals are generally produced in response to the detection of external stimuli by the brain. In some embodiments, suitable systems can include one or more stimulus generators 130 to produce audio, visual or electrical stimuli that can elicit evoked potentials (EP) to be evaluated by system 100. The administration of stimuli can facilitate production of EP signals and aid in the diagnosis of certain neurological disorders. External stimuli can include auditory, visual, and electrical. Typically, the amplitude of EP signals are approximately one order of magnitude smaller than the base electrical signals.
The stimulus generator may interface with a stimulus output device, such as an audible stimulus output device 30, positioned proximate a patient's ear and configured to produce sounds that can generate EPs. In some embodiments, consistent with features and principles of the present invention, the stimulus generator 130 may also reside within the chip 200.
One subset of EP signals are auditory evoked potential (AEP) signals. AEP signals are elicited by administering auditory stimuli. AEP signals further comprise an auditory brainstem response (ABR), a mid-latency cortical response (MLR), and a slow cortical response. ABR generally occurs during the first 11 ms after the stimulus is administered.
In an exemplary embodiment, neurological evaluation system 100 may utilize the advantages of ABR signals to map specific auditory, neurological and psychiatric dysfunctions. In such an embodiment, stimulus generator 130 can administer auditory stimuli. As noted above, auditory stimuli can be administered by placing an auditory output device 30 in proximity to patient 10 such that the stimuli may be detected by the patient. Auditory stimuli can comprise discrete or continuous sound signals, or a combination of both. Examples of discrete sounds, which can be used with neurological evaluation system 100, include clicks and pulses. In some embodiments, the sounds can be administered as a succession of sounds at varying frequencies.
In an alternate exemplary embodiment, stimulus generator 130 may administer visual stimuli. Visual stimuli may be applied by placing a visual output device in proximity to patient 10, such that the stimuli may be detected by patient 10. Visual stimuli may comprise discrete or continuous visual signals, or a combination of both. Examples of discrete visual signals may include flashes of light and light of varying wavelengths.
As noted above, system 100 can further include electrode array 190, which may be configured to receive signals pertaining to neurological electrical activity so that such signals can be acquired and processed by system 100. Electrode array 190 can comprise any number of electrodes 191-1 . . . , 191-n arranged to facilitate acquisition of data pertaining to brain electrical activity. Many such arrangements exist, wherein the number of electrodes may range from about one to about twenty or more electrodes. Electrodes 191 can be positioned in a variety of locations on or near the head, including, but not limited to, the forehead, the scalp, the temples near the ears, and on the neck or upper back.
An example of such an arrangement known in the art is typically referred to as the standard 10/20 system. In the standard 10/20 system, raw data is collected from nineteen regions of the head using twenty electrodes positioned along the forehead and scalp of patient 10.
Another example of such an arrangement includes a configuration of nine electrodes covering the areas around the right mastoid, far right of the forehead, near right of the forehead, center top of the forehead, near left of the forehead, far left of the forehead, left mastoid, and left shoulder of patient 10. Such an arrangement is disclosed in U.S. Pub. No. 2007/0032737 A1, incorporated herein by reference in its entirety.
In some exemplary embodiments of electrode array 190, electrodes 191-1, . . . , 191-n are positioned primarily around the forehead. For example, electrode array 190 may include nine electrodes 191-1, . . . , 191-n positioned across the forehead and/or near the ears. It will be understood by one skilled in the art that alternative embodiments are within the scope of the disclosure and are consistent with features and principles of the present invention.
In some exemplary embodiments, electrode array 190, including electrodes 191-1, . . . , 191-n, may be contained within an attachable subset of system 100. For example, each of electrodes 191 can be individually or collectively connected to chip 200 to interface with components contained therein. Further, electrode array 190 may be configured to include hooks or nontoxic adhesive or conducting gel to enable noninvasive and reliable attachment to patient 10.
In some exemplary embodiments, analog module 300 can interface with digital signal processor 400 through an interface, such as a multiplexer (MUX). Further, a suitable interface may also comprise an analog-to-digital converter (ADC), such as a 1-bit sigma-delta analog-to-digital converter, to digitize the continuous analog signals for processing. Such configurations are described in detail with reference to
In some exemplary embodiments, system processes 320 may include checking an impedance 326 by feeding a signal back into each electrode 328. Checking an impedance 326 may function to characterize the effectiveness of connection of a surface electrode to a subject. This would further enable the ability to test applied electrodes at patient site before connection to the system 100, and measure the electrode impedances continuously in real-time while a patient is being monitored. In some embodiments, the electrodes 191-0 . . . 191-n may further contain LEDs, which turn on when its impedance is higher than the preselected value. In another embodiment, the impedance of the applied electrodes may be displayed on the output device 110 connected to the digital signal processor 400.
In an exemplary embodiment, digital signal processor 400 may be configured to perform a harmonic signal analysis algorithm 470. Harmonic signal analysis algorithm 470 may comprise at least one of wavelet transform methods, such as wavelet packets, discrete wavelet transform, or diffusion wavelet transform. Wavelet processing methods are disclosed in U.S. Pat. No. 7,054,454, which is assigned to Everest Biomedical Instruments Company and is incorporated in its entirety herein by reference. The digital signal processor 400 may also be configured to perform fractal analysis and multiscale harmonic analysis.
In one exemplary embodiment, the digital signal processor 400 may include a plurality of multiply accumulate units (MAUs) 471-1, . . . , 471-N, lookup table 472, and prescaled, preshifted coefficients 474, as may be stored in lookup table 472. Advantages of custom signal processing integration, as such, include reduction of power consumption by digital signal processor 400.
In some exemplary embodiments, digital signal processor 400 may include N multiply accumulate units 471-1, . . . , 471-N, corresponding to N channels, 481-1, . . . , 481-N, that carry 1-bit data stream in parallel to the N MAUs. Advantages of parallel processing and distribution may include improved online, real-time data processing. The N channels, carrying the 1-bit data stream from the sigma-delta ADC converter, correspond to the analog neuroelectric signal received from the analog channels.
Referring again to
In some embodiments, output device interface 410 can include a bus that connects digital signal processor 400 with output device 110. The data that is sent along the bus, or other interface, such as a wireless connection, may be particularly suited for the type of output device 110 deployed. In some embodiments, stimulus generator interface 430 may connect a stimulus generator 130 to the digital signal processor 400, which controls the stimulus generator. In some embodiments, external connection interface 440 may be a wireless connection to a printer or a handheld or otherwise mobile device. Additionally, external connection interface 440 may comprise a direct wired connection to any external device.
User input interface 460 can connect system 100 to a user input device, such as a keyboard, through digital signal processor 400. In some embodiments, user input interface 460 can be incorporated in output device interface 410. For example, output device 110 can include a touch screen that is designed to both display end-user information and accept user input. In some embodiments, user input interface 460 may be incorporated with an interface for external connection 440. For example, interface for external connection 440 can enable a connection between system 100 and a mobile device or stationary computer 470, and the input interface 460 may be further configured to accept and transmit input data to digital signal processor 400. The external connection 440 may again be a direct wired or wireless connection.
As shown in exemplary integrated circuit 500, electrodes 191-1, . . . , 191-n acquire data relating to the brain electrical activity of patient 10 and feed the data into analog channels 291-1, . . . , 291-n. Additionally, exemplary integrated circuit 500 includes unused analog channels 291-0, 291-n+1, which serve as dummy or compensatory structures at the edge of the array of channels. Advantages of having the unused channels may include mitigation of errors caused by edge effects in the integrated circuit, and more particularly, to the mitigation of mismatches and non-uniformities between the electrical structures.
In some exemplary embodiments, integrated circuit 500 can comprise nine electrodes 191-1, . . . , 191-9 and eleven analog channels 291-0, . . . , 291-10, wherein data from analog channels 291-0, 291-10 are unused. Advantages of having nine electrodes 191-1, . . . , 191-9, as opposed to a standard 20/10 electrode set, can include reduced placement complexity.
In some embodiments of integrated circuit 500, the recording electrodes are not directly connected to the differential amplifier, but are connected by way of preamplifier stages 511, that may serve to amplify submicrovolt signals for processing in some embodiments. Such amplifiers may have high input impedances and low output impedances to increase the effective CMRR (Common Mode Rejection Ratio). Subsequent to preamplification, the signal may be passed through differential amplifier stages 513. Each differential amplifier has two inputs and an electrode is connected to each input via the preamplifier, in a manner called ‘montage’ which is known in the prior art. The differential amplifier measures the voltage difference between the two signals at each of its inputs, and the resultant signal is amplified.
In some embodiments, the amplified analog signal produced by differential amplifiers 513 can be used to check lead impedance 326 and a signal can be fed back to the electrode via the digital signal processor 400, as described by system processes 320 with reference to
In some embodiments, the analog signal produced by differential amplifiers 513 can be passed through a common mode detector 515 (a right leg drive circuit), which raises the CMRR of the system. This may reduce noise that appears as common-mode voltage signal on both input leads of the differential amplifier, thereby improving the signal-to-noise ratio of the signal processing component of system 100.
In some embodiments, integrated circuit 500 can additionally include a gain stage with filtering 517. The one or more filters used in stage 517 can include low pass, band pass, or high pass filters, depending on the algorithm employed by integrated circuit 500. In an exemplary embodiment of integrated circuit 500, as may be used in conjunction with neurological evaluation system 100.
Additionally, integrated circuit 500 can further include multiplexer (MUX) 550, an ADC 560 which can be 1-bit sigma-delta (ΣΔ) modulator without noise shaping, and a digital signal processor 400. MUX 550 may additionally be configured to output a channel timing 512 signal, which serves as the clock signal for the shift registers of digital signal processor 400. ADC 560 may transmit 1-bit stream 510 to processor 400. ADC 560 may also have a variable sampling rate, which enables oversampling to avoid aliasing.
Additionally, as shown in an exemplary embodiment, digital signal processor 400 can comprise a plurality of multiply accumulate units 471-1, . . . , 471-N with transform coefficient lookup table 610 per channel, a plurality of shift registers that help in handling the data processing, channels 481-1, . . . , 481-N that carry the 1-bit data stream from the ADC 560, and an EP sync block for synchronizing the timing of the operation of the processor 400 with the timing of generating stimulus pulses by the stimulus generator 130, since the EPs are time-locked to stimuli onset to improve signal-to-noise ratio. One of the input to the shift registers is the clock pulse input from the MUX 550, and data is shifted right (down) into the MAUs according to the clocking rate. The look-up tables store pre-scaled, pre-shifted coefficients, and the size of the look-up table is kept limited to the requirements of the wavelet algorithm to limit memory storage demands.
Once selected, an electrode array may be attached to a subject, as indicated at Step 720. As disclosed with reference to
Next, a stimulus generator may be activated if evoked potentials have to be recorded, as indicated at Step 730. The stimulus generator may be activated by the digital signal processor 400. The device provided at step 710 may require configuration prior to activating the stimulus generator at Step 730. Configuration requirements may include, but are not limited to, activating the device, providing user input, and establishing a connection to one or more external devices.
The activation of the stimulus generator at Step 730 may cause the subject's neurological activity to include EP activity. The device may detect data at Step 740. The data may comprise spontaneous brain electrical activity and evoked potentials.
Next, as shown in exemplary method 700, the device may continue to activate the stimulus generator and detect data in parallel, or the device may record the base brain electrical activity without eliciting evoked potential. The data is processed by the digital signal processor using harmonic signal analysis. The processor may also be configured to perform transform-domain denoising algorithm, which would efficiently remove both Gaussian as well as Gaussian mixed with impulse noise contamination. The processor may also be configured to perform fractal analysis and multiscale harmonic analysis to process the data. At Step 750, when the device has sufficient data to perform analysis, a determination may be made as to the subject's neurological state, which may be based on the analysis results. The method may continue to assess the subject's neurological state as additional data is acquired and processed over time.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
