The present disclosure generally relates to systems and method for patient monitoring and, more particularly, to systems and methods for wireless monitoring of physiological signals.
Electroencephalogram (“EEG”) and other physiological monitoring has become a standard practice being used to diagnose and treat patients in various clinical settings, including operating rooms and intensive care units. For instance, a number of EEG monitoring systems have been developed to help track the level of consciousness of patients receiving general anesthesia or sedation during surgery or other medical procedures, such as a medically induced coma. By analyzing EEG measurements, monitoring systems typically provide feedback to clinicians in the form of partial or amalgamated representations indicating the condition of the patient at any one time.
For instance, traditional monitoring systems have often quantified a patient's depth of anesthesia through a single dimensionless index, such as the so-called Bispectral Index (“BIS”). In particular, the BIS is derived by computing spectral and bispectral features from acquired EEG waveform. The computed features are then provided as input to proprietary algorithms to derive an index between 0 and 100. Decreased BIS values indicate deepening levels of anesthesia or sedation, with 100 corresponding to a fully awake state and 0 corresponding to the most profound state of coma. More recent approaches have identified and implemented other information extracted from acquired EEG data to indicate various states of anesthesia and sedation, including patterns in signal spectra, transient signals, signal coherence and synchrony, to name but a few.
EEG monitors have also been used to help diagnose and treat sleep disorders. In particular, sleep is a natural, restorative, altered state of consciousness common to every living human being. Neurophysiologically, sleep is a continuous, dynamic process involving the complex interaction of cortical and sub-cortical networks within the brain operating on multiple time scales. As such, EEG monitoring naturally provides brain activity information, including correlates of activity from numerous brain regions. Furthermore, EEG data has also been used to study psychological (e.g., schizophrenia, depression, and anxiety) and neurological (e.g., Alzheimer's disease and Parkinson's disease) disorders, which affect millions of people worldwide and are often associated with disrupted sleep dynamics,
Although much progress has been made in identifying key indicators of states of consciousness and sleep, their accuracy relies on the quality and reliability of the acquired EEG signals. However, in realistic clinical situations, such as during surgery, EEG data can be subjected to various sources of noise and distortion. For instance, current monitoring systems include EEG sensors with extended wires, which act as antennas that pick up external noise from equipment and machines as well as spurious noise present in the operating room. Also, long wires can be quite cumbersome for medical staff during surgery, and other medical procedures. In addition, EEG sensors used in current monitoring systems are typically incorporated into headbands or headsets that are either uncomfortable or unsuitable for long term use, or are prone to artifacts or signal interruptions due to poor connectivity to the patient.
Clinical investigations of sleep disorders, and other neurological conditions, have often been limited to EEG monitoring systems in sleep labs or other clinical settings. Notwithstanding that many such clinical EEG systems are not amenable to non-clinical or home applications, they also suffer from similar data noise and distortion, particularly due to movement during sleep. In addition, although wearable consumer devices are increasingly being used for various sleep information applications, data provided by these devices do not have clinically proven reliability or accuracy, and are hence not used for scientific or medical purposes.
In light of the above, there is a need for improved technologies for monitoring physiological signals from patients.
The present disclosure provides a novel system and method for monitoring of physiological signals, including wireless electroencephalogram (“EEG”) and other physiological monitoring. As will be described, the provided system and method includes elements and features that overcome drawbacks of present technologies.
In one aspect of the disclosure, an electroencephalogram (“EEG”) monitoring system is provided. The system includes an electrode patch assembly configured to attach to a subject's skin, the electrode patch assembly comprising a flexible circuit layer having a plurality of electrical leads configured to acquire EEG signals from the subject, the flexible circuit layer having a shielding layer configured to substantially reduce a coupling of the plurality of electrical leads to external sources of noise, and a holder to which the flexible circuit layer is secured. The system also includes an electronics module removably coupled to the holder and configured to engage electrical contacts on the flexible circuit layer, the electronics module comprising a front-end module configured to perform an active noise cancellation process on the acquired EEG signals and generate digitized data using noise cancelled signals and a processor configured to transmit the digitized data using a wireless communication module. The system further includes an external device configured to receive and analyze the digitized data transmitted to determine a condition of the subject.
In another aspect of the disclosure, a system for wirelessly monitoring a subject is provided. The system includes an electrode patch assembly configured to attach to a subject's skin, the electrode patch assembly comprising a flexible circuit layer having a plurality of electrical leads configured to acquire physiological signals from the subject, the flexible circuit layer having a shielding layer configured to substantially reduce a coupling of the plurality of electrical leads to external sources of noise, and a holder to which the flexible circuit layer is secured. The system also includes an electronics module removably coupled to the holder and configured to engage electrical contacts on the flexible circuit layer, the electronics module comprising a front-end module configured to generate digitized data using the acquired physiological signals and a processor configured to wirelessly transmit, using a transceiver in the electronics module, the digitized data. The system further includes an external device configured to communicate with the electronics module using a wireless communication protocol to receive the digitized data transmitted.
In yet another aspect of the disclosure, a system for wirelessly monitoring a subject is provided. The system includes an electrode patch assembly configured to attach to a subject's skin, the electrode patch assembly comprising a flexible circuit layer having a plurality of electrical leads configured to acquire physiological signals from the subject, the flexible circuit layer having a shielding layer configured to substantially reduce a coupling of the plurality of electrical leads to external sources of noise, and a holder to which the flexible circuit layer is secured. The system also includes an electronics module removably coupled to the holder and configured to engage electrical contacts on the flexible circuit layer using an electrical coupling, the electronics module comprising a front-end module configured to generate digitized data using the acquired physiological signals and a processor configured to compress and wirelessly transmit the digitized data, using a transceiver in the electronics module.
The foregoing and other aspects and advantages of the invention will appear from the following description. In the description, reference is made to the accompanying drawings that form a part hereof, and in which there is shown by way of illustration a preferred embodiment of the invention. Such embodiment does not necessarily represent the full scope of the invention, however, and reference is made therefore to the claims and herein for interpreting the scope of the invention.
The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
The present disclosure provides a system and method for monitoring of physiological signals. As will become apparent from description below, the provided system and method have a wide range of applicability in various settings, including identifying, based on the measured physiological signals, such as electroencephalogram (“EEG”) signals, acute or long-term signatures indicative of a subject's medical condition. That is, the present platform may provide reliable monitoring over minutes, hours, and days, in operating rooms, intensive care units, and non-clinical settings. Identified signatures may then be used to determine a medical or brain condition of the subject, such as the onset and/or level of anesthesia, sedation, coma, sleep, pain, and others. In addition, the present system and method may also be used to determine an effectiveness of an administered treatment or medication.
The present monitoring platform includes an electrode patch assembly, which may refer broadly to any system, device or applicator having features and capabilities in accordance with the present disclosure. Non-limiting examples may include bandages, patches, headbands, wristbands, legbands, straps, necklaces, cuffs, belts, wearable electronics, and so forth, that are configured for placement and coupling to various portions of the body.
Referring particularly to
As shown in
Specifically, the processor 112 may be configured to coordinate the various operation modes and states of the electronics module 102 using transitory and non-transitory instructions stored in a memory, as well as instructions provided via the wireless communication module 114 and/or input 122. As one non-limiting example, the processor 112 may include a low-power high performance microcontroller, including a microcontroller having self-programming flash memory, a boot code section, SRAM, EEPROM, an external bus interface, a multi-channel DMA controller, multi-channel event system, and other features.
In some aspects, the processor 112 may be configured to coordinate physiological signal acquisition and processing, wireless communication with an external device 126, power management, and other functions. By way of example, the external device 126 or remote host may be a computer, laptop, workstation, mobile device, tablet, phone, and so forth, configured to receive, process, and analyze received data, as well as transmit data and instructions. For example, the external device 126 may be configured to analyze acquired EEG data, and other physiological data, and determine a brain condition of the subject, such as the onset and/or level of anesthesia, sedation, coma, sleep, pain, and others. In addition, the external device 126 may be configured to determine an effectiveness of an administered treatment or medication based on the acquired physiological data.
In one implementation, the processor 112 may run a software application program that coordinates the acquisition and processing of detected physiological signals, such as EEG signals, electromyography (“EMG”) signals, galvanic skin response (“GSR”) signals, electrocardiogram (“ECG”) signals. and other physiological signals. In some aspects, the processor 112 may also be configured to acquire and process actigraphy or multi-axis accelerometer signals using the internal sensors 122, which may be used for detecting, for example, arousals in sleep or in the operating room, as well as a body position. In alternative embodiments, the processor 112 may obtain actigraphy signals from accelerometers included in the electrode patch assembly 104. Signal acquisition may be performed at a pre-determined sampling rate, or as instructed by the external device 126, and may depend upon the signal type.
The processor 112 may then set up a wired or wireless link to a host, receive commands and setup information, and transmit processed physiological signals in the form of digitized and/or compressed physiological data in real-time using a specific communication protocol, such as a wireless communication protocol. Alternatively, or additionally, the processor 112 may be configured to pre-process raw signal data, as well as store the pre-processed or raw signal data in the memory 128 for subsequent retrieval, pre-processing, and/or transmission. The processor 112 may also set up a battery charger integrated circuits, and display operational status using the output 116. In some aspects, the processor 112 may be configured to identify the type of electrode patch assembly 104 that is coupled to the electronics module 102. As such, modes of operation and operational parameters may be adapted based upon the detected and identified electrode patch assembly 104. For example, the processor 112 may determine the type of electrode patch assembly 104 by the number of types of signals received. In addition, the processor 112 may also be configured to detect whether a connection has been established or lost with the electrode patch assembly 104, and provide an indication to the user via the output 116.
Referring again to
As such, the front-end module 110 may include a wide variety of electrical components, including passive components, as well as an integrated circuit (“IC”) with amplifiers and an analog-to-digital (“A/D”) converter. In some embodiments, the front-end module 110 may include one or more low-pass, or high-pass filters with cutoff frequencies approximately between 0.5 and 500 Hz, although other values may be possible. The front-end module 110 may also include a band-pass filter, or any combinations of filters. In some aspects, the front-end module 110 alone, or in cooperation with the processor 112, may be configured to analyze analog or digitized physiological signals, or other measured signals, and coordinate an active noise cancellation process either via direct noise filtration of the measured signals, or via electric signals provided to shielding or grounding leads or layers in the electrode patch assembly 104, as will be described. In some aspects, the pre-processing may depend on signal characteristics, such as signal amplitudes, frequencies, phases, power spectra, noise profiles, and so forth of the acquired physiological signals. Also, in some aspects, such signal pre-processing may vary depending upon the identified electrode patch assembly 104, as described.
In one non-limiting example, the IC included in the front-end module 110 may be configured to provide one or more reference signals, in the form of bias voltage for instance, based on received EEG or other physiological signals signals, in order to remove unwanted voltage offsets from the received EEG or other signals. The offset EEG signals may then be amplified and converted into 24-bit digital values, for instance.
As mentioned, the processor 112 also communicates with a wireless communication module 114, allowing the wireless transmission and reception of data, instructions, and other information between the electronics module 102 and external device 126 via a customizable communication protocol. As such, the wireless communication module 114 includes a radio transceiver, and other hardware. For example, the radio transceiver may be a Bluetooth radio transceiver configured to manage both the physical and data link layers, although other types of wireless transceivers may be possible.
Referring again to
For instance, voltage regulators in the power management module 118 may be used to convert a voltage of the battery 120 into lower voltages that are needed by the various components of the electronics module 102. Also, the power management module 118 may include a battery charger IC that can manage the proper charging of the battery 120. That is, when an external charge voltage provided by the charging station 106 is detected, by way of an electrical connection to the electrical coupling 108, the charger IC can apply a charge voltage and current to the battery 120 based on a current level of the battery 120, as detected by the power management module 118, for instance. As such, the charger IC can then manage charge voltage/current profile in order to safely charge the battery 120 and extend its life. In one example, the battery 120 may be a single cell (i.e. 3.6V) lithium-polymer rechargeable battery. The battery 120 may be configured and dimensioned in accordance with desired run time before recharging, and physical size.
As shown, the electronics module 102 includes an output 116, which may be in the form of LEDs, LCD displays, and the like, configured to provide various indications to a user. For instance, in some implementations, the output 116 may include one or more colored LEDs that indicate the operational state of the electronics module 102. By way of example, operational states of the electronics module 102 may include when the electronics module 102 is coupled to the charging station 106, when the battery 102 is charging, when the battery 120 is fully charged, when the battery 120 requires charging, when the electronics module 102 is connected to the electrode patch assembly 104, when data is being transmitted or received from the external device 126, when no connection is made to the external device 126, when a data connection is made to the external device 126 yet data is not being transmitted, and so forth. As shown in
Turning now to
The bottom portion 204 of the housing includes an electrical coupling opening 206, which allows electrical contacts 208 to protrude therethrough (
Referring again to
Referring particularly to
Although the housing of the electronics module 200 is shown in a particular implementation in
Referring now to
As shown in
In one application, electrodes 306 included in the central portion 308 may be coupled to the subject's forehead, while electrodes 306 included in the extended portion 310 may be coupled to the mastoid processes (behind the ear) of the subject. For example, during one type of measurement, seven of the electrodes 306 may be used as EEG signal inputs and one as reference input, with the reference electrode 312 being located in the central portion 308 of the flexible circuit layer 300. Alternatively, various combinations of the electrodes can be used for additional reference schemes, for example, a common average reference or a Laplacian reference. In this configuration, various physiological signals may be obtained from the subject, including EEG alpha signals. In particular, this design facilitates the acquisition of occipital EEG alpha signals without the difficulties of using an area of head that has hair, or an area of the back of the head that includes large muscles producing interfering signals.
Referring specifically to
As described, the flexible electrode circuit 302 of
The holder 350 may also include a circular recess 356 configured to hold a magnetic or metallic material that is configured to engage with a magnet of an electronics module, as described with reference to
The insertion and locking mechanism described above allows the electronics module to be easily and quickly attached while making a high quality electrical connection between the electronics module and the flexible electrode circuit due to the mechanical pivoting action that drags the leaf-spring contacts on the electronics module against the exposed conductive traces on the flexible material. The electronics module can then be easily removed by pulling the free end of the module until the strength of the bond between the magnets is broken. In this manner, multiple electronics modules can be removed and replaced with freshly charged ones without need for removing electrode patch assembly from the subject. This allows for monitoring for periods of time that are much longer than the battery life of any single electronics module with minimal interruption.
Referring again to
As mentioned, the flexible circuit layer 300 may be configured to be coupled to a subject's skin. As such, in some aspects, at least a portion of the flexible circuit layer 300 may also include an adhesive layer that is configured to provide attachment to the subject's skin (for clarity not shown in
Prior to use, the adhesive layer may be protected by removable packaging. Referring now
Before use, the user peels back and removes the release liner 534 from the bottom of the electrode patch assembly, exposing both the gel-covered conductive electrodes on the bottom side of the flexible circuit layer 502 as well as the adhesive layer 528. Conductive gel is kept in place over the exposed electrode and remains fresh due to the release liner 534 creating a tight seal to the flexible circuit layer 502. After the electrode patch assembly has been adhered to the skin, the application stiffener 532 may then be peeled off and removed, allowing the skin to breath freely through the adhesive layer 528. Views of an electrode patch assembly with an application stiffener in place and covering an adhesive layer are shown below in
By keeping the conductive paths of electrical leads in the electrode patch assembly narrow, and by holding electrical leads and electrodes to the skin using a very thin, breathable, and stretchable adhesive layer, the present monitoring system is comfortable to wear for long periods of time. In addition, the described electrode patch assembly, while disposable, includes features that allow for improved clinical-grade physiological signal acquisition with high signal-to-noise ratio. Specifically, the conductive shield layer extending substantially over the length of the electrical leads in the electrode patch assembly and connecting to a reference point can reduce the coupling of external electro-magnetic signals to the signal paths. Also, a flexible, breathable adhesive layer holding the conductive paths tightly to the skin reduces motion artifacts, eliminating electrical voltages that are typically created when wires are able to move in free space. Other advantages of the present system include being small, lightweight, portable, and low-cost, allowing for simple use and being logistically efficient. In addition, physiological signal digitization close to the source, and optionally compression that allows for efficient and high quality data to be transmitted and analyzed.
As an example,
As described, electronics modules, in accordance with aspects of the present disclosure, may be recharged.
Referring now to
As indicated by step 900 in
In the sleep state, the processor of the electronics module may turn off as much of the circuitry as possible in order to reduce power consumption. The processor may then be put into a low power sleep state, waking periodically to verify whether there is any reason to exit the sleep state. For instance, if a charge voltage is detected, the application enters the battery charging state, as indicated by step 904. In the battery charging state, the application may turn on the battery charger and monitor the charge state, displaying the charge status on the colored LED indicators, or other indicators, as appropriate. If the charge voltage disappears, the application may then return to the sleep state.
Alternatively, if an electrode patch is detected, a state that looks for Bluetooth connections may then be entered, as indicated by step 906. In addition, based upon the type of patch detected, the signal acquisition and/or signal processing may be adapted accordingly. Upon entering the state of looking for a Bluetooth connection to the host, the application may enable the Bluetooth radio transceiver and begin advertising the presence of the electronics module. If an electrode patch/patch assembly is no longer detected, the application may shut off the Bluetooth radio transceiver and return to the sleep state. If a data connection with a host is detected, advertising messages may be stopped and the state that supports the host may be entered, as indicated by step 908.
In the host connection support state, commands received from the host may be acted upon. The command for status may be answered, and the command for setting operational characteristics may be processed. If the command to begin streaming EEG and other physiological data is received, the front-end module may be enabled to begin capturing data at the pre-determined sampling rate. The application may then read samples and send them to the host in the pre-determined packet format. Sampling may continue until the command to stop is received, the Bluetooth link to the host is dropped, or the patch is no longer seen. When the electrical connection to the electrode patch is lost, the application may then return to the sleep state. If the host connection is dropped, the application may return to the state that looks for Bluetooth connections.
In some implementations, a wireless communication protocol between the electronics module and an external device, or host may include two communication modes, namely a command/response and streaming data. In the first communication mode, commands may be sent from the host to the electronics module, and the electronics module sends an immediate reply. The command sequence may include a fixed synch header, a command and supporting information, and a checksum. A checksum may be generated across the command and supporting information, allowing the electronics module to calculate the checksum on any command sequence that is received from the host and determine if the command sequence was received correctly. If not, the command sequence may be ignored. Responses to commands sent from the electronics module to the host may include a fixed synch header, the command that is being responded to, supporting information required to reply to the command, and a checksum. The checksum may be generated across the command and supporting information, allowing the host to calculate the checksum on any response sequence that is received from the electronics module and determine if the reply sequence was received correctly.
In the second communication mode, physiological data may be streamed continuously from the electronics module to the host without the need for any support from the host. The streaming packet format may include a fixed synch header, a sequence number, a block of physiological information, and a checksum. The checksum may generated over the entire block of physiological information, allowing the host to determine whether the physiological data was received correctly. Each packet of streaming physiological data increments the sequence number by one, indicating to the host when a block of physiological data was not received.
In some applications, physiological data may be natively acquired in a 24-bit format, yet the communication protocol may allow for the streaming of the data in a different format, such as 8-bit (upper 8 bits of the native 24-bit format), 16 bit (upper 16 bits), 24 bit (full native format data). In some aspects, the physiological data may be transformed into a 16-bit “delta” format. This last format compresses 24-bits of physiological data into 16 bits by subtracting the most recent 24-bit physiological value from the previous 24-bit value using 16-bit arithmetic. Compressed data may be advantageous for reducing power consumption, and thus increasing the time between battery replacement or recharging. As such, the format of the transmitted data may therefore depend upon the richness and fidelity of the data to be transmitted, energy needs and consumption of the system or device, as well as desired acquisition longevity or use. By way of example, one command may request the status and current operating modes of the electronics module, where the reply includes the firmware version, the number of samples in each physiological data streaming packet, the type of format used to send samples, the number of channels being sampled on the electrode patch, and the charge level of the battery. Another example command may allow the host to set the operating characteristics of the electronics module, including the number of the sampling rate of the physiological values, the number of physiological samples to include in each physiological data streaming packet, the format to use when streaming physiological data, the amplifier settings such as gain, the number of physiological channels to sample from the patch, and the referencing scheme. Yet another example command may turn physiological data streaming on or off. Yet another example command may request a patch type status response. Yet another command may set a gain setting. In addition, other commands may be used for diagnostic reasons to directly write and read the control registers within the front-end module of the electronics module.
Turning now to
The transmitted physiological data may then be analyzed at process block 1010 to determine a condition of the subject. As described, this may include identifying specific signatures in the data that may then be used to determine a medical or brain condition of the subject, such as the onset and/or level of anesthesia, sedation, coma, sleep, pain, and others. In addition, an effectiveness of an administered treatment or medication may be determined based on the analyzed data. A report may then be generated, as indicated by process block 1012. The report may include real-time information, such as various waveforms representing measured physiological signals, as well as information or data derived therefrom.
As may be appreciated from the above, the herein provided patient monitoring system and method affords significant advantages compared to current technologies. To further illustrate this point, a sleep experiment was carried out, where 10 minutes of EEG data was simultaneously recorded using a system, in accordance with the present disclosure, and a traditional sleep lab monitoring system. The results are shown in
The results show similar closed-eye alpha (8-12 Hz) signals, and slow oscillation activity (<5 Hz), indicating that the present approach can provide clinical-quality data. However, unlike the traditional system, the present system is able to provide high-fidelity data even in problematic conditions, such as during patient motion, or head shaking, as indicated in
Moreover, further experiments were performed with patients in a sleep lab setting, where simultaneous full-night sleep EEG recordings were acquired using the present approach and a standard 6-channel wired clinical EEG system. The recordings were scored independently by a clinical sleep technician using the procedures outlined by the American Academy of Sleep Medicine to determine the sleep stages across the night (the hypnogram). The results showed no significant difference between sleep stages when using the present system as compared to a traditional clinical system (Cohen's Kappa >0.6). This finding illustrates rigorous equivalence in the ability to capture brain activity during sleep using present approach and the gold standard of clinical systems used in sleep medicine.
The present invention has been described in terms of one or more preferred embodiments, and it should be appreciated that many equivalents, alternatives, variations, and modifications, aside from those expressly stated, are possible and within the scope of the invention.
This application is based on, claims priority to, and incorporates herein by reference in its entirety, U.S. Provisional Application No. 62/213,232, filed on Sep. 2, 2015, and entitled “Wireless EEG sensors.”
This invention was made with government support under Grant No. DP2-OD006454 awarded by the National Institutes of Health. The government has certain rights in the invention.
Filing Document | Filing Date | Country | Kind |
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PCT/US16/50230 | 9/2/2016 | WO | 00 |
Number | Date | Country | |
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62213232 | Sep 2015 | US |