Wearable non-invasive electroencephalogram and ultrasound device for deep brain stimulation in rapid eye movement sleep enhancement

Abstract

Disclosed herein are systems and devices for providing stimulation based on electroencephalogram (EEG) data. An example Non-Invasive EEG / Ultrasound Stimulation Electronic Patch (NEUSleeP) device can provide, via a wearable ultrasound transducer, non-invasive ultrasound stimulation to the subject's subthalamic nucleus (STN) or other target areas of the subject's brain.

Description

Attorney Docket No. 10046-659W018551 WAN WEARABLE NON-INVASIVE ELECTROENCEPHALOGRAM (EEG) AND ULTRASOUND DEVICE FOR DEEP BRAIN STIMULATION IN RAPID EYE MOVEMENT (REM) SLEEP ENHANCEMENTGovernment Support Clause

[0001] This invention was made with government support under Grant No. HR0011-24-9-0328, awarded by the Defense Advanced Research Projects Agency (DARPA). The government has certain rights in the invention.Related Application

[0002] This application claims priority to, and the benefit of, U. S. Provisional Patent Application No. 63 / 719,761, filed November 13, 2024, and Provisional Patent Application No. U. S. 63 / 895,615, filed October 8, 2025, the contents of which are incorporated by reference herein in their entireties.Background

[0003] Sleep is critical in human health, affecting mental and physical performance, reaction time, and decision-making. However, service members often face poor sleep due to demanding work schedules, operational commitments, and external factors like noise and light. Insufficient sleep and sleep disturbances contribute to decreased rapid eye movement (REM) sleep, primarily occurring in the second sleep period. The decrease in and fragmentation of REM sleep negatively impact emotional well-being and resilience and inhibit the ability to adapt to stress and trauma, which service members frequently encounter. The decrease in REM sleep can result in reduced military performance, resilience, and increased rates of physical and mental health issues, including post-traumatic stress disorder (PTSD).

[0004] There is a need for devices, systems, and methods to improve and enhance REM sleep in human subjects.Summary

[0005] In accordance with the purposes of the disclosed materials and methods, as embodied and broadly described herein, the disclosed subject matter, in one aspect, relates to compositions, devices, systems, and methods of making and using said compositions, devices, and systems.

[0006] In some implementations, the techniques described herein relate to a Non-Invasive EEG / Ultrasound Stimulation Electronic Patch (NEUSleeP) device configured to be worn in proximity to a subject's head or for facial feature conformation, the device can be configuredAttorney Docket No. 10046-659W018551 WAN to: obtain, via one or more hydrogels, electroencephalogram (EEG) data from the subject; and provide, via a wearable ultrasound transducer and a long-term stable bioadhesive acoustic couplant, non-invasive ultrasound stimulation to the subject's subthalamic nucleus (STN) to enhance rapid eye movement (REM) sleep, wherein the wearable ultrasound transducer is adjustable for focal depth targeting of the STN.

[0007] In some implementations, the device further includes at least one of: an integrated Concentric Ring Array Transducer (CRUTA) for adjustable focal depth in targeting STN for non-invasive neuromodulation of STN in REM sleep enhancement, and one or more two- dimensional (2D) array transducers configured for beamsteering and beamfocusing to target the subject's STN.

[0008] In some implementations, the device is operatively coupled to a controller configured to: determine a plurality of STN stimulation parameters (e.g., frequency parameters, acoustic intensity parameters, and focal depth) and / or a stimulation protocol; and provide the non-invasive ultrasound stimulation according to the determined stimulation parameters.

[0009] In some implementations, the device is operatively coupled to an external ultrasound generator or a wireless ultrasound device.

[0010] In some implementations, the one or more hydrogels are fixably attached to a bioadhesive elastomer substrate.

[0011] In some implementations, a wearable device is provided. The wearable device can include: a bioadhesive elastomer substrate; one or more acoustic hydrogel couplants (e.g., each including an acoustic lens and hydrogel or hydrogel coating on an acoustic lens) fixably attached to the bioadhesive elastomer substrate; and an ultrasound transducer or device operatively coupled to an ultrasound generator, wherein the wearable device is configured to adhere to a subject's skin and provide non-invasive ultrasound stimulation to the subject.

[0012] In some implementations, the wearable device is in electronic communication with a controller configured to: determine a target area of the subject's brain (e.g., based on a medical condition of the subject); determine a plurality of stimulation parameters and / or a stimulation protocol corresponding with the target area; and cause the wearable device to deliver the non-invasive ultrasound stimulation to the target area in accordance with the determined plurality of stimulation parameters and / or the stimulation protocol.

[0013] In some implementations, the controller is further configured to: control or direct ultrasound stimulation from the ultrasound transducer or device, and control the ultrasoundAttorney Docket No. 10046-659W018551 WAN stimulation based, at least in part, on analysis of EEG data obtained via the one or more acoustic hydrogel couplants.

[0014] In some implementations, the plurality of stimulation parameters includes at least one of Center frequency (fO), Pulse Duration (PD), Pulse Repetition Frequency (PRF), Pulse Duty, Burst Duty, Cycles per pulse, Cycles per burst, Peak Pressure (P), Spatial peak pulse average intensity (Isppa), Spatial peak temporal average intensity (Ispta), Mechanical Index (MI), acoustic intensity, and focal depth.

[0015] In some implementations, the wearable device further includes one or more two- dimensional (2D) array transducers, wherein the one or more two-dimensional array transducers are used for beamsteering and beamfocusing to target the target area of the subject’s brain.

[0016] In some implementations, each hydrogel of the one or more acoustic couplants is formed from: a) a first monomer including one or more ion-forming moieties; b) a polyol: and c) water; wherein the first monomer and water have a ratio by weight from about 1: 1 to about 1:4; and wherein the polyol is present in an amount from about 10% to about 40% by weight based on the weight of the hydrogel.

[0017] In some implementations: the first monomer includes 2-acrylamido-2-methylpropane sulfonic acid or a salt thereof; and the polyol includes glycerol.

[0018] In some implementations, the hydrogel is further formed from: d) a crosslinker (such as N, N-methylenebis(acrylamide), N, N-dimethylacrylamide (DMAA), polyethylene glycol) diacrylate (PEGDA), or a combination thereof); and / or e) an initiator (such as ammonium persulfate in combination with a catalyst, for example tetramethylethylenediamine (TMEDA)).

[0019] In some implementations, the bioadhesive elastomer substrate is formed from: a) a polysiloxane (such as polydimethylsiloxane); b) a polyamine (such as polyethyleneimine); and c) optionally one or more additives.

[0020] In some implementations, the device is used for treatment of at least one of: Parkinson's disease, epilepsy, Alzheimer's disease, stroke, traumatic brain injury, psychiatric disorders (e.g., depression, anxiety, obsessive-compulsive disorder), pain, (e.g., brain stimulation, spinal cord stimulation, or peripheral stimulation), peripheral chronic joint pain, overactive bladder syndrome, sleep disorders (e.g., sleep apnea, redness leg syndrome), carpal tunnel syndrome, visual prosthetics and / or blindness, or mood disorders, or any combination thereof.Attorney Docket No. 10046-659W018551 WAN

[0021] In some implementations, a bioadhesive elastomer formed from: a) a polysiloxane; b) a polyamine; and c) optionally one or more additional additives is provided.

[0022] In some implementations, the polysiloxane is selected from polydimethylsiloxane (PDMS), polymethylhydrosiloxane (PMHS), polymethylphenyl siloxane (PMPS), polydiphenylsiloxane, polydiethylsiloxane, an amino-functionalized polysiloxane, an epoxy¬ functionalized polysiloxane, an acrylate- or methacrylate-functionalized polysiloxane, or combinations thereof, more particularly wherein the polysiloxane is polydimethylsiloxane (PDMS).

[0023] In some implementations, the polyamine is selected from polyethyl enimine (PEI), polypropyleneimine (PPI), poly(amidoamine) (PAM AM), or combinations thereof, more particularly wherein the poiyamine is polyethyleneimine (PEI).

[0024] In some implementations, an article including the bioadhesive elastomer is provided.

[0025] In some implementations, the article is a device, such as a medical device.

[0026] The details of one or more aspects of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the disclosure will be apparent from the description, the drawings, and the claims.Brief Description of Drawings

[0027] FIG. 1 is an example computing device, in accordance with an illustrative embodiment.

[0028] FIG. 2A is an example system, in accordance with an illustrative embodiment.

[0029] FIG. 2B is a flowchart diagram of an example method in accordance with an illustrative embodiment.

[0030] FIG. 3 A shows an example device, also referred to as a Non-Invasive Electrophysiological Recording and Ultrasound Neuromodulation Sleep Patch (NEUSLeep) device, configured to improve rapid eye movement (REM) sleep.

[0031] FIG. 3B shows an example Eco-PEIE-Gel bioadhesive encapsulation substrate / layer in the exemplary device.

[0032] FIG. 3C shows an example 2-Acrylamido-2-methylpropane sulfonic acid-based Sleep Gel (ASG) in the exemplary device.

[0033] FIG. 3D shows an example 8-channel piezoelectric concentric ring transducer array (CRUTA) in accordance with an illustrative embodiment.Attorney Docket No. 10046-659W018551 WAN

[0034] FIGS. 4A - 4N show the experimental fabrication and characterization of the exemplary device and its components, and the evaluations of the exemplary device and its impacts on the sleep quality of experiment participants.

[0035] FIGS. 5 A - 5E shows further evaluations of the impacts of the exemplary device on the brains and sleep quality of the participants.Detailed Description

[0036] The following description of the disclosure is provided as an enabling teaching of the disclosure in its best, currently known aspects. Many modifications and other aspects disclosed herein will come to mind to one skilled in the art to which the disclosed compositions and methods pertain, benefiting from the teachings presented in the descriptions herein and the associated drawings. Therefore, it is understood that the disclosures are not limited to the specific aspects disclosed and that modifications and other aspects are intended to be included within the scope of the appended claims. The skilled artisan will recognize many variants and adaptations of the aspects described herein. These variants and adaptations are intended to be included in the teachings of this disclosure and to be encompassed by the claims herein.

[0037] Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.

[0038] As would be apparent to those of skill in the art upon reading this disclosure, each of the individual aspects described and illustrated herein has discrete components and features that may be readily separated from or combined with the features of any of the other several aspects without departing from the scope or spirit of the present disclosure.

[0039] Any recited method can be carried out in the order of events recited or any other order that is logically possible. Unless otherwise expressly stated, it is in no way intended that any method or aspect set forth herein be construed as requiring that its steps be performed in a specific order. Accordingly, where a method claim does not explicitly state in the claims or descriptions that the steps are to be limited to a particular order, it is in no way intended that an order be inferred in any respect. This holds for any possible non-express basis for interpretation, including logic concerning the arrangement of steps or operational flow, meaning derived from grammatical organization or punctuation, or the number or type of aspects described in the specification.

[0040] All publications mentioned herein are incorporated by reference to disclose and describe the methods or materials in connection with which the publications are cited. The publications discussed herein are provided solely for their disclosure before the filing date ofAttorney Docket No. 10046-659W018551 WAN the present application. Furthermore, the dates of publication provided herein may differ from the actual publication dates, which may require independent confirmation.

[0041] It is also to be understood that the terminology herein describes particular aspects only and is not intended to be limiting. Unless defined otherwise, all technical and scientific terms herein have the same meaning as commonly understood by one of ordinary skill in the art to which the disclosed compositions and methods belong. It can be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the specification and relevant art and should not be interpreted in an idealized or overly formal sense unless expressly- defined herein.

[0042] Before describing the various aspects of the present disclosure, the following definitions are provided and should be used unless otherwise indicated. Additional terms may be defined elsewhere in the present disclosure.

[0043] As used herein, “comprising” is interpreted as specifying the presence of the stated features, integers, steps, or components but does not preclude the presence or addition of one or more features, integers, steps, components, or groups thereof. Moreover, each of the terms “by,” “comprising,” “comprises,” “comprised of,” “including,” “includes,” “included,” “involving,” “involves,” “involved,” and “such as” are used in their open, non-limiting sense and may be used interchangeably. Further, the term “comprising” is intended to include examples and aspects encompassed by the terms “consisting essentially of’ and “consisting of.” Similarly, “consisting essentially of” is intended to include examples encompassed by the term “consisting of.”

[0044] As used in the specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the context dictates otherwise.

[0045] Ratios, concentrations, amounts, and other numerical data can be expressed herein in a range format. Further, the endpoints of each of the ranges are significant both in relation to the other endpoint and independently of the other endpoint. There are many values disclosed herein, and each value is also disclosed as “about” that particular value in addition to the value itself. For example, if the value “10” is disclosed, then “about 10” is also disclosed. Ranges can be expressed herein as from “about” one particular value and to “about” another particular value. Similarly, when values are expressed as approximations, using the antecedent “about,” the particular value forms a further aspect. For example, if the value “about 10” is disclosed, then “10” is also disclosed.Attorney Docket No. 10046-659W018551 WAN

[0046] When a range is expressed, a further aspect includes from the one particular value and to the other particular value. For example, where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure, e.g., the phrase “x to y” includes the range from ‘x’ to ‘y’ as well as the range greater than ‘x’ and less than ‘y’. The range can also be expressed as an upper limit, e.g. ‘about x, y, z, or less’ and should be interpreted to include the specific ranges of ‘about x,’ ‘about y,’ and ‘about z’ as well as the ranges of ‘less than x,’ ‘less than y.’ and ‘less than z.’ Likewise, the phrase ‘about x, y, z, or greater’ should be interpreted to include the specific ranges of ‘about x,’ ‘about y,’ and ‘about z’ as well as the ranges of ‘greater than x,’ greater than y,’ and ‘greater than z.’ In addition, the phrase “about ‘x’ to ‘y’,” where ‘x’ and ‘y’ are numerical values, includes “about ‘x’ to about ‘y’

[0047] Such a range format is used for convenience and brevity and thus, should be interpreted flexibly to include not only the numerical values explicitly recited as the limits of the range but also to include all the individual numerical values or sub-ranges encompassed within that range as if each numerical value and sub-range is explicitly recited. To illustrate, a numerical range of “about 0.1 % to 5%” should be interpreted to include not only the explicitly recited values of about 0.1% to about 5%, but also include individual values (e.g., about 1%, about 2%, about 3%, and about 4%) and the sub-ranges (e.g., about 0.5% to about 1.1%; about 5% to about 2.4%; about 0.5% to about 3.2%, and about 0.5% to about 4.4%, and other possible sub-ranges) within the indicated range.

[0048] As used herein, the terms “about,” “approximate,” “at or about,” and “substantially” mean that the amount or value in question can be the exact value or a value that provides equivalent results or effects as recited in the claims or taught herein. That is, amounts, sizes, formulations, parameters, and other quantities and characteristics are not and need not be exact but may be approximate, larger or smaller, as desired, reflecting tolerances, conversion factors, rounding, measurement error, and the like, and other factors known to those of skill in the art such that equivalent results or effects are obtained. In some circumstances, the value that provides equivalent results or effects cannot be reasonably determined. In such cases, as used herein, “about” and “at or about” mean the nominal value indicated ±10% variation unless otherwise indicated or inferred. In general, an amount, size, formulation, parameter, or other quantity or characteristic is “about,” “approximate,” or “at or about,” whether or not expressly stated to be such. Where “about,” “approximate,” or “at or about” is used before a quantitative value, the parameter also includes the specific quantitative value itself unless expressly stated otherwise.Attorney Docket No. 10046-659W018551 WAN

[0049] As used herein, “optional” or “optionally” means that the subsequently described event or circumstance can or cannot occur. The description includes instances where said event or circumstance occurs and those where it does not.

[0050] As used interchangeably herein, “subject,” “individual,” or “patient” can refer to a vertebrate organism, such as a mammal (e.g., human). “Subject” can also refer to a cell, a population of cells, a tissue, an organ, or an organism, preferably to a human and constituents thereof.

[0051] As used herein, “treating” and “treatment” generally refer to obtaining a desired pharmacological or physiological effect. The effect can be but does not necessarily have to be prophylactic in preventing or partially preventing a disease, symptom, or condition. The effect can be therapeutic regarding a partial or complete cure of a disease, condition, symptom, or adverse effect attributed to the disease, disorder, or condition. The term “treatment” as used herein can include any treatment of a disorder in a subject, particularly a human. It can include any one or more of the following: (a) preventing the disease from occurring in a subject who may be predisposed to the disease but has not yet been diagnosed as having it; (b) inhibiting the disease, i.e., arresting its development; and (c) relieving the disease, i.e., mitigating or ameliorating the disease or its symptoms or conditions. The term “treatment,” as used herein, can refer to both therapeutic treatment alone, prophylactic treatment alone, or both therapeutic and prophylactic treatment. Those in need of treatment (i.e., subjects in need thereof) can include those already with the disorder or those in which the disorder is to be prevented. As used herein, the term “treating” can include inhibiting the disease, disorder, or condition, e.g., impeding its progress; and relieving the disease, disorder, or condition, e.g., causing regression of the disease, disorder, or condition. Treating the disease, disorder, or condition can include ameliorating at least one symptom of the particular disease, disorder, or condition, even if the underlying pathophysiology is not affected, e.g., such as treating the pain of a subject by administration of an analgesic agent even though such agent does not treat the cause of the pain.

[0052] As used herein, the term or phrase “effective,” “effective amount,” or “conditions effective to” refers to such amount or condition that is capable of performing the function or property for which an effective amount or condition is expressed. As will be pointed out below, the exact amount or particular condition required will vary from one aspect to another, depending on recognized variables such as the materials employed and the processing conditions observed. Thus, it is not always possible to specify an exact “effective amount” or “condition effective to.” However, it should be understood that an appropriate effectiveAttorney Docket No. 10046-659W018551 WAN amount will be readily determined by one of ordinary skill in the art using only routine experimentation.

[0053] The terms “coupled” and “associated” generally mean electrically, electromagnetically, and / or physically (e.g., mechanically or chemically) coupled or linked and do not exclude the presence of intermediate elements between the coupled or associated items.

[0054] It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element, or intervening elements can be present. In contrast, when an element is referred to as being "directly connected" or "directly coupled" to another element, there are no intervening elements present. Other words used to describe the relationship between elements or layers should be interpreted in a like fashion (e.g., "between" versus "directly between," "adjacent" versus "directly adjacent," "on" versus "directly on").

[0055] It will be understood that although the terms "first," "second," etc., can be used herein to describe various elements, components, regions, layers and / or sections. These elements, components, regions, layers, and / or sections should not be limited by these terms. These terms are only used to distinguish one element, component, region, layer, or section from another element, component, region, layer, or a section. Thus, a first element, component, region, layer, or section discussed below could be termed a second element, component, region, layer, or section without departing from the teachings of example aspects.

[0056] Spatially relative terms, such as, “ "beneath," "below," "lower," "above," "upper," “upward,” “downward,” “top,” “bottom,” and the like, can be used herein for ease of description to describe one element or feature's relationship to another element(s) or feature! s) as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is turned over, elements described as "below" or "beneath" other elements or features would then be oriented "above" the other elements or features. Thus, the term "below" can encompass both an orientation of above and below. The device can be otherwise oriented (rotated 90 degrees or at other orientations), and the spatially relative descriptors used herein are interpreted accordingly.

[0057] Terms such as “proximal,” “distal,” “ radially outward,” “radially inward,” “outer,” “inner,” and “side” describe the orientation and / or location of portions of the components or elements within a consistent but arbitrary frame of reference which is madeAttorney Docket No. 10046-659W018551 WAN clear by reference to the text and the associated drawings describing the components or elements under discussion. Such terminology can include the words specifically mentioned above, derivatives thereof, and words of similar import. Similarly, the terms “first,” “second,” and other such numerical terms referring to structures neither imply a sequence nor order unless clearly indicated by the context.

[0058] As used herein, the term "substantially" means that the subsequently described event or circumstance completely occurs or that the subsequently described event or circumstance generally, typically, or approximately occurs.

[0059] Still further, the term “substantially” can, in some aspects, refer to at least about 90 %, at least about 91 %, at least about 92 %, at least about 93 %, at least about 94 %, at least about 95 %, at least about 96 %, at least about 97 %, at least about 98 %, at least about 99 %, or about 100 % of the stated property, component, composition, or other condition for which substantially is used to characterize or otherwise quantify an amount.

[0060] As used herein, the term “substantially,” in, for example, the context “substantially identical” or “substantially similar,” refers to a method or a system, or a component that is at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, or about 100% by similar to the method, system, or the component it is compared to.

[0061] Compounds are described using standard nomenclature. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as is commonly understood by one of skill in the art to which this disclosure belongs.

[0062] Certain materials, compounds, compositions, and components disclosed herein can be obtained commercially or readily synthesized using techniques generally known to those of skill in the art. For example, the starting materials and reagents used in preparing the disclosed compounds and compositions are either available from commercial suppliers, such as Sigma- Aldrich (formerly MilliporeSigma, Burlington, MA) or Thermo Fisher Scientific Inc. (Waltham, MA), or are prepared by methods known to those skilled in the art following procedures set forth in references such as Fieser and Fieser's Reagents for Organic Synthesis (John Wiley and Sons, 2007): Organic Reactions (John Wiley and Sons, 2004); March's Advanced Organic Chemistry, (John Wiley and Sons, 8thEdition); and Larock's Comprehensive Organic Transformations (John Wiley and Sons, 3rdedition, 2017).

[0063] Some aspects described herein relate to systems and methods. In certain aspects, the systems can comprise computers, processing devices, controllers, and the like. In otherAttorney Docket No. 10046-659W018551 WAN aspects, the methods can be computer-implemented. That is, where the method or other events are described herein, it should be understood that they may be performed by a computing device having a processor and a memory. Memory of a computing device is also referred to as a non-transitory computer-readable medium, which can include instructions or computer code for performing various computer-implemented operations. The computer- readable medium (or processor-readable medium) is non-transitory in the sense that it does not include transitory propagating signals per se (e.g., a propagating electromagnetic wave carrying information on a transmission medium such as space or a cable). The media and computer code (also referred to as code) may be those designed and constructed for a specific purpose or purpose. Examples of non-transitory computer-readable media include but are not limited to magnetic storage media such as hard disks, floppy disks, and magnetic tape; optical storage media such as Compact Disc / Digital Video Discs (CD / DVDs), Compact Disc -Read Only Memories (CD-ROMs), and holographic devices; magneto-optical storage media such as optical disks; carrier wave signal processing modules, Read-Only Memory (ROM), Random-Access Memory (RAM) and / or the like. One or more processors can be communicatively coupled to the memory and operable to execute the code stored on the non-transitory processor-readable medium. Examples of processors include general purpose processors (e.g., CPUs), Graphical Processing Units, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Digital Signal Processor (DSPs), Programmable Logic Devices (PLDs), and the like. Examples of computer code include, but are not limited to, micro-code or micro-instructions, machine instructions, such as those produced by a compiler, code used to produce a web service, and files containing higher-level instructions that are executed by a computer using an interpreter. For example, aspects may be implemented using imperative programming languages (e.g., C, Fortran, etc.), functional programming languages (Haskell, Erlang, etc.), logical programming languages (e.g., Prolog), object-oriented programming languages (e.g., Java, C++, etc.) or other suitable programming languages and / or development tools. Additional examples of computer code include but are not limited to, control signals, encrypted code, and compressed code.

[0064] In one aspect, a Non-Invasive EEG / Ultrasound Stimulation Electronic Patch device is provided.

[0065] In some aspects, the device can be configured to be work in proximity to a subject’s head.Attorney Docket No. 10046-659W018551 WAN

[0066] In some aspects, the device can be configured to obtain electroencephalogram (EEG) data from the subject. In some aspects, the device can obtain the EEG data via one or more sensors. In some aspects, the one or more sensors include an acoustic hydrogel.

[0067] In some aspects, the device can be configured to provide non-invasive ultrasound stimulation to the subjects subthalamic nucleus (STN). In some aspects, the device can provide ultrasound stimulation via a wearable transducer.

[0068] In some aspects, the device can enhance rapid eye movement (REM) sleep. In some aspects, the device can enhance the duration of REM sleep.

[0069] In some aspects, the device can further include an integrated Concentric Ring Array Transducer (CRUTA). In some aspects, the CRUTA can be for adjustable focal depth in targeting the STN. In some aspects, the CRUTA can be for non-invasive neuromodulation of the STN in REM sleep enhancement.

[0070] In some aspects, the device can further include a long-term stable bioadhesive acoustic couplant for applying the ultrasound stimulation.

[0071] In some aspects, the device can be configured for facial feature conformation.

[0072] In some aspects, the device can further include one or more two-dimensional (2D) array transducers. In some aspects, the one or more 2D array transducers can be used for beamsteering and beamfocusing to target the subject’s STN.

[0073] In some aspects, the device can be operatively coupled to an external ultrasound generator or a wireless ultrasound device.

[0074] In some aspects, the one or more sensors each include a hydrogel.

[0075] In some aspects, the one or more sensors can be fixably attached to a bioadhesive elastomer substrate.

[0076] In another aspect, a wearable device is provided.

[0077] In some aspects, the wearable device can include a bioadhesive elastomer substrate.

[0078] In some aspects, the wearable device can include one or more hydrogel couplants. In some aspects, the one or more hydrogel couplants can each include an acoustic lens and a hydrogel. In some aspects, the one or more hydrogel couplants can each include a hydrogel coating on an acoustic lens. In some aspects, the one or more hydrogel couplants can be fixably attached to the bioadhesive polymer substrate.

[0079] In some aspects, the wearable device can include an ultrasound transducer or device.Attorney Docket No. 10046-659W018551 WAN

[0080] In some aspects, the wearable device can be configured to adhere to a subject’s skin during sleep.

[0081] In some aspects, the wearable device can be in electronic communication with at least one of a controller and an ultrasound generator.

[0082] In some aspects, the controller can be configured to control the ultrasound stimulation. In some aspects, the controller can be configured to control the ultrasound stimulation based, at least in part, on analysis of EEG data obtained via the one or more acoustic hydrogel couplants.

[0083] In some aspects, the controller is configured to provide control signals for controlling operations of the wearable device. In some aspects, the controller can provide control signals via computer readable instructions or electronic circuitries.

[0084] In some aspects, the wearable device can include an integrated Concentric Ring Array Transducer (CRUTA). In some aspects, the CRUTA can be fur adjustable focal depth in targeting the STN for non-invasive neuromodulation of the STN in REM sleep enhancement.

[0085] In some aspects, the wearable device can include one or more two-dimensional (2D) array transducers. In some aspects, the one or more 2D array transducers can be used for beamsteering and beamfocusing to target the subject’s STN.

[0086] In some aspects, the hydrogel can be formed from a first monomer compri ing one or more ion-forming moieties. In some aspects, the hydrogel can be further formed from a polyol. In some aspects, the hydrogel can be further formed from water.

[0087] In some aspects, the first monomer and water can have a ratio by weight from about 1: 1 to about 1:4, for example, from about 1: 1 to about 1:2, from about 1: 1 to about 1:3, from about 1:2 to about 1:4, from about 1:2 to about 1:3, or from about 1:3 to about 1:4. In some aspects, the first monomer and water have a ratio by weight of about 1: 1. In some aspects, the first monomer and water can have a ratio by weight of about 1:2. In some aspects, the first monomer and water can have a ratio by weight of about 1:3. In some aspects, the first monomer and water can have a ratio by weight of about 1:4.

[0088] In some aspects, the polyol can be present in an amount from about 10% to about 60% by weight based on the weight of the hydrogel, for example, from about 10% to about 55%, about 10% to about 50%, about 10% to about 45%, about 10% to about 40%, about 10% to about 35%, from about 10% to about 30%, from about 10% to about 25%, about 10% to about 20%, about 10% to about 15%, about 15% to about 60%, about 1 % to about 55%, about 15%’ to about 50%, about 15% to about 45%’, about 15%’ to about 40%, about 15% toAttorney Docket No. 10046-659W018551 WAN about 35%, about 15% to about 30%, about 15% to about 25%, about 20% to about 30%, about 20% to about 50%, about 20% to about 60%, about 20% to about 40%, about 20% to about 35%, about 20% to about 0%, about 20% to about 25%, about 25% to about 60%, about 25% to about 50%, about 25% to about 40%, about 25% to about 35%, about 25% to about 30%, about 30% to about 60%, about 30% to about 50%, about 30% to about 40%, about 30% to about 35%, or about 35% to about 40% by weight based on the weight of the hydrogel. In some aspects, the polyol can be present in an amount of about 10%’ by weight based on the weight of the hydrogel. In some aspects, the polyol can be present in an amount of about 15% by weight based on the weight of the hydrogel. In some aspects, the polyol can be present in an amount of about 20% by weight based on the weight of the hydrogel. In some aspects, the polyol can be present in an amount of about 25% by weight based on the weight of the hydrogel. In some aspects, the polyol can be present in an amount of about 30% by weight based on the weight of the hydrogel. In some aspects, the polyol can be present in an amount of about 35% by weight based on the weight of the hydrogel. In some aspects, the polyol can be present in an amount of about 40% by weight based on the weight of the hydrogel. In some aspects, the polyol can be present in an amount of about 50% by weight based on the weight of the hydrogel. In some aspects, the polyol can be present in an amount of about 60% by weight based on the weight of the hydrogel.

[0089] In some aspects, the polyol can be present in an amount from about 0% to about 60% by weight based on the weight of the hydrogel. In some aspects, the polyol can be present in an amount of about 60% by weight or more based on the weight of the hydrogel.

[0090] In some aspects, the hydrogel can be formed from a) a first monomer comprising one or more ion-forming moieties; b) a polyol; and c) water; wherein the first monomer and water have a ratio by weight from about 1: 1 to about 1:4; and wherein the polyol is present in an amount from about 10% to about 40% by weight based on the weight of the hydrogel.

[0091] In some aspects, the hydrogel can be formed from a) a first monomer comprising one or more ion-forming moieties; b) a polyol; and c) water; wherein the first monomer and water have a ratio by weight from about 1:1 to about 1:4; and wherein the polyol is present in an amount from about 10% to about 60% by weight based on the weight of the hydrogel.

[0092] In some aspects, the first monomer includes one or more anion-forming moieties, one or more cation-forming moieties, or combinations thereof.

[0093] In some aspects, the first monomer can include one or more anion-forming moieties. An “anion” is any molecule, portion of a molecule (e.g., zwitterion), a cluster of molecules, molecular complex, moiety, or atom that contains a net negative charge or thatAttorney Docket No. 10046-659W018551 WAN can be made to contain a net negative charge. The term “anion-forming moiety” is used herein to specifically refer to a moiety that can be converted to an anion via a chemical reaction (e.g., deprotonation). Representative examples of such first monomers include but are not limited to, vinyl sulfonic acid, styrene sulfonic acid, allyl sulfonic acid, ethyl acrylate sulfonic acid, butyl acrylate sulfonic acid, acryl sulfonic acid, methacryl sulfonic acid, 2- acrylamido-2-methylpropane sulfonic acid, vinyl carboxylic acid, styrene carboxylic acid, allyl carboxylic acid, acryl carboxylic acid, methacryl carboxylic acid, 2-acrylamido-2-methylpropane carboxylic acid, isoprene carboxylic acid, polyacrylic acid, salts thereof, or combinations thereof. In some particular aspects, the first monomer includes 2-acrylamido-2-methylpropane sulfonic acid (AMPS) and / or a salt thereof.

[0094] In other aspects, the first monomer can include one or more cation-forming moieties. A “cation” is any molecule, portion of a molecule (e.g., zwitterion), a cluster of molecules, molecular complex, moiety, or atom containing a net positive charge or that can be made to contain a net positive charge. The term “cation-forming moiety” is used herein to specifically refer to a moiety that can be converted to a cation via a chemical reaction (e.g., protonation or alkylation). Representative examples of such first monomers include but are not limited to, vinyl pyridine (such as 2-vinyl pyridine or 4-vinyl pyridine), an aminoethyl methacrylate (such a 2-aminoethyl methacrylate or 2-(dimethylamino)ethyl methacrylate), or 2,2,6,6-tetramethyl-piperidenyloxyl-4-yl methacrylate, or any combination thereof.

[0095] In some aspects, the polyol can be a diol, a triol, or the like. Representative examples of suitable polyols include but are not limited to, glycerol, trimethylolpropane, pentaerythritol, ethylene glycol, 1,5 -butanediol, 1,2,5-hexanetriol, diethylene glycol, triethylene glycol, maltitol, sorbitol, xylitol, erythritol, isomalt, malic acid, a polyalkylene glycol (such as polyethylene glycol or polypropylene glycol), polyvinyl alcohol, a polyether polyol, a polyester polyol, or combinations thereof. In some particular aspects, the polyol includes glycerol.

[0096] In some aspects, the hydrogel can be formed from a) a first monomer comprising one or more ion-forming moieties; b) a polyol; and c) water; and further from: d) a crosslinker, wherein the first monomer and water have a ratio by weight from about 1:1 to about 1:4; and wherein the polyol is present in an amount from about 10% to about 40% by weight based on the weight of the hydrogel.

[0097] In some aspects, a hydrogel can be formed from a) a first monomer comprising one or more ion-forming moieties; b) a polyol; and c) water; and further from: d) a crosslinker, wherein the first monomer and water have a ratio by weight from about 1: 1 toAttorney Docket No. 10046-659W018551 WAN about 1:4; and wherein the polyol is present in an amount from about 10% to about 60% by weight based on the weight of the hydrogel.

[0098] In some aspects, the hydrogel can be substantially crosslinked. In further aspects, the hydrogel is crosslinked. Any known crosslinkers in the art can be utilized. For example, and without limitation, the crosslinker can include N, N-methylenebis(acrylamide), N, N- dimethylacrylamide (DMAA), or polyfethylene glycol) diacrylate (PEGDA), or any combination thereof. However, it is further understood that any other crosslinkers suitable for the desired application can be used. In still further aspects, if the crosslinker is present, the crosslinking of the hydrogel can be achieved by any known and suitable for the desired application. For example, and without limitations, the crosslinking of the hydrogel can be achieved through thermal crosslinking, radiation-induced crosslinking, e-beam-induced crosslinking, and the like, or any combination thereof.

[0099] In some aspects, the hydrogel can be formed from a) a first monomer comprising one or more ion-forming nioieties; b) a polyol; c) water; and d) optionally a crosslinker; and further from e) an initiator, wherein the first monomer and water have a ratio by weight from about 1:1 to about 1:4; and wherein the polyol is present in an amount from about 10% to about 40% by weight based on the weight of the hydrogel.

[0100] In some aspects, the hydrogel can be formed from a) a first monomer comprising one or more ion-forming moieties; b) a polyol; c) water; and d) optionally a crosslinker; and further from e) an initiator, wherein the first monomer and water have a ratio by weight from about 1:1 to about 1:4; and wherein the polyol is present in an amount from about 10% to about 60% by weight based on the weight of the hydrogel.

[0101] In some aspects, the initiator can include a photoinitiator. Any known photoinitiators in the art can be utilized. Representative examples of photoinitiators that can be used include but are not limited to 2-hydroxy-4’-(2-hydroxyethoxy)-2-methylpropiophenone, 4,4’-azo-bis(4-cyanopentanoic acid), or 40benzoylphenyl acrylate (4-ABP), or any combination thereof.

[0102] In some alternative aspects, the initiator can include a radical initiator. Any known radical initiators in the art and suitable for the desired application can be used. In some alternative aspects, the radical initiator can include an azo compound, an organic peroxide, an inorganic peroxide, or any combination thereof. Representative examples of radical initiators which can be used include but are not limited to, azobisisobutyronitrile (AIBN), 1,1’-azobis(cyclohexanecarbonitrile) (ABCN), di-tert-butyl peroxide, benzoyl peroxide, methyl ethyl ketone peroxide, acetone peroxide, or a peroxydisulfate salt (such as sodium persulfate,Attorney Docket No. 10046-659W018551 WAN potassium persulfate, or ammonium persulfate), or any combination thereof. In some alternative aspects, the radical initiator includes ammonium persulfate.

[0103] In some alternative aspects, the radical initiator can be used in combination with a catalyst. For example, when ammonium persulfate can be used as the radical initiator, tetramethylethylenediamine (TMEDA) may also be used as a catalyst.

[0104] In some aspects, the hydrogel can be substantially adhesive. In other aspects, the hydrogel is adhesive. In still further aspects, the hydrogel can have an adhesion force of about 1 N / m or greater as determined by ASTM 02861-87(1998) (August 1, 2.017), for example of about 1 N / m or greater, 2 N / m or greater, 3 N / m or greater, 4 N / m or greater, or 5 N / m or greater. In some aspects, the hydrogel is adhesive to a biological tissue or organ (e.g., skin). A “biological tissue,” as used herein, refers to an assembly of similar cells and their extracellular matrix from the same embryonic origin that carry out a specific function. An “organ,” as used herein, refers to a collection of tissues joined in a structural unit to serve a common function. “Skin,” as used herein, refers to a flexible layer or layers of outer tissue covering the body of a vertebrate mammal. In humans, the skin comprises up to several layers of ectodermal tissue comprising the epidermis (comprising the stratum corneum, stratum lucidum, stratum granulosum, stratum spinosum, and stratum basale), the dermis, and the hypodermis or subcutaneous tissue.

[0105] In some aspects, the hydrogel can exhibit substantially no swelling over a period of about 10 days, about 20 days, about 30 days, about 40 days, about 50 days, about 60 days, or about 100 days. It is understood that in other aspects, the hydrogel exhibits substantially no swelling over a period of about 30 days. In other aspects, the hydrogel exhibits substantially no swelling over a period of about 50 days.

[0106] In still further aspects, the hydrogel can be moldable to form any desired shape. In yet other aspects, any known in the art shapes can be formed. The shapes can be irregular or regular. In yet other aspects, the hydrogel can be 3D printed to form the desired shapes. In still further aspects, the desired shape can comprise circular, square, rectangular shape, microneedles, or micropillars shape.

[0107] In some aspects, the bioadhesive elastomer can be formed from a polysiloxane. In some aspects, the bioadhesive elastomer can be further formed from a polyamine. In some aspects, the bioadhesive elastomer can be further formed from one or more additives.

[0108] In some aspects, the polysiloxane can be selected from polydimethylsiloxane (PDMS), polymethylhydrosiloxane (PMHS), polymethylphenyl siloxane (PMPS), polydiphenylsiloxane, polydiethylsiloxane, an amino-functionalized polysiloxane, an epoxy¬Attorney Docket No. 10046-659W018551 WAN functionalized poly siloxane, an acrylate- or methacrylate-functionalized poly siloxane, or combinations thereof. In some aspects, the polysiloxane can include polydimethylsiloxane.

[0109] In some aspects, the polyamine can be selected from polyethylenimine (PEI), polypropyleneiniine (PPI), poly(amidoamine) (PAM AM), or combinations thereof. In some aspects, the polyamine can include polyethyleneimine (PEI).

[0110] Representative examples of additives which may be used include, but are not limited to, reinforcing fillers (such as fumed silica or precipitated silica), plasticizers and processing aids (such as silicon oils or hydrocarbon oils), crosslinking and curing agents (such as peroxides, for example dicumyl peroxide or benzoyl peroxide, and platinum catalysts), stabilizers (such as heat stabilizers, for example zinc oxide, iron oxide, and cerium oxide, UV stabilizers, such as hindered amine light stabilizers (HALS), benzotriazoles, and titanium dioxide, and antioxidants), pigments and colorants (such as inorganic pigments, for example titanium dioxide, iron oxide, and carbon black, and organic pigments), flame retardants (such as platinum catalysts or other chemical flame retardants), fluorosilicone polymers, vinyl-functional silicones, nanoclays, carbon nanotubes, graphene, antimicrobial agents (such as silver compounds or zinc pyrithione), optical brighteners, mold release agents, lubricants, and flow promoters.

[0111] In some aspects, a bioadhesive elastomer is provided formed from a poly siloxane, a polyamine, and optionally one or more additives. In some aspects, the polysiloxane can be selected from polydimethylsiloxane (PDMS), polymethylhydrosiloxane (PMHS), polymethylphenyl siloxane (PMPS), polydiphenylsiloxane, polydiethylsiloxane, an amino¬ functionalized polysiloxane, an epoxy-functionalized polysiloxane, an acrylate- or methacrylate-functionalized polysiloxane, or combinations thereof. In some aspects, the polysiloxane can include polydimethylsiloxane. In some aspects, the polyamine can be selected from polyethylenimine (PEI), polypropyleneimine (PPI), poly(amidoamine) (PAMAM), or combinations thereof. In some aspects, the polyamine can include polyethyleneimine (PEI).

[0112] In another aspect, an article is provided including a bioadhesive elastomer as described herein. In some aspects, the article can be a device. In some aspects, the article can be a medical device.

[0113] In another aspect, a sy stem is provided. In some aspects, the system can include at least one device as described herein. In some aspects, the system can include an ultrasound generator in electronic communication with the at least one device. In some aspects, theAttorney Docket No. 10046-659W018551 WAN system can include a controller operatively coupled to the ultrasound generator and the at least one device.

[0114] In some aspects, the device can be used for treatment of at least one of:Parkinson’s disease, epilepsy, Alzheimer’s disease, stroke, traumatic brain injury, psychiatric disorders (e.g., depression, anxiety, obsessive-compulsive disorder), pain, (e.g., brain stimulation, spinal cord stimulation, or peripheral stimulation), peripheral chronic joint pain, overactive bladder syndrome, sleep disorders (e.g., sleep apnea, redness leg syndrome), carpal tunnel syndrome, visual prosthetics and / or blindness, or mood disorders, or any combination thereof.

[0115] In some aspects, the device can be used for increasing a duration and / or a frequency of rapid eye movement (REM) sleep in a subject.

[0116] Sleep in a subject (such as sleep in a human, for example) comprises a cyclic architecture of non-rapid eye movement (NREM) stages Nl, N2, N3, followed by rapid eye movement (REM) sleep, repeating every approximately 90-110 minutes for 4-5 cycles per typical adult night. Sleep is organized into consolidated cycles progressing from Nl to N2 to N3, then returning to lighter NREM and transitioning into REM, with REM episodes lengthening across the night while deep N3 diminishes in later cycles. In healthy human adults, about 75-80% of total sleep time is NREM (largely N2) and about 20-25% is REM, with a complete cycle averaging -90-110 minutes and the first REM period being shortest.

[0117] Nl is the lightest stage of sleep marking sleep onset, characterized by low-amplitude mixed-frequency EEG with easy arousability and brief duration during initial dozing. Physiologically, there is gradual reduction in muscle tone and slowed eye movements, serving as a transitional phase toward more stable NREM sleep.

[0118] N2 represents stable light-to-intemiediate sleep and constitutes the largest proportion of adult sleep time within NREM. It is defined by EEG features including sleep spindles and K-compiexes with reduced chin EMG compared to wake, and functions as a gatekeeper stage preceding REM transitions in the cycle.

[0119] N3 is deep, slow-wave sleep, characterized by high-amplitude, low-frequency delta activity and associated with restorative physiological processes and homeostatic recovery. Modern AASM scoring consolidates the historical R& K stages 3 and 4 into N3, reflecting the slow-wave component and distinguishing it from lighter stages by delta power criteria.

[0120] REM is marked by low-amplitude mixed-frequency EEG, rapid eye movements, and skeletal muscle atonia with preserved phasic twitches, and is the primary stage associatedAttorney Docket No. 10046-659W018551 WAN with vivid dreaming. Across the night, REM episodes lengthen to as much as ~60 minutes in later cycles, contributing roughly one-quarter of total sleep in human adults under typical conditions.

[0121] A typical hypnogram shows early-night predominance of N3 and late-night predominance of REM, with cycles ordered N1 — >■ N2 N3 N2 — >■ REM and repeating 4-5 times per night. The first NREM-REM cycle tends to be shorter (-70-100 minutes), with subsequent cycles somewhat longer (-90-120 minutes), consistent with established adult sleep physiology.

[0122] Current staging nomenclature follows the American Academy of Sleep Medicine (AASM) manual: W (wake), Nl, N2, N3 for NREM, and R for REM, superseding R& K Sl- S4 by consolidating slow-wave sleep as N3. AASM scoring criteria specify characteristic EEG, EOG, and EMG features for each stage, including the requirement set for REM of low-amplitude mixed-frequency EEG, reduced chin tone, and rapid eye movements when present.

[0123] A decrease in REM sleep duration or frequency is associated with a variety of neurological, psychiatric, and sleep disorders. In some aspects, the devices here can be used in the treatment of a decrease in REM sleep duration or frequency as a result of a neurological, psychiatric, or sleep disorder, including, but not limited to, obstructive sleep apnea, traumatic brain injury (TBI), major depressive disorder, REM sleep behavior disorder (RBD), narcolepsy, Addison’s disease, restless leg syndrome (RES), post-traumatic stress disorder (PTSD), and anxiety disorders.

[0124] In some aspects, a decrease in REM sleep duration or frequency can be associated with obstructive sleep apnea. Individuals with sleep apnea often experience reduced time spent in REM sleep due to frequent arousal and airway collapse, leading to sleep fragmentation.

[0125] In some aspects, a decrease in REM sleep duration or frequency can be associated with traumatic brain injury (TBI). Patients with TBI typically have shorter REM sleep duration and greater difficulty initiating and maintaining sleep.

[0126] In some aspects, a decrease in REM sleep duration or frequency can be associated with major depressive disorder. Depression can alter sleep architecture, frequently causing decreased REM latency (i.e., earlier onset of REM) but sometimes reduced REM duration, especially in recurrent or severe cases. Antidepressants, especially SSRIs and tricyclics, can suppress REM sleep duration.

[0127] In some aspects, a decrease in REM sleep duration or frequency can be associated with REM sleep behavior disorder (RBD). Although RBD is primarily characterized by lossAttorney Docket No. 10046-659W018551 WAN of muscle atonia during REM, associated neurodegenerative conditions such as Parkinson’s disease, Lewy body dementia, and multiple system atrophy (MSA) can also involve disrupted or reduced REM sleep microstructure and duration.

[0128] In some aspects, a decrease in REM sleep duration or frequency can be associated with narcolepsy. Narcolepsy type 1, associated with orexin deficiency, may destabilize REM sleep, sometimes leading to a decrease in REM sleep duration as well as REM behavior disorder symptoms.

[0129] In some aspects, a decrease in REM sleep duration or frequency can be associated with Addison’s Disease. This endocrine disorder can lead to decreased REM sleep, especially when untreated.

[0130] In some aspects, a decrease in REM sleep duration or frequency can be associated with restless leg syndrome (RLS). RES is linked with sleep deprivation, which can reduce REM sleep indirectly through fragmentation of sleep cycles.

[0131] In some aspects, a decrease in REM sleep duration or frequency can be associated with post-traumatic stress disorder (PTSD). PTSD can alter REM sleep structure, contributing to disturbances such as nightmares and fragmented REM phases.

[0132] In some aspects, a decrease in REM sleep duration or frequency can be associated with an anxiety disorder. Chronic anxiety can diminish REM sleep and disrupt overall sleep quality.

[0133] Sleep is tracked using EEG (electroencephalogram) by recording the brain’s electrical activity by detecting voltage fluctuations resulting from ionic current flows within the neurons of the brain. EEG does not measure the activity of a single neuron but records the combined electrical activity of thousands of neurons, creating signals large enough for detection.

[0134] The EEG captures brain waves as oscillating lines, which are then analyzed for characteristic patterns corresponding to different sleep stages. EEG is used to differentiate the various stages of sleep. N1 shows low amplitude, mixed frequency brain activity, representing the transition from wakefulness to sleep. N2 is characterized by the presence of sleep spindles and K-complexes, identifiable patterns of brain waves unique to this stage. N3 shows high-amplitude, low-frequency waves known as delta waves. EEG of REM resembles wakefulness, with low-amplitude, mixed frequency activity. REM sleep is distinguished from wakefulness mainly by the absence of muscle tone and the presence of rapid eye movements.

[0135] After recording, EEG signals can be digitized and analyzed using computer-based algorithms. Frequency, amplitude, and other features can be extracted, often using methodsAttorney Docket No. 10046-659W018551 WAN like Fast Fourier Transform (FFT) and wavelet transforms to classify the signals into distinct sleep stages. Automated systems can assist with sleep staging by preprocessing the EEG data, extracting features, and applying machine learning classifiers for improved accuracy in identifying sleep stages and assessing sleep quality.

[0136] In view of the described articles, devices, compositions, and methods, certain more particular aspects of the disclosure are described below. These particularly recited aspects should not, however, be interpreted to have any limiting effect on any different claims containing different or more general teachings described herein, or that the “particular” aspects are somehow limited in some way other than the inherent meanings of the language and formulae literally used therein.

[0137] Aspect 1. A Non-invasive EEG / Ultrasound Stimulation Electronic Patch (NEUSleeP) device configured to be worn in proximity to a subject’s head, the device configured to:obtain, via one or more sensors (e.g., acoustic hydrogels), electroencephalogram (EEG) data from the subject; andprovide, via a wearable ultrasound transducer, non-invasive ultrasound stimulation to the subject’s subthalamic nucleus (STN) to enhance rapid eye movement (REM) sleep.

[0138] Aspect 2. The device of any aspect herein, such as aspect 1, wherein the wearable ultrasound transducer can be adjustable for focal depth targeting of the STN.

[0139] Aspect 3. The device of any aspect herein, such as aspect 1, further including:an integrated Concentric Ring Array Transducer (CRUTA) for adjustable focal depth in targeting STN for non-invasive neuromodulation of STN in REM sleep enhancement.

[0140] Aspect 4. The device of any aspect herein, such as aspect 1 or 3, further including:a long-term stable bioadhesive acoustic couplant for applying the ultrasound stimulation.

[0141] Aspect 5. The device of any aspect herein, such as any one of aspects 1-4, wherein the device can be configured for facial feature conformation.

[0142] Aspect 6. The device of any aspect herein, such as any one of aspects 1-5, further including one or more two-dimensional (2D) array transducers, wherein the one or more two- dimensional array transducers can be used for beamsteering and beamfocusing to target the subject’s STN.Attorney Docket No. 10046-659W018551 WAN

[0143] Aspect 7. The device of any aspect herein, such as any one of aspects 1-6, wherein the device can be operatively coupled to an external ultrasound generator or a wireless ultrasound device.

[0144] Aspect 8. The device of any aspect herein, such as any one of aspects 1-7, wherein the one or more sensors each include a hydrogel.

[0145] Aspect 9. The device of any aspect herein, such as aspect 8, wherein each hydrogel of the one or more sensors can be formed from:a) a first monomer including one or more ion-forming moieties;b) a polyol; andc) water;wherein the first monomer and water have a ratio by weight from about 1:1 to about 1:4; andwherein the polyol can be present in an amount from about 10% to about 40% by weight based on the weight of the hydrogel.

[0146] Aspect 10. The device of any aspect herein, such as aspect 9, wherein the first monomer includes one or more anion-forming moieties, one or more cation-forming moieties, or combinations thereof.

[0147] Aspect 11. The device of any aspect herein, such as aspect 9 or 10, wherein the first monomer includes one or more anion-forming moieties.

[0148] Aspect 12. The device of any aspect herein, such as any one of aspects 9-11, wherein the first monomer includes vinyl sulfonic acid, styrene sulfonic acid, allyl sulfonic acid, ethyl acrylate sulfonic acid, butyl acrylate sulfonic acid, aery) sulfonic acid, methacryl sulfonic acid, 2-acrylamido-2-methylpropane sulfonic acid, vinyl carboxylic acid, styrene carboxylic acid, allyl carboxylic acid, acryl carboxylic acid, methacryl carboxylic acid, 2-acrylamido-2-methylpropane carboxylic acid, isoprene carboxylic acid, polyacrylic acid, salts thereof, or combinations thereof.

[0149] Aspect 13. The device of any aspect herein, such as any one of aspects 9-12, wherein the first monomer includes 2-acrylamido-2-methylpropane sulfonic acid (AMPS) or a salt thereof.

[0150] Aspect 14. The device of any aspect herein, such as any one of aspects 9-13, wherein the polyol includes glycerol, trimethylolpropane, pentaerythritol, ethylene glycol, 1,5-butanediol, 1,2, 5 -hexanetriol, diethylene glycol, triethylene glycol, maltitol, sorbitol, xylitol, erythritol, isomalt, malic acid, a polyalkylene glycol (such as polyethylene glycol orAttorney Docket No. 10046-659W018551 WAN polypropylene glycol), a polyvinyl alcohol, a polyether polyol, a polyester polyol, or combinations thereof.

[0151] Aspect 15. The device of any aspect herein, such as any one of aspects 9-14, wherein the polyol includes glycerol.

[0152] Aspect 16. The device of any aspect herein, such as any one of aspects 9-15, wherein the hydrogel can be formed from a), b), and c), and further from:d) a crosslinker.

[0153] Aspect 17. The device of any aspect herein, such as aspect 16, wherein the crosslinker includes N, N-methylenebis(acrylamide), N, N-dimethylacrylamide (DMAA), or polyethylene glycol) diacrylate (PEGDA), or a combination thereof.

[0154] Aspect 18. The device of any aspect herein, such as aspect 16 or aspect 17, wherein the hydrogel can be substantially crosslinked.

[0155] Aspect 19. The device of any aspect herein, such as any one of aspects 9-18, wherein the hydrogel can be formed from a), b), and c), optionally d), and further from:e) an initiator.

[0156] Aspect 20. The hydrogel of aspect 19, wherein the initiator can be a radical initiator.

[0157] Aspect 21. The hydrogel of aspect 20, wherein the radical initiator includes an azo compound, an organic peroxide, an inorganic peroxide, or a combination thereof.

[0158] Aspect 22. The hydrogel of aspect 20 or 21, wherein the radical initiator includes azobisisobutyronitrile (AIBN), l,r-azobis(cyclohexanecarbonitrile) (ABCN), di-tert-butyl peroxide, benzoyl peroxide, methyl ethyl ketone peroxide, acetone peroxide, a peroxydisulfate salt (such as ammonium persulfate), or a combination thereof.

[0159] Aspect 23. The device of any aspect herein, such as any one of aspects 20-22, wherein the radical initiator can be ammonium persulfate.

[0160] Aspect 24. The device of any aspect herein, such as any one of aspects 20-23, wherein the radical initiator can be used in combination with a catalyst.

[0161] Aspect 25. The device of any aspect herein, such as aspect 24, wherein the catalyst includes tetramethylethylenediamine (TMEDA).

[0162] Aspect 26. The device of any aspect herein, such as any one of aspects 1-25, wherein the one or more sensors can be fixably attached to a bioadhesive elastomer substrate.

[0163] Aspect 27. The device of any aspect herein, such as aspect 26, wherein the bioadhesive elastomer substrate can be formed from:a) a poly siloxane;Attorney Docket No. 10046-659W018551 WAN b) a polyamine; andc) optionally one or more additives.

[0164] Aspect 28. The device of any aspect herein, such as aspect 27, wherein the polysiloxane can be selected from polydimethylsiloxane (PDMS), polymethylhydrosiloxane (PMHS), polymethylphenyl siloxane (PMPS), polydiphenylsiloxane, polydiethylsiloxane, an amino-functionalized polysiloxane, an epoxy-functionalized polysiloxane, an acrylate- or methacrylate-functionalized polysiloxane, or combinations thereof.

[0165] Aspect 29. The device of any aspect herein, such as aspect 27 or aspect 28, wherein the polyamine can be selected from polyethylenimine (PEI), polypropyleneimine (PPI), poly(amidoamine) (PAMAM), or combinations thereof.

[0166] Aspect 30. The device of any aspect herein, such as any one of aspects 27-29, wherein the polyamine can be polyethylenimine (PEI).

[0167] Aspect 31. A wearable device including:a bioadhesive elastomer substrate;one or more acoustic hydrogel couplants (e.g., each including an acoustic lens and hydrogel or hydrogel coating on an acoustic lens) fixably attached to the bioadhesive elastomer substrate; andan ultrasound transducer or device, wherein the wearable device can be configured to adhere to a subject’s skin during sleep.

[0168] Aspect 32. The device of any aspect herein, such as aspect 31, wherein the wearable device can be in electronic communication with at least one of a controller and an ultrasound generator.

[0169] Aspect 33. The device of any aspect herein, such as aspect 32, wherein the controller can be configured to control or direct ultrasound stimulation from the ultrasound transducer or device.

[0170] Aspect 34. The device of any aspect herein, such as aspect 33, wherein the controller can be configured to control the ultrasound stimulation based, at least in part, on analysis of EEG data obtained via the one or more acoustic hydrogel couplants.

[0171] Aspect 35. The device of any aspect herein, such as any one of aspects 32-34, wherein the controller can be configured, via computer readable instructions or electronic circuitries, to provide control signals for controlling operations of the wearable device.

[0172] Aspect 36. The device of any aspect herein, such as any one of aspects 31-35, further including an integrated Concentric Ring Array Transducer (CRUTA) for adjustableAttorney Docket No. 10046-659W018551 WAN focal depth in targeting STN for non-invasive neuromodulation of STN in REM sleep enhancement.

[0173] Aspect 37. The device of any aspect herein, such as any one of aspects 31-36, further including one or more two-dimensional (2D) array transducers, wherein the one or more two-dimensional array transducers can be used for beamsteering and beamfocusing to target the subject’s STN.

[0174] Aspect 38. The device of any aspect herein, such as any one of aspects 31-37, wherein each hydrogel of the one or more acoustic couplants can be formed from:a) a first monomer including one or more ion-forming moieties;b) a polyol; andc) water;wherein the first monomer and water have a ratio by weight from about 1:1 to about 1:4; andwherein the polyol can be present in an amount from about 10% to about 40% by weight based on the weight of the hydrogel.

[0175] Aspect 39. The device of any aspect herein, such as aspect 38, wherein the first monomer includes one or more anion-forming moieties, one or more cation-forming moieties, or combinations thereof.

[0176] Aspect 40. The device of any aspect herein, such as aspect 38 or 39, wherein the first monomer includes one or more anion-forming moieties.

[0177] Aspect 41. The device any one of aspects 38-40, wherein the first monomer includes vinyl sulfonic acid, styrene sulfonic acid, allyl sulfonic acid, ethyl acrylate sulfonic acid, butyl acrylate sulfonic acid, acryl sulfonic acid, methacryl sulfonic acid, 2-acrylamido-2-methylpropane sulfonic acid, vinyl carboxylic acid, styrene carboxylic acid, allyl carboxylic acid, acryl carboxylic acid, methacryl carboxylic acid, 2-acrylamido-2- methylpropane carboxylic acid, isoprene carboxylic acid, polyacrylic acid, salts thereof, or combinations thereof.

[0178] Aspect 42. The device of any aspect herein, such as any one of aspects 38-41, wherein the first monomer includes 2-acrylamido-2-methylpropane sulfonic acid (AMPS) or a salt thereof.

[0179] Aspect 43. The device of any aspect herein, such as any one of aspects 38-42, wherein the polyol includes glycerol, trimethylolpropane, pentaerythritol, ethylene glycol, 1,5-butanediol, 1,2,5-hexanetriol, diethylene glycol, triethylene glycol, maltitol, sorbitol, xylitol, erythritol, isomalt, malic acid, a polyalkylene glycol (such as polyethylene glycol orAttorney Docket No. 10046-659W018551 WAN polypropylene glycol), a polyvinyl alcohol, a polyether polyol, a polyester polyol, or combinations thereof.

[0180] Aspect 44. The device of any aspect herein, such as any one of aspects 38-43, wherein the polyol includes glycerol.

[0181] Aspect 45. The device of any aspect herein, such as any one of aspects 38-44, wherein the hydrogel can be formed from a), b), and c), and further from:d) a crosslinker.

[0182] Aspect 46. The device of any aspect herein, such as aspect 45, wherein the crosslinker includes N, N-methylenebis(acrylamide), N, N-dimethylacrylamide (DMAA), or polyethylene glycol) diacrylate (PEGDA), or a combination thereof.

[0183] Aspect 47. The device of any aspect herein, such as aspect 45 or 46, wherein the hydrogel can be substantially crosslinked.

[0184] Aspect 48. The device of any aspect herein, such as any one of aspects 38-47, wherein the hydrogel can be formed from a), b), and c), optionally d), and further from:e) an initiator.

[0185] Aspect 49. The device of any aspect herein, such as aspect 48, wherein the initiator can be a radical initiator.

[0186] Aspect 50. The device of any aspect herein, such as aspect 49, wherein the radical initiator includes an azo compound, an organic peroxide, an inorganic peroxide, or a combination thereof.

[0187] Aspect 1. The device of any aspect herein, such as aspect 49 or aspect 50, wherein the radical initiator includes azobisisobutyronitrile (AIBN), 1,1’- azobis(cyclohexanecarbonitrile) (ABCN), di-tert-butyl peroxide, benzoyl peroxide, methyl ethyl ketone peroxide, acetone peroxide, a peroxydisulfate salt (such as ammonium persulfate), or a combination thereof.

[0188] Aspect 52. The device of any aspect herein, such as any one of aspects 49-51, wherein the radical initiator can be ammonium persulfate.

[0189] Aspect 53. The device of any aspect herein, such as any one of aspects 49-52, wherein the radical initiator can be used in combination with a catalyst.

[0190] Aspect 54. The device of any aspect herein, such as aspect 53, wherein the catalyst includes tetramethylethylenediamine (TMEDA).

[0191] Aspect 55. The device of any aspect herein, such as any one of aspects 31-54, wherein the bioadhesive elastomer substrate can be formed from:a) a poly siloxane;Attorney Docket No. 10046-659W018551 WAN b) a polyamine; andc) optionally one or more additives.

[0192] Aspect 56. The device of any aspect herein, such as aspect 55, wherein the polysiloxane can be selected from polydimethylsiloxane (PDMS), polymethylhydrosiloxane (PMHS), polymethylphenyl siloxane (PMPS), polydiphenylsiloxane, polydiethylsiloxane, an amino-functionalized polysiloxane, an epoxy-functionalized polysiloxane, an acrylate- or methacrylate-functionalized polysiloxane, or combinations thereof.

[0193] Aspect 57. The device of any aspect herein, such as aspect 55 or aspect 56, wherein the polyamine can be selected from polyethylenimine (PEI), polypropyleneimine (PPI), poly(amidoamine) (PAMAM), or combinations thereof.

[0194] Aspect 58. The device of any aspect herein, such as any one of aspects 55-57, wherein the polyamine can be polyethylenimine (PEI).

[0195] Aspect 59. The device of any aspect herein, such as any one of aspects 31-58, wherein the wearable device can be configured as a cap, hat, or face-conformable attachment.

[0196] Aspect 60. The device of any aspect herein, such as any one of aspects 1-59, wherein the device can be used for treatment of at least one of:Parkinson’s disease, epilepsy, Alzheimer’s disease, stroke, traumatic brain injury, psychiatric disorders (e.g., depression, anxiety, obsessive-compulsive disorder), pain, (e.g., brain stimulation, spinal cord stimulation, or peripheral stimulation), peripheral chronic joint pain, overactive bladder syndrome, sleep disorders (e.g., sleep apnea, redness leg syndrome), carpal tunnel syndrome, visual prosthetics and / or blindness, or mood disorders, or any combination thereof.

[0197] Aspect 61. A system including:at least one device of any aspect herein, such as any one of aspects 1-60; an ultrasound generator in electronic communication with the at least one device or at least one wearable device; anda controller operatively coupled to the ultrasound generator and the at least one device or at least one wearable device.

[0198] Aspect 62. A bioadhesive elastomer formed from:a) a polysiloxane;b) a polyamine; andc) optionally one or more additional additives.

[0199] Aspect 63. The bioadhesive elastomer of any aspect herein, such as aspect 62, wherein the polysiloxane can be selected from polydimethylsiloxane (PDMS),Attorney Docket No. 10046-659W018551 WAN polymethylhydrosiloxane (PMHS), polymethylphenyl siloxane (PMPS), polydiphenylsiloxane, polydiethyl siloxane, an amino-functionalized polysiloxane, an epoxyfunctionalized polysiloxane, an acrylate- or methacrylate-functionalized polysiloxane, or combinations thereof.

[0200] Aspect 64. The bioadhesive elastomer of any aspect herein, such as aspect 62 or aspect 63, wherein the polyamine can be selected from polyethylenimine (PEI), polypropyleneimine (PPI), poly (amidoamine) (PAM AM), or combinations thereof.

[0201] Aspect 65. The bioadhesive elastomer of any aspect herein, such as any one of aspects 62-64, wherein the polyamine can be polyethylenimine (PEI).

[0202] Aspect 66. An article including a bioadhesive elastomer of any aspect herein, such as any one of aspects 62-65.

[0203] Aspect 67. The article of any aspect herein, such as aspect 66, wherein the article can be a device, such as a medical device.

[0204] Example Computing Device

[0205] It should be appreciated that the logical operations described herein with respect to the various figures may be implemented (1) as a sequence of computer-implemented acts or program modules (i.e., software) running on a computing device (e.g., the computing device described in FIG. 1), (2) as interconnected machine logic circuits or circuit modules (i.e., hardware) within the computing device and / or (3) a combination of software and hardware of the computing device. Thus, the logical operations discussed herein are not limited to any specific combination of hardware and software. The implementation is a matter of choice dependent on the performance and other requirements of the computing device. Accordingly, the logical operations described herein are referred to variously as operations, structural devices, acts, or modules. These operations, structural devices, acts and modules may be implemented in software, in firmware, in special purpose digital logic, and any combination thereof. It should also be appreciated that more or fewer operations may be performed than showm in the figures and described herein. These operations may also be performed in a different order than those described herein.

[0206] Referring to FIG. 1, an example computing device 1000 upon which embodiments of the invention may be implemented is illustrated. This disclosure contemplates that the controller(s) for operating the flexure elements and / or imaging apparatus can be implemented using computing device 1000. It should be understood that the example computing device 1000 is only one example of a suitable computing environment upon which embodiments of the invention may be implemented. Optionally, the computing device 1000 can be a 'ell-Attorney Docket No. 10046-659W018551 WAN known computing system including, but not limited to, personal computers, servers, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, network personal computers (PCs), minicomputers, mainframe computers, embedded systems, and / or distributed computing environments including a plurality of any of the above systems or devices. Distributed computing environments enable remote computing devices, which are connected to a communication network or other data transmission medium, to perform various tasks. In the distributed computing environment, the program modules, applications, and other data may be stored on local and / or remote computer storage media.

[0207] In its most basic configuration, computing device 1000 typically includes at least one processing unit 1006 and system memory 1004. Depending on the exact configuration and type of computing device, system memory 1004 may be volatile (such as random access memory (RAM)), non-volatile (such as read-only memory (ROM), flash memory, etc.), or some combination of the two. This most basic configuration is illustrated in FIG. 1 by dashed line 1002. The processing unit 1006 may be a standard programmable processor that performs arithmetic and logic operations necessary for operation of the computing device 1000. The computing device 1000 may also include a bus or other communication mechanism for communicating information among various components of the computing device 1000.

[0208] Computing device 1000 may have additional features / functionality. For example, computing device 1000 may include additional storage such as removable storage 1008 and non-removable storage 1010 including, but not limited to, magnetic or optical disks or tapes. Computing device 1000 may also contain network connection(s) 1016 that allow the device to communicate with other devices. Computing device 1000 may also have input device(s) 1014 such as a keyboard, mouse, touch screen, etc. Output device(s) 1012 such as a display, speakers, printer, etc. may also be included. The additional devices may be connected to the bus in order to facilitate communication of data among the components of the computing device 1000. All these devices are well known in the ait and need not be discussed at length here.

[0209] The processing unit 1006 may be configured to execute program code encoded in tangible, computer-readable media. Tangible, computer-readable media refers to any media that is capable of providing data that causes the computing device 1000 (i.e., a machine) to operate in a particular fashion. Various computer-readable media may be utilized to provide instructions to the processing unit 1006 for execution. Example tangible, computer-readable media may include, but is not limited to, volatile media, non-volatile media, removable mediaAttorney Docket No. 10046-659W018551 WAN and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. System memory 1004, removable storage 1008, and non-removable storage 1010 are all examples of tangible, computer storage media. Example tangible, computer-readable recording media include, but are not limited to, an integrated circuit (e.g., field- programmable gate array or application-specific IC), a hard disk, an optical disk, a magnetooptical disk, a floppy disk, a magnetic tape, a holographic storage medium, a solid-state device, RAM, ROM, electrically erasable program read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices.

[0210] In an example implementation, the processing unit 1006 may execute program code stored in the system memory 1004. For example, the bus may carry data to the system memory 1004, from which the processing unit 1006 receives and executes instructions. The data received by the system memory 1004 may optionally be stored on the removable storage 1008 or the non-removable storage 1010 before or after execution by the processing unit 1006.

[0211] It should be understood that the various techniques described herein may be implemented in connection with hardware or software or, where appropriate, with a combination thereof. Thus, the methods and apparatuses of the presently disclosed subject matter, or certain aspects or portions thereof, may take the form of program code (i.e., instructions) embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other machine-readable storage medium wherein, when the program code is loaded into and executed by a machine, such as a computing device, the machine becomes an apparatus for practicing the presently disclosed subject matter. In the case of program code execution on programmable computers, the computing device generally includes a processor, a storage medium readable by the processor (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. One or more programs may implement or utilize the processes described in connection with the presently disclosed subject matter, e.g., through the use of an application programming interface (API), reusable controls, or the like. Such programs may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case,Attorney Docket No. 10046-659W018551 WAN the language may be a compiled or interpreted language and it may be combined with hardware implementations.

[0212] Example System

[0213] FIG. 2A is an example system 200 in accordance with certain embodiments of the present disclosure. As shown in FIG. 2A, the system 200 includes a processing device 110 configured to communicate with an electrophysiological recording and ultrasound neuromodulation system 101. The processing device 110 can store, host data for use by the system 101. In various implementations, the processing device 110 and the system 101 are configured to transmit data to and receive data from one another over a network 102. The system 200 can include one or more databases, data stores, repositories, and the like. As shown, the system 200 includes database(s) 115 in communication with the system 101 and the processing device 110. In some implementations, the database(s) 115 can be hosted by the processing device 110 or the system 101. This disclosure contemplates that the system 200 can be configured for treatment of Parkinson’s disease, epilepsy, Alzheimer’s disease, stroke, traumatic brain injury, psychiatric disorders (e.g., depression, anxiety, obsessive-compulsive disorder), pain, (e.g., brain stimulation, spinal cord stimulation, or peripheral stimulation), peripheral chronic joint pain, overactive bladder syndrome, sleep disorders (e.g., sleep apnea, redness leg syndrome), carpal tunnel syndrome, visual prosthetics and / or blindness, or mood disorders, or any combination thereof.

[0214] In some implementations, as illustrated, the system 101 includes an analyzing component 104, a beamsteering / beamfocusing component 105, stimulating component 106, and a controller 108 configured to provide non-invasive stimulation to a subject. In one embodiment, the system 101 is configured to provide non-invasive stimulation to the subject’s STN to enhance REM sleep. In accordance with certain embodiments, one or more of the components of FIG. 2A may be configured to process data (e.g., EEG data from the subject) and direct a NEUSleeP device 100 positioned in proximity to a subject’s face, head, neck, and / or the like to provide non-invasive ultrasound stimulation via an ultrasound generator 112 operatively coupled to the NEUSleeP Device 100. The NEUSleeP device 100 can be or comprise a cap / hat and / or can be configured to conform to a wearer’s face. The ultrasound generator 112 can be an external or wireless ultrasound device and can be part of or remote from the NEUSleeP device 100.

[0215] As described in more detail below, an example NEUSleeP device 100 can comprise one or more sensors (e.g., acoustic hydrogels) configured to obtain data (e.g., EEG data) from the subject for processing by the system 101. The controller 108 of the system 101Attorney Docket No. 10046-659W018551 WAN can direct or control ultrasound stimulation (via the ultrasound generator 112 and / or NEUSleeP Device 100) based on analysis of the received data by the analyzing component 104. In some implementations, the NEUSleeP device 100 comprise an integrated Concentric Ring Array Transducer (CRUTA) for adjustable focal depth in targeting STN for non- invasive neuromodulation of STN in REM sleep enhancement. The NEUSleeP Device 100 can also comprise a long-term stable bioadhesive acoustic couplant for applying the ultrasound stimulation. The NEUSleeP Device 100 can include one or more two-dimensional (2D) array transducers that operate in conjunction with the beamsteering / beamfocusing component 105 to target the subject’s S'l'N or other areas of the subject’s brain.

[0216] As illustrated, the system 101 is in electronic communication with one or more NEUSLeeP devices 100 and one or more ultrasound generators 112. In some implementations, the components shown in FIG. 2A may be in the same or different cloud service environments and may communicate with each other over one or more network connections, such as, a LAN, WAN, Internet or other network connectivity. This disclosure contemplates that the system and method can be individually implemented by one or more systems (e.g., remote systems) and devices which can each include some or all of the components of the system 200.

[0217] Example Method

[0218] Referring now to FIG. 2B, a flowchart diagram depicting a method 201 in accordance with certain embodiments of the present disclosure is provided. The proposed method 201 can be used to control an Ultrasound Neuromodulation Sleep Patch (NEUSLeeP) Device or wearable device (“device”) and provide non-invasive ultrasound stimulation to treat various medical conditions. This disclosure contemplates that the device can be used in a clinical setting (e.g., for sleep studies) or can be a medical device programmed for use at home by a subject undergoing treatment over a period of time. The method 200 can be at least partially implemented by the system 200 described above in connection with FIG. 2A (e.g., via the controller 108) and can be configured for open-loop and closed-loop operations.

[0219] Beginning at step / operation 202, the method 201 includes obtaining a subject’s data from a database, Electronic Health Record, and / or the device itself. Such data can include biophysical data (breathing rate, heart rate, heart rate variability, SpO2, heart rate, and blood pressure) functional magnetic resonance imaging (fMRI) data, MRI data, medical condition(s), combinations thereof, and / or the like. Such data can be used to set baseline values for operating the device or customizing device operations for the subject. The data can also be used to determine the subject’s medical condition.Attorney Docket No. 10046-659W018551 WAN

[0220] At step / operation 204, the method 201 includes determining a target area of the subject’s brain based on a known or determined medical condition. In various embodiments, the medical condition can be Parkinson’s disease, epilepsy, Alzheimer’s disease, stroke, traumatic brain injury, psychiatric disorders (e.g., depression, anxiety, obsessive-compulsive disorder), pain, (e.g., brain stimulation, spinal cord stimulation, or peripheral stimulation), peripheral chronic joint pain, overactive bladder syndrome, sleep disorders (e.g., sleep apnea, redness leg syndrome), carpal tunnel syndrome, visual prosthetics and / or blindness, or mood disorders, or any combination thereof.

[0221] At step / operation 206, the method 201 includes determining stimulation parameters and / or a stimulation protocol corresponding with the target area of the subject’s brain. For example, if the subject has a sleep disorder, the corresponding target area can be the subject’s STN. An example device can include one or more 2D arrays configured for beamsteering and beamfocusing to focus on a particular target area (e.g., STN or other areas) of the subject’s brain. This disclosure contemplates that other areas of the brain can be targeted based on the subject’s medical condition.

[0222] At step / operation 208, the method 201 includes causing the device to deliver stimulation according to the determined stimulation parameters and / or stimulation protocol. In some embodiments, the stimulation parameters are STN-related parameters and / or based on the subject’s circadian cycle (e.g., as determined from the subject’s data in step / operation 202) and / or at a predetermined frequency (e.g., every 90 minutes, every 120 minutes, as generally or optimally determined for the subject). In other implementations, the stimulation parameters comprise frequency parameters, acoustic intensity parameters, a focal depth, combinations thereof, and / or the like. Additionally, and / or alternatively, the stimulation parameters can include at least one of at least one of a Center frequency (fo), Pulse Duration (PD), Pulse Repetition Frequency (PRF), Pulse Duty, Burst Duty, Cycles per pulse, Cycles per burst, Peak Pressure (P), Spatial peak pulse average intensity (Isppa), Spatial peak temporal average intensity (Ispta), Mechanical Index (MI), acoustic intensity, and focal depth, as described in more detail herein.

[0223] Optionally, at step / operation 210, the method 201 includes adjusting the stimulation in real-time based on detected changes to monitored parameters (e.g., EEG data, breathing rate, heart rate, SpO2, heart rate, heart rate variability, and blood pressure). For example, in a closed loop implementation, the controller can increase or decrease a frequency and / or intensity of the stimulation being provided based on the subject’s physiological and biological responses to the stimulation, a detected sleep stage, and / or the like.Attorney Docket No. 10046-659W018551 WAN

[0224] Example Non-Invasive Electrophysiological Recording and Ultrasound Neuromodulation Sleep Patch (NEUSLeeP) Device

[0225] FIG. 3A shows an example device 100, also referred to as NEUSLeeP or NEUSLeeP device, configured to improve rapid eye movement (REM) sleep.

[0226] In FIG. 3 A, subpanels (a) and (b), the exemplary device (shown as device 100 in FIG. 2A) includes six electrophysiological recording channels 302a - 302f (e.g„ 4 EEG, 1 EOG, 1 EMG) with ultra-low impedance 2-Acrylamido-2-methylpropane sulfonic acid (AMPS) based Sleep Gel (ASG) 304a - 304g to provide sufficient coverage to capture key features in sleep recording. 'The exemplary device includes a Concentric Ring Ultrasound Transducer Array (CRUTA) 306, allowing adjustable axial focal depth for focused ultrasound stimulation (FUS) to target the Subthalamic Nucleus (STN) for neuromodulation. The exemplary device integrates the CRUTA 306 and electrophysiological recording units 302 with a bioadhesive elastomeric substrate 308 using Ecoflex-Gel modified with Polyethyleneimine ethoxylate (Eco-PEIE-Gel).

[0227] In some embodiments, the exemplary device 100 employs a multi-layer fabrication approach, including transfer-printed laser-etched copper interconnects 310 on polyimide (Cu-PI), and encapsulation 308 with a bioadhesive elastomeric substrate including Ecoflex-Gel modified with Polyethyleneimine ethoxylate (Eco-PEIE-Gel), which provides stable adhesion to the skin. In FIG. 3A, subpanel (b), the exploded view shows a modular configuration with two separable layers: (1) the FUS layer containing CRUTA 306, and (2) the electrophysiological recording layer comprising ASG and Eco-PEIE-Gel. This modular configuration facilitates targeted neuromodulation and high-fidelity sleep monitoring.

[0228] In some embodiments, the exemplary device is lightweight (e.g., 103.4 grams) and attachable to various skin surfaces, including oily and hairy skin, for an extended duration, allowing ease of use for overnight sleep. In FIG. 3A, subpanel (c) shows that the exemplary device is applicable for transcranial FUS (tFUS) at STN to improve REM sleep performance and for electrophysiological recording to determine sleep staging during sleep, by characterizing the effect of FUS in stress management and brain activity modulation through heart rate variability measurements and functional magnetic resonance imaging (fMRI) under stress-related tasks. In FIG. 3A, subpanel (d) shows a schematic of a sleep experiment using the exemplary device 100 to induce improvements in REM sleep.

[0229] Example Eco-PEIE-Gel Bioadhesive Encapsulation Substrate

[0230] FIG. 3B shows an example Eco-PEIE-Gel bioadhesive encapsulation substrate / layer (see 308, FIG. 3A). In FIG. 3B, subpanel (a) shows that Ecoflex-Gel, utilizedAttorney Docket No. 10046-659W018551 WAN as a backbone of the bioadhesive encapsulation layer, is modified with PEIE to create a robust and soft bioadhesive elastomer (Eco-PEIE-Gel). An addition of PEIE creates a polymer chain of amine, hydroxyl, and carboxylic groups that create hydrogen bonding, electrostatic ion pairing, and ammonium-carboxylic pairing with the stratum corneum of human skin. The surface modification of PEIE also creates small pores, supplementing mechanical interlocking structures, aside from the minuscule Van der Waals force. In FIG.3B, subpanel (b) shows a photograph of the Eco-PEIE-Gel encapsulation layer on the human skin.

[0231] Example 2-Acrylamido-2-methylpropane sulfonic acid-based Sleep Gel ( ASG)

[0232] FIG. 3C shows an example 2-Acrylamido-2-methylpropane sulfonic acid-based Sleep Gel (ASG) (see 304, FIG. 3A). In FIG. 3C, subpanel (a) shows that ASG is developed by using the poly(AMPS) chain network with water-glycerol solvent that is (i) initiated with ammonium persulfate (APS) and (ii) catalyzed with a thermo-initiator (Tetramethylethylenediamine, TEMED) cross-linked with methylenebisacrylamide (MBAA).

[0233] In FIG. 3C, subpanel (b) shows a photograph of ASG on the human skin. ASG uses AMPS as the primary ionic monomer for skin interfaces, allowing for improved biocompatibility and conductivity with salt ions in sweat. Increasing the glycerol content during the development of ASG can improve its hydration retention, and thermal heating ASG can create a drier surface with improved adhesion while maintaining high water content internally, resulting in a low-impedance property of ASG. The trade-off in adhesion may facilitate a 50% decrease in impedance within an EEG signal band range of 1-100 Hz. The development of ASG provides a soft, comfortable, and low-impedance electrode that enables sleep recording, which is essential for electrophysiological recording in the exemplary device.

[0234] Example Concentric Ring Ultrasound Transducer Array (CRUTA)

[0235] FIG. 3D shows an example 8-channel piezoelectric concentric ring transducer array (CRUTA) (see 306, FIG. 3A), where each channel corresponds to a transducer (also referred to as a transducer element). As shown, the 8-channel CRUTA uses a high electromechanical coupling of bulk piezoelectric to generate high acoustic pressures at a specific resonant frequency (e.g., high Q-factor) and hybridizes the bulk piezoelectric with soft elastomer encapsulation to enable a light-weight, comfortable, and acoustic coupling with soft biological tissue

[0037] ,

[0038] .

[0236] In some embodiments, transfer printing of a laser-etched bilayer stacking of polyimide (e.g., PI, 24 μm, Cu 660 μm) is used to fabricate flexible electrodes to interconnectAttorney Docket No. 10046-659W018551 WAN between the eight concentric ring arrays of transducers and wires. In some embodiments, a concentric ring array is configured to target the STN through the temporal bone above the zygomatic arch of a subject. An acoustic pressure field, caused by an ultrasound beam from the CRUTA, can be adjustable through changes in voltage supplied by a voltage control system (e.g., Vantage 64LE system). The ultrasound beam from the CRUTA can be formed collectively by the interference of ultrasound waves emitted from the individual transducers. In some embodiments, the focal depth of the ultrasound beam is tuned by controlling the phase delays between individual transducers, enabling axial focusing and spatial targeting of specific anatomical regions. The ultrasound beam’s focal depth can influence the acoustic pressure field.

[0237] Experimental Results and Additional Examples

[0238] A study was conducted to develop and evaluate an experimental device (also referred to as NEUSLeeP), as described in relation to FIGs. 1 - 3.

[0239] Experiment Procedure

[0240] Synthesis of Eco-PEIE-Gel. In an experiment, the study prepared Ecoflex-Gel by mixing the base elastomer and the cross-linking agent in a 1:1 ratio. To the resulting mixture, 5% by weight of an additive was incorporated and stirred uniformly using a digital stirrer at 1500 RPM. The final mixture was then poured into a mold of the desired shape and cured for 48 hours. After curing, the surface was rinsed with water and dried under ambient conditions for 12 hours.

[0241] Synthesis of ASG hydrogel. To prepare the hydrogel precursor solution, 2 g of AMPS was fully dissolved in 2.5 g of deionized (DI) water under magnetic stirring until a homogeneous and transparent solution was obtained. Subsequently, 50 μL of a 0.05 M aqueous solution of MBAA was introduced as a crosslinker, followed by the addition of glycerol at a 30 wt% mass ratio relative to the total solution mass to enhance flexibility and water retention. The mixture was stirred thoroughly to ensure a uniform distribution of all components. To initiate polymerization, 43 μL of a 0.097 M aqueous solution of TEMED was added as an accelerator, followed by 32 μL of a 0.02 M APS solution as a radical initiator. The resulting precursor solution was mixed and transferred using a micropipette into a polylactic acid (PLA) mold produced via 3D printing. To prevent dehydration during the curing process, the filled mold was sealed inside a plastic enclosure. Thermal polymerization was carried out in a convection oven at 60 °C for 1 hour, ensuring complete gelation. After curing, the ASG hydrogel was demolded and stored in a sealed container before characterization and functional testing.Attorney Docket No. 10046-659W018551 WAN

[0242] Material Characterization of Eco-PEIE-Gel and ASG. Fig. 4A shows material characterizations of the Eco-PEIE-Gel bioadhesive encapsulation layer and the ASG recording electrodes. Specifically, FIG. 4A, subpanel (a) shows a chemical structure of Eco-PEIE-Gel and its mechanism to interface with human skin through hydrogen bonding, electrostatic pairing, and ammonium-carboxylic pairing of the stratum corneum in strong adhesion. FIG. 4A, subpanel (b) shows a photograph of Eco-PEIE-Gel on the skin. FIG. 4A, subpanel (c) shows an Attenuated Total Reflectance with Fourier Transform Infrared spectroscopy (ATR-FTIR) of 5% weight percentage of PEIE in Eco-PEIE-Gel and Pristine Ecoflex gel, outlining the modification of chemical structure in Eco-PEIE-Gel. FIG. 4 A, subpanel (d) shows a 90° T-peel test of Eco-PEIE-Gel (PEIE 5 wt%) on various materials to determine its adhesion strength (n = 4, independent samples). FIG. 4A, subpanel (e) shows an adhesion cycling of Eco-PEIE-Gel (5 wt% and 10 wt%) on human skin (n = 4, independent samples). FIG. 4A, subpanel (f) shows a stress-strain curve for various loadings of PEIE in Eco-PEIE-Gel (n = 4). FIG. 4A, subpanel (g) shows a failure strain of Eco-PEIE-Gel of varying PEIE loading (n = 4, independent samples). FIG. 4A, subpanel (h) shows a Young’s modulus derived from the stress-strain curve of varying PEIE loading (n = 4, independent samples).

[0243] FIG. 4A, subpanel (i) shows a chemical structure of ASG, and its adhesion allows strong interfacing with the skin. FIG. 4A, subpanel (j) shows a photograph of ASG on skin and copper. FIG. 4A, subpanel (k) shows a 90° T-peel test of ASG on skin and metal substrates (n = 4). FIG. 4A, subpanel (1) shows a Bode impedance comparison of ASG to commercial-grade electrodes (e.g., Kendall 31050) and conductive gels (e.g., EasyCap Supervise). FIG. 4A, subpanel (m) shows a long-term skin impedance over 8 hours comparing ASG to commercial-grade electrodes and gels (n = 4, independent samples). FIG.4A, subpanel (n) shows a comparison of a 30-second window in the recorded signal during sleep at N2 and N3 between the experimental device (with ASG) and a commercial EEG headcap (e.g., 32-Channel AntNeuro). FIG. 4A, subpanel (o) shows a correlation matrix of hypnogram between the experimental device and the commercial EEG headcap (e.g., 32- channel AntNeuro). FIG. 4A, subpanel (p) shows a hypnogram of overnight sleep recording (n = 3 for each recording, Commercial vs. the experimental device).

[0244] The adhesion strength of Eco-PEIE-Gel and ASG was evaluated using modified ASTM F2255-05 and ASTM F2256-05 protocols with a testing system (e.g., FB5, Torbal) configured for 90° peel tests. The Eco-PEIE-Gel and ASG specimens were fabricated with dimensions of 20 x 50 x 1 mm (width x length x thickness), and a Kapton film (e.g., 7413D,Attorney Docket No. 10046-659W018551 WAN 3M) was laminated to the backside of each sample to prevent stretching during peeling. For skin adhesion tests, Eco-PEIE-Gel and ASG were applied to the skin and peeled away at a 90° angle at a rate of 68 mm / min. Similarly, both Eco-PEIE-Gel and ASG were applied to a variety of materials, including aluminum (Al), copper (Cu), iron (Fe), polylactic acid (PLA) plastic, polypropylene (PP) plastic, Ecoflex-0050, polydimethylsiloxane (PDMS), silicone (Si), and human skin (see FIG. 4A, subpanels (d) and (k)). Adhesion stability of Eco-PEIE-Gel prepared at 5% wt and 10% wt was performed similarly by repeated cycling of adhesion with 90° peeling up to 20 cycles on human skin.

[0245] Tensile properties of Eco-PEIE-Gel were characterized using the same mechanical testing apparatus (e.g., FB5, Torbal) employed for adhesion measurements. Eco-PEIE-Gel samples were molded into rectangular strips with dimensions of 20 x 50 x 2 mm (width x length x thickness). Each specimen was clamped at both ends to minimize slippage, with Kapton film backing (e.g., 7413D, 3M) applied when necessary to prevent stretching outside the gauge region. Tests were performed under uniaxial tensile loading at a constant crosshead speed of 68 mm / min until failure. Force-displacement data were continuously recorded and converted into stress-strain curves by normalizing the applied load to the initial cross-sectional area and the displacement to the initial gauge length (see FIG. 4A, subpanel (f)). The stress-strain curves determined the elastic modulus, tensile strength, and elongation at break (see FIG. 4A, subpanels (g) - (h)).

[0246] The stability of the skin-electrode interface was evaluated over 8 hours using an impedance spectrum analyzer (e.g., SP-300, BioLogic). ASG electrodes were affixed to the forearm skin after standard cleaning with 70% isopropyl alcohol to minimize variability from surface oils and debris. An electrode-skin contact area of 615 mm2was maintained across all tests, with the electrodes secured. Impedance spectra were collected at predetermined intervals of every 2 hours across a frequency range of 1 Hz to 1 MHz using a sinusoidal excitation signal of 10 mV RMS. The analyzer recorded both magnitude and phase components of impedance, allowing extraction of resistive and capacitive contributions of the skin interface. Throughout the 8-hour measurement window, the subject remained at rest in a controlled laboratory environment (e.g., temperature -22 °C, relative humidity -45%) to minimize physiological and environmental variability (see FIG. 4A, subpanel (m)). Similarly, the study measured the impedance of electrodes (see FIG. 4A, subpanel (1)).

[0247] Fourier transform infrared spectra were collected to characterize the chemical structure of Eco-PEIE-Gel samples prepared with different PEIE concentrations (0, 2.5, 5, and 7.5 wt%). Films of each formulation were cast and cured under identical conditions andAttorney Docket No. 10046-659W018551 WAN then cut into flat pieces (-1 mm thickness) suitable for ATR measurement. Spectra were acquired using an ATR-FTIR spectrometer (e.g., Invenio R-FTIR, Bruker) with a diamond / ZnSe crystal. Each sample was firmly pressed onto the ATR crystal to ensure consistent contact. Spectra were collected over a range of 4000-500 cm-1with a resolution of 4 cm-1, averaging 256 scans per spectrum. Background spectra were recorded before each measurement and automatically subtracted. Spectral data were processed with baseline correction and normalization to facilitate comparison across different PEIE concentrations. Characteristic absorption bands corresponding to Si-O-Si, Si-CEb, C-N, C-O-C, and N-H groups were analyzed to assess chemical interactions and compositional changes induced by increasing PEIE content (see FIG. 4A, subpanel (c)).

[0248] Configuration and Characterization of CRUTA. For CRUTA, a concentric ring array shape and its corresponding dimensions were determined to be 60 - 80 mm based on the focal depth from the temporal window to the subthalamic nucleus

[0128] , which were then validated to be 72.2 ± 4.62 mm through anatomical MRI scans across 28 subjects. In a free-field, the maximum achievable focal depth zmaxfor a flat concentric ring array transducer can be approximated by Equation 1

[0129] ,>_ (2RadiusCRUrA)2^max ~(Eq. 1)

[0249] FIG. 4B shows the information and study groups of 28 subjects participating in the experiment. FIG. 4B, subpanel (a) shows the demographic and PSQI scores for a Focused Ultrasound Stimulation at the Subthalamic Nucleus (STN-FUS) targeting group. FIG. 4B, subpanel (b) shows the demographic and PSQI scores for a healthy group. FIG. 4B, subpanel (c) shows the demographic and PSQI scores for an insomnia group.

[0250] A maximum focal depth could be 90 mm using a center frequency of 650kHz, and a medium could be water (c = 1500 m / s), similar to that of brain tissue acoustically (k = speed of sound in water / center frequency), then the outer diameter of the CRUTA should be no less than 30 mm. In addition, to avoid off-targeting stimulation effects, minimization of grating lobes and high locality was necessary. Therefore, the trade-off between transducer size, ring width, and number of rings could be optimized using Equation 2

[0129] , requiring the ring width of each element to be greater than 1.15 mm. To account for fabrication limitations, the study selected the ring width to be 4.72 mm.2Ring Width > —Attorney Docket No. 10046-659W018551 WAN (Eq. 2)

[0251] Given the constraints, the study used (i) Equation 3

[0129] to control an adjustment of axial focal depth, where dnis diameter of nthelement, 2 is acoustic wavelength in medium, and 0nis phase-delay of n*11element, (ii) Equation 4

[0129] to determine the acoustic field pressure, where pmis acoustic pressure at a 3D point, p is density of medium, c is speed of sound in medium, k is real wave number, Anis amplitude, m is angular frequency, rmnqis distance to point m from point q with reference to element n, and Snis surface area of element n, and (iii) optimization and simulation using finite element analysis software (e.g., COMSOL Multiphysics 6.2, COMSOL Inc.) to determine acoustic field distribution at varying phase delays (see Table 1), resulting in various design parameters (see Table 2) for CRUTA.z, d-n ■ n (Eq. 3) Nipck v“’ g-ikr, Q i t -f- On ) | - dSPmn= ~2T L“ l Snrmnq (Eq. 4)

[0252] Table 1 shows the phase control parameters of CRUTA. Table 2 shows the dimensions and parameters of CRUTA.Table 1Channel Time Delay (gs)DelayVariable 1 2 3 4 5 6 7 8 50 3.41251506 3.21489905 2.91713277 2.52042039 2.02777903 1.44043567 0.76370241 0 60 2.8737777 2.70889273 2.46007496 2.12789311 1.71431743 1.21972224 0.64785615 0 70 2.47926528 2.33782904 2.12420323 1.83864537 1.48255151 1.05588634 0.56147943 0 80 2.17864985 2.05483266 1.8677085 1.61737021 1.30486884 0.92996337 0.4948993 0 90 1.9423205 1.83222387 1.6657681 1.44295417 1.16461072 0.83039216 0.44214872 0 100 1.7518221 1.65271136 1.5028217 1.30210118 1.05122677 0.74980136 0.39939385 0 110 1.59509505 1.50497837 1.36866152 1.18606156 0.95774725 0.68329893 0.36407685 0 120 1.46394362 1.3813255 1.25633103 1.0888592 0.87939861 0.62752329 0.33443344 0Attorney Docket No. 10046-659W018551 WAN 30 1.3526117 1.2763408 1.16093443 1.00628135 0.81280893 0.5800941 0.30921082 0 40 1.25694214 1.18611325 1.07893039 0.93527697 0.75553236 0.53928156 0.2874966 0 50 1.17385986 1.10774844 1.00769618 0.87358425 0.70575351 0.50379986 0.26861146 0 60 1.10104252 1.03905965 0.94524921 0.81949208 0.66209767 0.47267425 0.2520397 0 70 1.03670423 0.97836474 0.89006363 0.77168276 0.6235054 0.44515276 0.23738307 0 80 0.97944952 0.92434901 0.84094643 0.72912548 0.58914737 0.42064634 0.22432933 0 90 0.92817246 0.87597028 0.79695164 0.69100252 0.55836534 0.39868716 0.21263031 0 00 0.88198543 0.83239199 0.75731968 0.65665708 0.53063038 0.37889906 0.20208634 0Table 2ChannelID (mm) OD (mm) Material Geometry Electrode Plating ElementNickel, both 1 5.35 10.07 DL-47 Circular Ring electrodes same side Nickel, both 2 10.72 15.42 DL-47 Circular Ring electrodes same side Nickel, both 3 16.07 20.78 DL-47 Circular Ring electrodes same side Nickel, both 4 21.43 26.14 DL-47 Circular Ring electrodes same side Nickel, both 5 26.79 31.49 DL-47 Circular Ring electrodes same side Nickel, both 6 32,15 36.86 DL-47 Circular Ring electrodes same side Nickel, both 7 37.51 42.21 DL-47 Circular Ring electrodes same side Nickel, both 8 42.86 47.57 DL-47 Circular Ring electrodes same sideAttorney Docket No. 10046-659W018551 WAN

[0253] FIG. 4C shows an evaluation of the effects of STN-FUS using CRUTA. FIG. 4C, subpanel (a) shows an experimental protocol for evaluating the effects of STN-FUS using CRUTA by performing a resting state functional scan before and after 10-minute stimulation. The 10-minute stimulation was configured with 10 blocks, each block having (i) a 30s ON period and a 30s OFF period, (ii) a pulse repetition frequency (PRF) of 100 Hz, (iii) a pulse duration (PD) of 0.5 ms, and (iv) a pressure of 0.90 MPa. FIG. 4C, subpanel (b) shows a photograph of MRI-guided positioning and targeting of CRUTA for STN-FUS. FIG. 4C, subpanel (c) illustrates blood oxygen saturation levels (SpO₂) and heart rate, monitored throughout the evaluation, which show no significant changes with STN-FUS. FIG. 4C, subpanel (d ) shows a measured blood pressure indicating minimal STN-FUS changes. FIG.4C, subpanel I shows that a resting state blood oxygen level dependent variability (rsBOLDSD) at the left subthalamic nucleus (L-STN) increased with STN-FUS compared to baseline. FIG. 4C, subpanel (f) shows that the amplitude of low frequency fluctuation (JSBOLDALFF) was elevated below 0.03 Hz (n = 16, independent samples, two-sided paired t- test). FIG. 4C, subpanel (g) shows a cerebral blood flow (CBF) obtained from pseudo- continuous arterial spin labeling (pCASL) masked at regions-of-interest. Bilateral nucleus accumbens (Nac) indicated elevated CBF (n = 16, independent samples, two-sided paired t-test). FIG. 4C, subpanel (h) shows a group-level analysis to compare the effects of left STN- FUS on rsBOLD before and after stimulation. Changes in left Gpe, Gpi, Nac, and Pu were observed (n = 16, linear mixed effect model with probabilistic threshold-free cluster enhancement (pTFCE)). pTFCE values were zeroed between -4.90 and 4.90 for statistical representation. In FIG. 4C, all subpanels show mean + s.e.m (standard error of the mean) unless otherwise mentioned, *P < 0.05, **P < 0.01, ***P < 0.001, and *pTFCE > I4.90L

[0254] The study generated a tFUS acoustic profile from the CRUTA using a high-intensity focused ultrasound stimulation system (e.g., Vantage 64LE HIFU, Verasonics Inc.). The study delivered a train of pulses, following the 10-minute stimulation in the study (Pulse Repetition Frequency: 100 Hz, Pulse Duration: 0.5 ms, Duty Cycle: 5%), at a center frequency of 650kHz (see FIG. 4C, subpanel (a)).

[0255] FIG. 4D shows a fabrication process of the experimental device and its components. FIG. 4D, subpanel (a) shows a preparation of a base layer for CRUTA with a 3D-printed PEA mold. FIG. 4D, subpanel (b) shows a curing of a 1-mm thick backing layer with Ecoflex-050. FIG. 4D, subpanel (c) shows a placement of CRUTA by concentrically aligning eight piezoelectric elements. FIG. 4D, subpanel (d) shows a transfer printing of interconnect prepared for CRUTA and carefully placed / soldered onto the elements. FIG. 4D,Attorney Docket No. 10046-659WOI 8551 WAN subpanel I shows a preparation of an encapsulation layer for CRUTA with a 3.5mm-thick 3D-printed PLA mold. FIG. 4D, subpanel (f) shows wires (e.g., A WG 36) threaded through a 0.5” silicon tube and soldered onto interconnects. FIG. 4D, subpanel (g) shows an encapsulation of CRUTA with Ecoflex-050 for 60 min. FIG. 4D, subpanel (h) shows a release of CRUTA from the mold. FIG. 4D, subpanel (i) shows a preparation of a base layer for the EEG layer with a 1-mm-thick 3D-printed PLA mold. FIG. 4D, subpanel (j) shows a curing of a 1-mm-thick backing layer with Ecoflex-050. FIG. 4D, subpanel (k) shows a transfer printing of interconnect prepared for the EEG layer. FIG. 4D, subpanel (1) shows a preparation of the encapsulation layer of the EEG layer with a 3.5mm-thick 3D-printed PEA mold. FIG. 4D, subpanel (ni) shows a placement of a negative mold for an electrode opening for ASG attachment. FIG. 4D, subpanel (n) shows a preparation of 5% wt PEIE mixed with Ecoflex-Gel (Eco-PEIE-Gel) for encapsulation, which was cured for 48 hours. FIG. 4D, subpanel (o) shows a water rinse process to remove excess uncured materials, solder touch¬ proof wires, and release from the mold. FIG. 4D, subpanel (p) shows a bonding of CRUTA and EEG layer with Silpoxy and an attachment of ASG to the electrode terminals.

[0256] FIG. 4E shows a transfer printing process of interconnects in the experimental device. FIG. 4E, subpanel (a) shows a preparation of a backing layer substrate using Ultra 582U adhesive for transfer printing. FIG. 4E, subpanel (b) shows a lamination of copper adhesive interfaced with water-soluble tape onto the backing layer substrate for delamination post-transfer printing. FIG. 4E, subpanel (c) shows a laser-etched patterning of interconnect using LPKF U4 Protolaser. FIG. 4E, subpanel (d) shows a lamination onto polyimide film and peeled at a greater than 120° angle for transfer printing and release. FIG. 4E, subpanel I shows a cross-sectional view of substrate layers for transfer printing. FIG. 4E, subpanel (f) shows estimated Griffith’s energy release rates between substrate materials at various peel angles.

[0257] In the study, a 3.5mm-thick 3D-printed PLA mold was attached to a medium tack transfer tape (e.g., Ultra 582U, TransferRite), where a silicon elastomer (e.g., Ecoflex-0050, Smooth On) was poured and cured for 30 minutes (see FIG. 4D, subpanels (a) - (b)). A 660um-thick copper adhesive tape (e.g., 1126, 3M) was attached to water-soluble tape (e.g., 18C570, Aquasol), and a medium tack transfer tape (e.g., Ultra 582U, TransferRite) was laser etched into interconnect patterns (see FIG. 4E, subpanels (a) - (c)), which was then printed onto 25.4 pm electrical grade polyimide film (e.g., 2271K41, McMaster-Carr). Estimation of energy release between materials was identified using simplified Griffith’s equation

[0130] , known as the Kendall’s Peel Model

[0131] , which was used to determine feasibility of transferAttorney Docket No. 10046-659W018551 WAN printing copper onto polyimide, where the energy needed for the interface between the copper adhesive tape to polyimide film was greater than the interface between the other two interfaces (see FIG. 4E, subpanels (d) - (f)). The copper interconnect laminated film was then laid on top of the cured elastomer mold (see FIG. 4D, subpanels (c) - I). A thin layer of Ecoflex-050 was applied to encapsulate interconnects, exposing only the electrode terminals. Eight varying diameter piezoelectric rings with nickel-coated electrodes (e.g., DL-47, Del Piezo) were acquired based on the designed dimensions (see Table 2) and mounted onto copper electrode terminals with application of low-temperature solder paste (e.g., NP510-LT HRL1, Kester). The 3D-printed mold was removed and placed in a thermo-controlled soldering oven for 5 minutes at 120°C. The 3.5mm-thick mold was reapplied. Subsequently, a Imm-thick 3D printed PEA mold with a circular opening was placed on top and secured with mass weights. Eight pairs of 32-gauge wires were threaded through 6.35-mm silicon tubing into the circular opening, and the wires were soldered on the opening end of the copper interconnects (FIG. 4D, subpanel (fl). Lastly, Ecoflex-050 was prepared and poured into the mold until uniformity for encapsulation and released from the mold (FIG. 4D, subpanels (g) - (h)).

[0258] FIG. 4F shows phase control and characterization of CRUTA. FIG. 4F, subpanel (a) shows a schematic of a temporal bone in a human skull and the position of a zygomatic arch. FIG. 4F, subpanel (b) shows a photograph of CRUTA and the temporal bone in the experimental setup for acoustic characterization. FIG. 4F, subpanel (c) shows a simulation of an in vivo acoustic field distribution of CRUTA with the temporal bone. FIG. 4F, subpanel (d) shows a measured in-vitro acoustic field distribution of CRUTA with the temporal bone. FIG. 4F, subpanel I shows a time / phase delay of individual elements of CRUTA with respect to a placeholder variable (delay variable) used for determining focal depth. FIG. 4F, subpanel (f) shows a linear regression and relationship of focal depth measured across multiple CRUTA (n = 8, R2= 0.9509). FIG. 4F, subpanel (g) shows a zoomed-in view of the approximate average STN depth from temporal windows to demonstrate spatial resolution. FIG. 4F, subpanel (h) shows a linear regression and relationship of acoustic pressure measured across multiple CRUTA (n = 8, R2= 0.6217) in response to driven voltage.

[0259] FIG. 4G shows an evaluation of the concentric ring ultrasound transducer array (CRUTA) of the experimental device. FIG. 4G, subpanel (a) shows an experimental setup of CRUTA characterization. FIG. 4G, subpanel (b) a Bode impedance and phase response of CRUTA (n = 8). FIG. 4G, subpanel (c) shows an axial acoustic pressure of CRUTA with increasing focal depth adjustments. FIG. 4G, subpanel (d) shows an axial acoustic pressure ofAttorney Docket No. 10046-659W018551 WAN CRUTA with increasing driving voltage at a fixed focal depth. FIG. 4G, subpanel I shows an acoustic field distribution of CRUTA with and without the temporal bone at varying focal depths (f = 32.5, 48.0, 61.0, and 70.5 mm), normalized to the peak pressure of each focal depth. FIG. 4G, subpanel (f) shows axial and radial acoustic profiles measured and the corresponding focal depths with and without skulls, demonstrating the effects of attenuation due to the temporal skull.

[0260] The CRUTA was mounted on a 3D-printed submersible stand in a 457.2 mm x 180.34 nun x 139.7 mm (length x width x height) glass tank filled with degassed distilled water. Acoustic foams (e.g., Aptflex 48, Precision Acoustics) were padded internally along the glass walls to prevent scattering and reflection during measurements. Acoustic intensity and waveform were measured using a calibrated needle hydrophone (e.g., HNR-0500, Onda) mounted on a three-axis stage system with a workspace of 100 mm x 100 mm x 100 mm. The hydrophone was connected to an oscilloscope (e.g., SDS 1204-XE, Siglent), interfaced with a custom MATLAB program for axial, radial, and automated 3D scanning with signal processing (see FIG. 4F, subpanels (a) - (b)). CRUTA was controlled and driven by a commercially available ultrasound system (e.g., Vantage 64LE HIFU, Verasonics Inc.). Each of the eight channels of CRUTA was connected independently via LEMO-OO and driven with varying delay timings in accordance with the desired focal depth (see FIG. 4F, subpanel I).2D acoustic field scans in free-field were performed at 500pm increments (e.g., 0 - 100 mm from transducer in a 60 mm x 100 mm grid workspace) (see FIG. 4G, subpanel I). Axial and radial profiles generated from the scans obtained were then processed to determine focal depth and spatial peak locations (see FIG. 4G, subpanels (b) - (c)). In addition, a human skull (e.g., Skull Unlimited International Inc., 4-mm thick temporal cortical bone, rehydrated for 24h in phosphate buffer solution) was inserted in between the transducer and hydrophone (see FIG. 4G, subpanel (a)), where similar 2D acoustic field scan was performed with an offset of 20 mm to prevent collision of the hydrophone with the skull (e.g., 20 - 100 mm from transducer in a 60 mm x 80 mm grid workspace).

[0261] Using a two-electrode configuration, the study evaluated each of the eight channels in CRUTA with an impedance spectrum analyzer (e.g., SP300, BioLogic). The study measured a total of eight CRUTA devices. The study measured impedance between 0 and 1MHz to identify and validate resonant frequencies at approximately 650kHz (FIG. 4G, subpanel (b)).

[0262] FIG. 4H shows thermal heating effects of the CRUTA. FIG. 411, subpanel (a) shows a schematic representation of acoustic power loss. FIG. 4H, subpanel (b) shows aAttorney Docket No. 10046-659W018551 WAN computational method for thermal diffusion and estimation of in-vivo thermal heating effects of CRUTA for STN-FUS. FIG. 4H, subpanel (c) shows a calculated thermal heating response with CRUTA for STN-FUS at the desired focal depth. FIG. 4H, subpanel (d) shows a simulated thermal distribution at various time points (e.g., t = 0.5s, 300s, 600s). FIG. 4H, subpanel I shows a photograph of CRUTA in the experimental device. FIG. 4H, subpanel (f) shows a surface temperature of CRUTA before and after stimulation with / without ultrasound gel. FIG. 411, subpanel (g) shows a photograph of an endocranium temporal window and placement of the experimental device at the endocranium temporal window. FIG. 4H, subpanel (h) shows a surface temperature of the endocranium temporal window from CRUTA before and after stimulation. FIG. 4H, subpanel (i) shows a photograph of the experimental device on a human skull.

[0263] To determine the effective pressure field on the temperature in tissue, the study used a bioheat transfer equation

[0132] , Given the pressure field measured (see FIG. 4G, subpanel I) in free field, the power deposition per unit volume could be determined at the focal depth desired (see FIG. 4H, subpanels (a) -• (d); Table 3). The study measured the surface temperature of CRUTA using a thermal infrared camera (One Edge, FLIR) throughout the stimulation process to determine that nominal heating did not elicit any skin burns. The study performed ex vivo tests by applying the device on a human transcranial skull (e.g., Skull Unlimited International Inc., temporal bone, rehydrated for 24h in phosphate buffer solution) and measuring the thermal effects at the endocranium section of the temporal bone to ensure thermal diffusion did not elicit thermal damages to the dura, vessels, and cortical brain structures

[0022] (see FIG. 4H, subpanels I - (i)).

[0264] Table 3 shows the parameters used in the thermal simulations in the study.Table 3Parameter Value Units Ref CBFgray - cerebral blood flow in gray matter 80 ml / min / lOOg w - skull thickness 3.42 mni p - brain tissue density 1040 kg / m’ pb - blood density 1060 kg / m3ctskaii - atenuation coefficient of skull 5 Np / cm / MHzAttorney Docket No. 10046-659W018551 WAN abraini - attenuation coefficient brain 0.23 Np / cm / MHz Cb - specific heat of blood 3770 J / kg / °C kt- tissue thermal conductivity 0.195 W / m / °C cot- blood perfusion rate 0.000142 kg / nr’ / s Ta- arterial blood temperature 37 °C Zbraiti - acoustic impedance of brain tissues 1.5 Mrayl Zwateri - acoustic impedance of water 1.48 Mrayl Zskuii - acoustic impedance of skull 7.8 Mrayl

[0265] Fabrication of the Experimen tal Device. The experimental device included two components: an EEG layer and a CRUTA layer. The EEG layer was first developed by 3D-printing a 1mm-thick PLA mold (see FIG. 4D, subpanels (i) - (j)), which was then filled with Ecoflex-050 and cured to create a thin-substrate layer. Subsequently, copper interconnects were laser-etched and transfer-printed onto polyimide (Cu-Pi) and laminated onto the substrate (see FIG. 4D, subpanel (k)). A 3.5mm-thick 3D-printed PEA mold was then mounted on top of the electrode terminals with the addition of a separate mold (see FIG. 4D, subpanels (1) - (n)) to create an opening during encapsulation. 40 mg of Eco-PEIE-Gel was then prepared and poured onto the substrate for encapsulation. The EEG layer was then cured for 48 hours before being rinsed under water to remove the excess formation of ethoxylate and uncured Ecoflex-Gel on the surface before drying in ambient conditions for another 24 hours. Afterwards, a 10-blade scalpel was used to remove the substrate from the mold (FIG.4D, subpanel (o)). To finish, the fabricated CRUTA was bonded at a circular opening with silicon adhesive (Sil-poxy, Smooth-On) for 30 minutes (FIG. 4D, subpanel (p)).

[0266] Sleep Recording Performance of the Experimental Device. In the study, three volunteers wore (i) the experimental device and (ii) the AntNeuro 32CH EEG headcap injected with electrically conductive gel (e.g., Signagel, Parker Labs). The experimental device was connected to the EEG amplifier via a bipolar box to the amplifier (e.g., eEGO MyLab, AntNeuro), whereas the EEG headcap was connected directly. The volunteers were then placed into the sleep lab, and an 8-hour recording session was performed from 12 AM to 8 AM. The recorded data were split into two datasets with pseudo-randomized naming forAttorney Docket No. 10046-659W018551 WAN single-blinded sleep staging. The data were sent to a certified sleep staging expert and manually staged at 30-second epoch windows to evaluate the similarity in EEG recording signal quality between the experimental device and standard 10-20 commercial -grade EEG headcaps (see FIG. 4A, subpanels (n) - (p); FIG. 41).

[0267] FIG. 41 shows the sleep recording performance and benchmarking of the experimental device with the commercial EEG headcap. FIG. 41, subpanel (a) shows a correlation matrix of hyp nogram between the experimental device and the commercial EEG headcap (e.g., 32 -channel AntNeuro). FIG. 4J, subpanel (b) shows the individual hypnogram comparisons with a demonstration of the spectrogram under varying sleep stages.

[0268] Subthalamic Nucleus Target Engagement using CRETA. The study screened sixteen participants (8 male, 8 female, aged 19-37, with a mean age of 25.7 ± 6.3 years) for contraindications and neurological impairments. Table 4 shows the demographics of the sixteen participants during the STN-FUS evaluation using CRUTA.Table 4Subject ID Age Ethnicity Sex PSQI STN Distance (mm) 1 28 White Female 8 76.5 2 19 White Male 6 74.9 3 20 Asian Female 5 64.2 4 37 White Male 3 74.1 5 24 White Female 5 69.5 6 31 Asian Female 1 71.5 7 19 Asian Female 5 69.5 8 38 Asian Male 7 71.4Black or African9 33 Male 4 74.6American10 19 Asian Female 3 76.5 11 19 Prefer not to say Male 3 73.8 12 25 Asian Female 4 73.9 13 24 Asian Male 9 77.2Attorney Docket No. 10046-659W018551 WAN 14 26 White Male 7 71.9 15 23 Asian Female 2 74.1 16 25 Asian Male 7 73.1

[0269] Before the start of the session, the study obtained baseline measurements of vitals, including SpO2, heart rate, and blood pressure, and then placed the baseline measurements in the magnetic resonance imaging machine (e.g., 3T Vida, Siemens) for a standard Tl- weighted Magnetization Prepared Rapid Gradient Echo (MPRAGE) scan, followed by a Fast Gray Matter Acquisition T1 Inversion Recovery (FGATIR)

[0133] scan, to provide improved identification and localization of the subthalamic nucleus (see FIG. 4C, subpanel (a)).Subsequently, the study performed a 10-minute pre-FUS resting-state functional (e.g., T2-weighted single-shot gradient-echo planar imaging, EPI) to establish resting-state blood oxygen level dependent signals before stimulation. Next, the study attached a surrogate CRUTA device to the zygomatic arch, where the CRUTA device was created using 3D- printed PLA, embedded with 50 mg of gadodiamide (APExBio) dissolved in PBS, and encapsulated with Eco-PEIE-Gel. The study performed iterative rapid gradient scans and positioning of the CRUTA device until the study verified alignment and line-of-sight towards the subthalamic nucleus. Additionally, the study measured the distance between the CRUTA device and STN to determine focal depth by changing the delay parameter (FIG. 4C, subpanel (b)). Thereafter, the study used medical markers to mark the position before the removal and attachment of the CRUTA device. 'The CRUTA device was connected to the ultrasound system (e.g., Vantage 64LE, Verasonics) via LEMO-OO connectors. The study again measured the blood pressure before FUS to ensure no effects were caused during the MRI. The study then subjected the participants to 10 minutes of FUS (e.g., Table 1, pressure: 0.90 MPa, pulse repetition frequency: 100 Hz, pulse duration: 0.5 ms, duty cycle: 5%, 30s ON 30s OFF) whilst measuring their SpO2 and heart rate every minute to ensure no adverse effects due to FUS (FIG. 4C, subpanel (c)). After completing the FUS intervention, the study removed the CRUTA device and brought participants back to perform a post-FUS resting state functional scan.

[0270] Stress Adaptation and REM Enhancement Evaluation Post-FUS with the Experimental Device. Twenty-eight participants were subjected to screening processes involving compliance with MRI for health and safety and the Pittsburgh Sleep Quality Index (PSQI) questionnaire, to evaluate and assign study groups, health history, and demographics.Attorney Docket No. 10046-659W018551 WAN The study involved two groups: 1) healthy (e.g., PSQI < 5), and 2) insomnia (e.g., PSQI 6- 10). The healthy group included sixteen participants (8 male, 8 female, aged 19-37 with a mean age of 22.7 + 5.4 years), and the insomnia group included twelve participants (6 male, 6 female, aged 19-37 with a mean age of 25.4 ± 5.9 years). All participants were screened for contraindications and neurological impairments. Table 5 shows the demographics of the participants in the healthy group. Table 6 shows the demographics of the participants in the insomnia group.Table 5Subject ID Age Ethnicity Sex PSQI STN Distance (mm) 1 19 White Female 2 76.1 2 19 Asian Male 4 77.4 3 22 Prefer not to say Male 2 73.1 4 20 White Female 2 68.4 5 19 White Female 2 64.4 6 33 Asian Male 2 72.6 7 20 White Male 3 70.7 8 25 White Female 5 69.3 9 37 White Male 2 72.8 10 25 Asian Female 3 73.3Native Hawaiian or11 20 Male 4 77.1Other Pacific IslanderBlack or African12 20 Male 2 78.1American13 18 White Female 3 72.6 14 19 White Female 3 79.3 15 19 White Male 5 71.4 16 24 Asian Female 2 76.1Table 6Attorney Docket No. 10046-659W018551 WAN Subject ID Age Ethnicity Sex PSQI STN Distance (mm)17 18 Asian Female 10 68.8 18 24 Asian Male 5 69.1 19 25 Asian Female 9 74.2 20 28 White Female 7 62.7 21 27 Asian Female 8 66.6 22 38 Asian Male 7 69.3 23 18 Asian Female 6 65.1 24 26 White Male 7 72.8 25 33 Asian Male 10 82.3 26 27 Asian Male 9 73.6 27 21 Prefer not to say Male 7 74.1 28 20 White Female 6 69.8

[0271] All participants were subjected to an anatomical scan before the sleep study. The study placed the participants in the magnetic resonance imaging machine (e.g., 3T Vida, Siemens) for a standard T1 -weighted Magnetization Prepared Rapid Gradient Echo (MPRAGE) scan. The study then attached a surrogate CRUTA device to the zygomatic arch, where the CRUTA device was created using 3D-printed PLA, embedded with 50 mg of gadodiamide (APExBio) dissolved in PBS, and encapsulated with Eco-PEIE-Gel. The study performed iterative rapid gradient scans and positioning of the CRUTA device until the study verified alignment and line-of-sight towards the subthalamic nucleus. Additionally, the study measured the distance between the CRUTA device and STN to determine focal depth by changing the delay parameter (FIG. 4C, subpanel (b)).

[0272] FIG. 4J shows the rapid eye movement (REM) and sleep performance using the experimental device during a sleep experiment. FIG. 4J, subpanel (a) shows an experimental protocol of overnight sleep recording and stress measurements under STN-FUS using the experimental device. FIG. 4J, subpanel (b) shows the clinical questionnaire of the Epsworth Sleepiness Scale response from both the healthy group (n=16) and the insomnia group (n=12). FIG. 4J, subpanel (c) shows a hypnogram of the healthy and insomnia groups in theAttorney Docket No. 10046-659W018551 WAN sham and FUS nights. FIG. 4J, subpanel (d) shows a REM duration normalized to total sleep duration. FIG. 4 J, subpanel (e) shows that the REM latency decreased. FIG. 4J, subpanel (f) shows that the number of arousals (wake) was not changed, suggesting no adverse effects on sleep quality from the experimental device. FIG. 4J, subpanel (g) shows that sleep efficiency was not changed with the experimental device, indicating that total sleep duration (Nl, N2, N3, REM) was unaffected. FIG. 4J, subpanel (h) shows the REM duration percentage changes across sleep stages in the healthy group. FIG. 4J, subpanel (i) shows the REM latency changes across sleep stages in the healthy group. FIG. 4J, subpanel (j) shows a number of transitions in sleep stages in the healthy group. FIG. 4J, subpanel (k) shows responders and non-responders of the STN-FUS (enabled by the experimental device ) in the healthy group. FIG. 4J, subpanel (1) shows the REM duration percentage changes across sleep stages in the insomnia group. FIG. 4J, subpanel (m) shows the REM latency changes across sleep stages in the insomnia group. FIG. 4J, subpanel (n) shows a number of transitions in sleep stages in the insomnia group. FIG. 4J, subpanel (o) shows the responders and non- responders of STN-FUS (enabled by the experimental device) in the insomnia group. All subpanels show mean ± s.e.m unless otherwise mentioned, *P < 0.05, **P < 0.01, and ***P< 0.001.

[0273] The sleep experiment included two consecutive overnight sessions in which participants wore the NEUSLeeP device. The first night served as a sham condition, while the second night involved focused ultrasound stimulation (FUS) (see FIG. 4J, subpanel (a)). Participants received clinical questionnaires, including the Sleepiness Stanford Scale (SSS) [134-135], the Epsworth Sleepiness Scale (EPS)

[0136] , and the State-Trait Anxiety Inventory (STAI-S)

[0137] before the sessions to determine the secondary outcome of an individual’s perception of sleepiness and anxiety between sham and FUS. The study also collected vitals, including blood pressure, heart rate, and SpO2, before the sessions to establish a baseline measurement for comparison using a finger pulse oximeter (e.g., CMS60D, FaceLake) and sphygmomanometers (e.g., Track, iHealth). The participants then wore the experimental device.

[0274] The study applied ultrasound gel (Aquasonics 100, Parker Labs) to the CRUTA surface of the experimental device to ensure sufficient coupling between the transducer and the skin. Four gold-plated cup electrodes (e.g., 630-020-60, BrainMaster Technologies) were additionally placed and injected with conductive gel (Signagel, Parker Labs) at Oz, Pz, Cz, and Fz based on the 10-20 EEG system

[0138] measured using a measuring tape from the nasion to inion. Similarly, a conductive adhesive hydrogel electrode (e.g., 1050, Kendall)Attorney Docket No. 10046-659W018551 WAN was placed laterally to the outer canthi of the right eye. The additional electrodes were fixated with medical tape (e.g., Nexcare, 3M) and were used to serve as a supplementary channel in assisting ground-truth sleep staging and for simultaneous comparison with signal quality- compared with the ASG on the experimental device. A pair of bipolar electrodes (e.g., Red Dot, 3M) was applied on the participant’s lower section of sternum (avF) and left shoulder (aVL) following Einthoven’s Triangle configuration

[0138] to allow simultaneous ECG monitoring throughout the night for safety and heart rate variability measurements. The experimental device was then connected to an electrode box with an electrophysiological recording amplifier (e.g., BrainAmp ExG, BrainVision), which was connected to a computer in a separate room through fiber optic cable via a radiofrequency (RF) shielded panel.Similarly, the experimental device was connected with eight BNC-LEMO-OO connectors through the RF panel to the ultrasound system (e.g., Vantage 64LE, Verasonics). Infrared cameras were used to monitor the participants' sleep behavior, and detailed logs were recorded throughout the night. In addition, the study played white noise [139-142] through a speaker (e.g., Dohm Nova, Yogasleep) with a modulated 100 Hz square wave at less than 60dB

[0143] to mask all external noises and chirping noises generated by the CRUTA during the 100 Hz stimulation with the experimental device for both nights throughout the sleep session. Lights were turned off during the sleep session, and the temperature was adjusted in accordance with the participant’s preference within the range of 18 °C to 24 °C.

[0275] Upon completion of device and electrode setup, ECG was recorded for 5 minutes to obtain baseline “pre-sleep” heart rate variability. Subsequently, the 8-hour sleep recording session began. On the night of the sham session, no FUS was delivered from the experimental device. On the second night with the FUS session, FUS was delivered with the ultrasound system (e.g., Vantage 64LE, Verasonics) using 100 Hz PRF protocol (see FIG. 4C, subpanel (a); Table 7; pressure: 0.90 MPa, pulse repetition frequency: 100 Hz, pulse duration: 0.5 ms, duty cycle: 5%, 30s ON 30s OFF for 5 minutes) per block every 90 minutes for a total of five blocks overnight following an ultradian sleep cycle schedule

[0144] ,

[0145] . Focal depth targeting was adjusted based on the previously measured depth of STN. Triggers corresponding to the stimulation were recorded simultaneously. Recording was stopped upon reaching 8 hours or when the participant woke up.

[0276] Table 7 shows a summary of stimulation parameters for the STN-FUS using the experimental device.Table 7Attorney Docket No. 10046-659W018551 WAN in-SituParameter Free-Field (Derated at focal depth of 72.2 mm) GuidelineCenter frequency (fo) 650 kHzPulse Duration (PD) 0.5 msPulse Repetition Frequency (PRF) 100 HzPulse Duty 5%Burst Duty 50%Cycles per pulse 325Cycles per burst 975,000Peak Pressure (P) 0.90 MPa 0.68 MPaSpatial peak pulse average26.9 W / cm215.4 W / cm2_ intensity (Isppa) _2Spatial peak temporal average intensity (Ispta) 0.674 W / cm20.385 W / cm2<0.720 W / cm2Mechanical Index (MI) 0.93 0.70 <1.90

[0277] In the morning, the study performed an ECG recording again for a “post-sleep” heart rate variability comparison. Next, the experimental device and other electrodes were removed from the participants, followed by completion and recording of SSS, ESS, STAI-S, blood pressure, heart rate, and SpO2. Participants were then escorted to an imaging center for functional magnetic resonance imaging.

[0278] Participants were inserted into the imaging suite (e.g., 3T Prisma, Siemens), and a series of scans were performed to evaluate the effects post-sleep using the experimental device (sham or FUS). An anatomical scan using standard Tl-weighted Magnetization Prepared Rapid Gradient Echo (MPRAGE), followed by a 10-minute resting-state functional (e.g., T2-weighted single-shot gradient-echo planar imaging, EPI) was performed to establish resting-state blood oxygen level dependent signals. The participants were then asked to perform the Hariri Task, an emotional face processing task by matching varying shapes and emotions to a reference image to assess stress adaptation and response (see FIG. 4J, subpanel (a)).

[0279] Subjective sleepiness was assessed using the Stanford Sleepiness Scale (SSS), a validated self-report measure used in clinical and research settings. The SSS was a 7-point Likert- type scale in which participants rated their current level of sleepiness, ranging from 1 (“feeling active, vital, alert, or wide awake”) to 7 (“no longer fighting sleep, sleep onset soon, having dream-like thoughts”). Participants completed the SSS at predefined time points during the experimental session, including immediately before the MRI scan.

[0280] The Epworth Sleepiness Scale (ESS) assessed general daytime sleepiness by¬ asking participants to rate their likelihood of dozing off or falling asleep in eight common situations (e.g., sitting and reading, watching television, as a passenger in a car) on a scaleAttorney Docket No. 10046-659W018551 WAN from 0 (“would never doze”) to 3 (“high chance of dozing”). The total ESS score was calculated by summing all eight items in the ESS, yielding a range of 0-24, with higher scores indicating greater habitual sleepiness. Participants completed the ESS during the baseline assessment before the experimental protocol.

[0281] The STAI-S was a 20-item self-report inventory configured to assess current (state) anxiety. Participants rated how they felt “right now, at this moment” on a 4-point scale ranging from 1 (“not at all”) to 4 (“very much so”). Items in the STAI-S included both positively and negatively worded statements, and total scores (range: 20-80) were calculated by reversing positively worded items and summing all item scores, with higher scores indicating greater state anxiety.

[0282] EEG, EMG, and EoG data recorded from the experimental device and additional channels using at right EoG and Oz, Pz, Cz, Fz, were sampled at 500Hz and preprocessed to remove ECG / motion artifacts and baseline drift using a third-order Butterworth bandpass filter. Recordings were scored in 30-second epochs, and each epoch was classified into one of five stages: wake (W), non-rapid eye movement sleep stages (Nl, N2, N3), or rapid eye movement (REM) sleep, based on the characteristics of EEG, EoG, and EMG patterns.Epochs were scored as (i) N 1 based on low-amplitude mixed-frequency EEG with slow eye movements, (ii) N2 based on the presence of sleep spindles and / or K-complexes, (iii) N3 by high-amplitude (>75 gV), low-frequency (< 4 Hz) delta waves, and (iv) REM sleep by low-amplitude mixed-frequency with rapid eye movements in EoG, and muscle atonia in EMG. Sleep staging data were then summarized and calculated for total sleep time (TST), sleep efficiency, proportion of time spent in each sleep stage, number of arousals, number of transitions for each stage, and state transition probability matrices. The study used these metrics for group comparisons by performing multiple paired t-tests.

[0283] 5 -minute ECG recordings were extracted and filtered using a third-order Butterworth bandpass filter between 5 and 15 Hz to enhance the R-wave peak. 'The root mean square of successive differences (RMSSDHRV) was calculated from the filtered enhanced RR interval time series

[0146] ,

[0147] , as shown in Equation 5, where RR is the time between two successive R-waves.RMSSDHRV(Eq. 5)Attorney Docket No. 10046-659W018551 WAN

[0284] For each participant, a transition matrix was created by counting the number of transitions from state i to state j, where i, j G {W, Nl, N2, N3, REM}. 'Transitions were defined as consecutive changes between epochs, excluding self-transitions (i.e., remaining in the same stage). The raw counts were normalized by the total number of transitions from each originating state to obtain state-to-state transition probabilities, as shown in Equation 6.number of transitions from i to jl~’!ILk number of transitions from i to k(Eq. 6)

[0285] FIG. 4K shows a group-level state transition probability matrix for each experimental condition (FUS vs. Sham). FIG. 4K, subpanel (a) shows a probability matrix of the healthy group during the sham condition. FIG. 4K, subpanel (b) shows a probability matrix of the healthy group during STN-FUS using the experimental device. FIG. 4K, subpanel (c) shows a change in the probability matrix in the healthy group. FIG. 4K, subpanel (d) shows a probability matrix of the insomnia group during the sham condition. FIG. 4K, subpanel (e) shows a probability matrix of the insomnia group during STN-FUS using the experimental device. FIG. 4K, subpanel (f) shows a change in the probability matrix in the insomnia group. FIG. 4K, subpanel (g) shows the Frobenius distance of state transition matrices between FUS vs. Sham for healthy and insomnia groups, (n = 15 and 11, two-sided t-test). FIG. 4K, subpanel (h) shows a statistical analysis of state transitions (row-based chi-squared test and Mantel Spearman test).

[0286] Group-level transition matrices were computed by summing individual matrices within each experimental condition (FUS vs. Sham). A difference matrix (FUS - Sham) was calculated to visualize absolute differences in transition counts between conditions (see FIG.4K). The overall magnitude of difference between group and individual matrices was quantified using the Frobenius norm

[0148] , as shown in Equation 7.‖F‖(Eq. 7)

[0287] To assess row-wise differences in transition patterns (i.e., from each originating state), the study performed chi-square tests of independence on each row of the aggregated transition matrices, comparing the distribution of outgoing transitions between sham and FUS conditions

[0149] , P- values were corrected for multiple comparisons using Tukey’s and false discovery rate (FDR) correction (e.g., Benjamini -Hochberg procedure). At the matrix level, the study computed the Mantel test to evaluate the similarity between the sham and FUSAttorney Docket No. 10046-659W018551 WAN transition matrices. The Mantel test calculated the Spearman correlation between the off- diagonal elements of the two matrices and assessed significance using 10,000 label permutations

[0150] ,

[0288] Functional Magnetic Resonance Imaging. The study analyzed functional MRI data using Analysis of Functional NeuroImages (AFNI). Preprocessing included motion correction, slice timing correction, spatial normalization to the 1-mm slice MNI152 standard space, and spatial smoothing with a 6 mm full-width at half-maximum (FWHM) Gaussian kernel. The study conducted first-level statistical analyses using a general linear model (GLM), which modeled task conditions with canonical hemodynamic response functions and included six motion parameters as nuisance regressors. The study then applied temporal autocorrelation correction and high-pass filtering (cutoff = 100 s). The study carried forward individual contrast maps to group-level analyses using AFNI’s 3dLME for linear mixed- effects modeling for mixed-effects estimation with probabilistic threshold-free cluster enhancement. The study visualized all statistical maps on the MNI152 template using AFNI.

[0289] The study extracted a blood oxygen level dependence variability (BOLD) time series from a predefined anatomical mask of the left subthalamic nucleus

[0151] , The region of interest (ROI) was defined in MNI152 standard space using a high-resolution subcortical atlas and resampled to match the spatial resolution of each subject’s preprocessed functional data. Functional images were temporally bandpass filtered (e.g., 0.01 - 0.1 Hz) and detrended to remove low-frequency drifts. The left STN mask was then applied to each subject’s preprocessed 4D fMRI for both pre-FUS and post-FUS dataset. Resting-state BOLD variability was then obtained through Equation 8 by taking the standard deviation of the BOLD time-series data extracted within-subject for interpreting activity and behavior at the left STN

[0152] (see FIG. 4C, subpanel (e)). The resulting time series served as the seed regressor for subsequent correlation analyses. The study included head motion parameters, white matter, and cerebrospinal fluid (CSF) signals as nuisance regressors to reduce physiological and movement-related confounds.NrsBOLDSD= (1 / N) Σ rsBOLD(t)(Eq. 8)

[0290] Amplitude of low- frequency fluctuation (ALFF) in resting-state fMRI signals was used to reflect the intensity of regional spontaneous brain activity

[0153] , As such, BOLD time series extracted from the left STN were filtered between 0.01 - 0.10 Hz using a band-passAttorney Docket No. 10046-659W018551 WAN filter to remove low-frequency drift and high-frequency respiratory and cardiac noise [154-155]. 'The power spectral density of the time series was then obtained through Equation 9, where N is the number of voxels within the mask and [FFT(rsBOLD t) is the Fast Fourier Transform of the BOLD time series within the mask

[0156] . The resulting power spectral density reflects the ALFF at the left STN, where a paired t-test was used to evaluate the statistical difference among each frequency bin (FIG. 4C, subpanel (f)).1rsBOLDALFF= |[FFT(rsBOLD(t))]2|(Eq. 9)

[0291] Within each subject, the left STN mask was used as the region of interest, serving as the seed region. A voxel-wise Pearson correlation between the seed region and every other brain voxel was calculated through AFNI. Correlation maps were then Fisher Z-transformed to generate a Fisher-Z score map. Group-level statistical modeling was performed using AFNI’s multivariate model (multi variate modeling of variance) and linear' mixed effect models, allowing the i nclusion of both within-subject factors (e.g., condition: Pre-FUS vs. Post-FUS or Sham vs. FUS) and between-subject variables (e.g., group, sex). The contrast map was then clustered using probabilistic threshold-free cluster enhancement to account for false positives. The output included voxel-wise F- and t-statistics for main effects and interactions. Significant connectivity maps were visualized on the MNI152 template using AFNI. Selected ROI masks of brain structures associated with the basal ganglia circuit were used to mask and extract the mean t-score to determine the group-level effects of FUS compared to the sham condition (FIG. 4C, subpanel (g)).

[0292] Pseudo-continuous arterial spin labelling (pCASL) data were acquired using a 3T MRI scanner with a 64-channel head coil. The arterial spin labelling (ASL) sequence first involved a rapid gradient scan to place a labeling plane between the carotid bifurcation and the vessel segment perpendicular to the carotid artery. Subsequently, the study performed a sequence of 10-minute scans that had a series of background-suppressed-control -label pair acquisitions with a 3D gradient-echo EPI. The ASL was preprocessed and quantified using Python and FSL’s Brain Extraction Tool

[0157] , Preprocessing included motion correction, brain masking, and spatial smoothing with a 5 mm FWHM Gaussian kernel. Pairwise subtraction of label and control images was performed to generate perfusion-weighted images, followed by calibration to compute quantitative cerebral blood flow' (CBF) maps in units of mL / 100 g / min. Standard quantification assumed a labeling efficiency of 0.85, T1Attorney Docket No. 10046-659W018551 WAN blood ~ 1.65 s, and a blood- brain partition coefficient of 0.9 mL / g. All CBF maps were registered to the MNI152 2 mm standard space using affine and nonlinear warping

[0158] ,

[0293] FIG. 4L shows stress adaptation and response with STN-FUS (enabled by the experimental device) during the Hariri Task. FIG. 4L, subpanel (a) shows effects of the experimental device under emotion-based and facial-based stimuli (Hariri Task) under varying conditions (e.g., Anger, Fear, Happy, Neutral, Shapes) in left / right ipsilateral Amygdala, STN, SNc, and SNr for healthy and insomnia groups. Decreased activity in the left SNc / SNr under emotional salient stimuli was observed in the healthy group (n = 16, two- way Analysis of Variance (ANOVA) and Tukey’s multiple comparison correction). Elevated activity across all conditions in the Amygdala bilaterally was observed in the insomnia group (n = 12, two-way ANOVA and Tukey’s multiple comparison correction). FIG. 4L, subpanel (b) shows effects of STN-FUS during FUS and Sham, indicating decreased activity in the left ITG-a, PBP, RN, SNc / SNr, and VTA, with elevated cortical activity observed in the healthy group. Contrarily, the insomnia group had substantial inhibitory and excitatory effects across the brain (n = 16 and 12, linear mixed effect models with probabilistic threshold-free cluster enhancement (pTFCE)). pTFCE values were zeroed between -4.90 and 4.90 for statistical representation. FIG. 4L, subpanel (c) shows a sagittal image of voxel-wise group-level analysis with pTFCE under conditions in healthy and insomnia groups. FIG. 4L, subpanel (d) shows a change in heart rate variability by root mean square of successi ve differences of R-peak waves in ECG obtained between evening (pre-sleep) and morning (post-sleep) (n = 16 and 12, two-way ANOVA and Sidak’s test). FIG. 4L, subpanel (e) shows a response time during the Hariri Task (n = 16 and 12). A decrease in response time during Anger and Fear conditions was observed in the healthy group. All plots show mean ± s.e.m unless otherwise mentioned, *P < 0.05, **P < 0.01, ***P < 0.001, and *pTFCE > 14.901.

[0294] The study used the Hariri Task, an emotional face processing task [ 159-160] associated with stress response, to test the effects of FUS (see FIG. 4J, subpanel (a). With reference to a similar previous study

[0043] , faces from the NimStim set were used and organized into blocks of 10 trials of various conditions, where two blocks of each condition were pseudo-randomly ordered (e.g., Anger, Fear, Happy, Neutral, Shapes) and balanced for gender and ethnicity

[0161] , The Hariri Task involved neutral face and shape comparator conditions to account for and separate emotion-specific or face-processing effects. Each block included 10 trials, each trial lasting for 4 seconds, involving individuals prompted to a reference face / shape (top) and two selection faces / shapes (bottom) for 3 seconds, followed by a 1 -second fixation cross between trials. Participants matched the reference to one of the twoAttorney Docket No. 10046-659W018551 WAN selection faces / shapes using a button box. Tasks were presented using PsychoPy version 3.0.1, where visual stimuli were synchronized to scanner triggers, and stimulus onset times and response times (see FIG. 4L, subpanel (c)) were logged for subsequent modeling

[0162] , Simultaneously, the study conducted functional MRI using EPI scans (e.g., 1'2-weighted single-shot gradient-echo planar imaging). Condition onset times were derived from PsychoPy logs and formatted to AFNI-compatible stimulus timing files. In addition to the condition regressors, the GEM model included six motion parameters (e.g., three translational and three rotational components), baseline drift terms (Legendre polynomials up to third order), and censoring of TRs with motion exceeding 0.3 mm or outlier signal spikes.

[0295] Beta coefficients and t-statistics were estimated for each condition, and linear contrasts were defined to assess task-related effects (e.g., Anger vs. Shapes, Fear vs. Shapes). Two-way ANOV A with Tukey’s multiple comparison with each group (FUS / Sham) on the left and right ipsilateral ROI under each condition (Anger, Fear, Happy, Neutral) were compared to the control condition (Shapes) and labelled with an asterisk for p < 0.05.Individual-level contrast maps were carried forward to group-level analysis using linear mixed-effect models, where each mixed-effect model incorporated within-subject factors (Condition, i.e., Anger vs Shapes) and between-subject factors (e.g., Group: FUS vs Sham). Voxel-wise statistical maps for main effects and interactions were corrected for multiple comparisons using probabilistic threshold-free cluster enhancement (pTFCE) to improve sensitivity and true positive signal

[0163] , Spatial smoothness of residuals was estimated with the autocorrelation, and pTFCE thresholds were determined to control the family-wise error rate (voxel-wise p < 0.05, pTFCE Z < 0.05). FIGs. 4M - 4N show statistical maps on the MNI152 template using AFNI.

[0296] FIG. 4M shows a task-based comparison of beta coefficients between faces and shapes for emotional salient recognition from the healthy and insomnia groups, under varying conditions (e.g., Anger, Fear, Happy, Neutral, Shapes, FUS, Sham). Significant differences between compared conditions are labelled with *.

[0297] FIG. 4N shows a voxel-wise group-level analysis with probabilistic threshold-free cluster enhancement of the Hariri Task. FIG. 4N, subpanel (a) shows a sagittal image of voxel-wise group-level analysis with pTFCE under conditions in healthy and insomnia groups, thresholded at pTFCE Z-score = 4.90. FIG. 4N, subpanel (b) shows a summary of effects under FUS vs. Sham for pTFCE Z-scores in brain regions across healthy and insomnia participants under varying conditions (e.g., Anger, Fear, Happy, Neutral, Shapes). pTFCE values were zeroed between -4.90 and 4.90 for statistical representation.Attorney Docket No. 10046-659W018551 WAN

[0298] Experimental Results

[0299] Eco-PEIE-Gel. Silicon-based elastomers, e.g., Ecoflex and polydimethyl siloxane (PDMS), have been used in flexible wearable electronics. However, due to the interfacial Van der Waals force, their innate adhesion strength to skin is low

[0032] , Furthermore, when comparing Ecoflex and PDMS, Ecoflex provides flexible and soft mechanical properties due to its low Young’s modulus. According to previous studies, utilizing polyethyleneimine ethoxylated solution (PEIE) mixed with PDMS enabled a homogenous cross-linked network with skin adhesion of -0.48 N / cm and Young’s modulus of 24 kPa

[0033] . The instant study chose Ecoflex-Gel, modified with PEIE, as the backbone of the experimental device’s bioadhesive layer to create a robust and soft elastomer (Eco-PEIE-Gel). The addition of PEIE created a polymer chain of amine, hydroxyl, and carboxylic groups important for creating hydrogen bonding, electrostatic ion pairing, and ammonium-carboxylic pairing with the stratum corneum (see FIG. 4A, subpanels (a) - (b)). The surface modification of PEIE also created small pores, supplementing mechanical interlocking structures aside from the minuscule Van der Waals force. Evaluation of the chemical structures with PEIE addition at various weight loadings, using Attenuated Total Reflectance with Fourier Transform Infrared spectroscopy (ATR-FTIR), indicated the addition of N-H and O-H groups, which validated the improved interfacial adhesion of skin (see FIG. 4A, subpanel (c)) for Eco-PEIE-Gel. To demonstrate universal adhesiveness, an Eco-PEIE-Gel substrate was prepared with a 0.95:0.05 weight ratio of Ecoflex-Gel to PEIE and applied to metal (Al, Cu, Fe), thermoplastic polymers (PLA, PP), elastomers (Ecoflex-050, PDMS), and skin. Overall, the adhesion strength of the Eco-PEIE-Gel substrate remained > 0.6 N / cm, except for Ecoflex-050 and silicon (see FIG. 4A, subpanel (d)). The adhesion strength of the Eco-PEIE-Gel substrate with skin (0.749 ± 0.177 N / cm) provided a 2,024% increase compared to Ecoflex- Gel alone (0.037 N / cm)

[0034] . Adhesion cycling on skin was then performed at 5% and 10% weight loading, for up to 20 cycles, demonstrating stable and sustained adhesion (see FIG.4A, subpanel (e)) for the Eco-PEIE-Gel substrate. Moreover, the increased PEIE loading improved the stretchability of the Eco-PEIE-Gel while maintaining high flexibility (E = 18.11 ± 0.07 kPa at 5% wt), resembling a 25% increase in flexibility compared to PDMS (see FIG.4A, subpanels (f) - (h)). Overall, Eco-PEIE-Gel improved bioadhesives with robust and stable interfacial adhesion, which was suitable for long-term sleep recording and neuromodulation with heavy transducers.

[0300] AMPS-based Sleep Gel (ASG). Previous studies in the development of a self-adhesive and stable hydrogel for sleep recording using 2-acrylamido-2-methylpropaneAttorney Docket No. 10046-659W018551 WAN sulfonic acid (AMPS) with poly(3,4-ethylenedioxythiophene) (PEDOT: PSS) enabled a high ionic conductivity and water absorption capability 126]. Similarly, sodium-based PEDOT: PSS hydrogels enabled similar efficacy for sleep recording

[0035] , Despite exemplary performance, the need for PEDOT: PSS with residues on the scalp led to inconveniences and discomfort for long-term wearability, with potential contamination of the device visually. In previous studies, a bioadhesive acoustic hydrogel utilizing an AMPS-based network provided a long-term stable adhesion to the scalp for up to 28 days

[0022] , Therefore, the study developed an AMPS-based Sleep Gel (ASG) by using the poly(AMPS) chain network with water-glycerol solvent that is (i) initiated with ammonium persulfate (APS) and (ii) catalyzed with a thermo-initiator (Tetramethylethylenediamine, TEMED) cross-linked with methylenebisacrylamide (MBAA). This created a soft, clear, and adhesive hydrogel to the skin (see FIG. 4A, subpanels (i) - (k)), with the on-skin adhesion of 0.606 + 0.231 N / cm, similar to the Eco-PEIE-Gel.

[0301] While the ASG’s adhesion may not be comparable to previous studies, the study focused on the ASG hydrogel's low impedance to improve the sleep recording signal quality because the adhesion of Eco-PEIE-Gel in the large area of the experimental device provided sufficient support to the skin (see FIG. 4A, subpanel (a)). Removing PEDOT: PSS that operates via conjugated-Ti-electron networks, and using solely AMPS as the primary ionic monomer suitable for skin interfaces, allowed for improved biocompatibility and conductivity with the presence of salt ions in sweat. The study then (i) increased glycerol content to improve hydration retention and (ii) utilized a thermal initiator (MBAA) to mitigate the inhomogeneous curing (e.g., by an impermeable light of PEDOT: PSS) of the ASG hydrogel when using photo-initiators. Additionally, thermal heating created a drier surface with improved adhesion while maintaining high water content internally, resulting in low impedance in the ASG.

[0302] As a result, the trade-off in adhesion enabled a 50% decrease in impedance within the critical EEG signal band range of 1-100 Hz, performing favorably compared to commercial-grade electrodes and conductive gels (see FIG. 4A, subpanels (l) - (m))

[0036] . To assess long-term impedance stability, ASG and commercial electrodes / gels were applied to the skin and monitored over 8 hours. The ASG performed similarly to the commercial-grade electrodes and had good stability. To further demonstrate the feasibility of a stable sleep recording with ASG, the ASG was integrated into the experimental device. Three participants then simultaneously wore the experimental device and a commercial EEG headcap (e.g., AntNeuro 32-channel EEG headcap). There was no difference in terms of signal quality andAttorney Docket No. 10046-659W018551 WAN sleep staging (see FIG. 4A, subpanels (n) - (p); FIG. 41). The development of the ASG provided a soft, comfortable, and low impedance electrode that enabled sleep recording, which was essential for electrophysiological recording in the experimental device.

[0303] Concentric Ring Ultrasound Transducer Array (CRUTA). The 8-channel piezoelectric concentric ring transducer array (CRUTA) used the high electromechanical coupling of bulk piezoelectric to generate high acoustic pressures at a specific resonant frequency (high Q-factor) and hybridized the bulk piezoelectric with soft elastomer encapsulation to enable a light-weight, comfortable, and acoustic coupling with soft biological tissue

[0037] ,

[0038] . The combination of design and flexible housing enabled the CRUTA to weigh less than 103.4 g and be 3.5 mm thick, 80% thinner than current ultrasound stimulation devices

[0039] ,

[0040] . The CRUTA with a thickness of 3.1 mm had a center frequency of 0.65 MHz, where successful neuromodulation was in the cortex

[0022] ,

[0041] , thalamus

[0042] , and amygdala

[0043] , This enabled a millimeter axial resolution (see FIG. 4G, subpanels (a) - (d); FIG. 4F) by controlling the phase delay between each channel element, comparable with current ultrasound stimulation devices operating at similar frequencies (see Table 1). Transfer printing of a laser-etched bilayer stacking of polyimide (e.g., PI, 24 pm, Cu 660 pm) was used to fabricate flexible electrodes to interconnect between the eight concentric ring arrays of transducers and LEMO-OO wires. The array was configured to target the STN through the temporal skull above the zygomatic arch, with coverage of varying anatomical positions across the general population in STN (72.2 ± 4.62 mm, see FIG. 4B) from the temporal window. Acoustic pressure of the CRUTA was adjustable through changes in voltage driven from the Vantage 64LE system (see FIG. 4G, subpanel (d); FIG. 4F).Variances in performances of CRUTA were accounted for by characterization of locality, acoustic pressure, and impedance.

[0304] In addition, the study characterized acoustic pressure fields emitted from the CRUTA using a calibrated hydrophone on a motorized 3-axis system submerged in a degassed distilled water tank (see FIG. 4G, subpanel (a)). Firstly, the study measured acoustic field distribution in free-field, where the full-width half maximum (FWHM) of axial and radial beam profiles increased exponentially (see FIG. 4B). At the desired STN of 72.2 mm, the axial / radial FWHM in free-field and skull were 44.6 mm / 58.6 mm and 18.6 / 5.2 mm, respectively. The focus of the beam profiles decreased as the focal depth increased due to the constraints of the geometric transducer diameter (47.57 mm) and center frequency due to the principle of interference in acoustics

[0044] , The complexity of the effects of skull-altering beam properties depended on the morphology, thickness, and angulation of the skull

[0045] , AsAttorney Docket No. 10046-659W018551 WAN such, previous studies using transcranial focused ultrasound computational models, constructed from computed tomography (CT) and magnetic resonance (MR) scans in varying sexes and skull segments, have demonstrated a spatial focusing effect on the beam profile through the temporal window

[0046] , As such, improvement in FWHM was observed when the temporal skull was present both axially and radially with the CRUTA (see FIG. 4G, subpanels (e) - (f); FIG. 5A).

[0305] FIG. 5A shows the spatial resolution of the CRUTA of the experimental device. FIG. 5A, subpanel (a) shows average axial full-width half maximum measured at various focal depths dependent on the delay variable (n = 8) in free-field and with a temporal skull. FIG. 5A, subpanel (b) shows the average radial full-width half maximum measured at various focal depths dependent on the delay variable (n = 8) in free-field and with a temporal skull.

[0306] ST -FUS-induced Ipsilateral Changes of the Basal Ganglia Network. Deep brain stimulation at the STN (STN-DBS) for Parkinson’s disease improves motor symptoms and sleep quality and reduces sleepiness

[0047] ,

[0048] . Specifically, STN-DBS has increased REM duration percentage from +1.3%

[0049] to 6.2%

[0015] . Yet, the need for an invasive surgical implant leads to long-term complications, including cognitive

[0050] and non-motor

[0001] decline, and glial response-induced inflammation, resulting in reduced efficacy

[0052] , In the study, the STN-FUS provided a non-invasive alternative to emulate the same outcomes of STN-DBS. STN plays a vital role in inhibiting movement and attentional processes

[0054] . Furthermore, inhibition of the STN suggested a promotion of muscle atonia and reduced wakefulness [55-58], Here, for the first time, the study utilized FUS to target STN using the CRUTA.

[0307] Sixteen participants (see FIG. 4B and Table 4) with a broad spectrum of age and self-reported sleep diagnoses were represented through the Pittsburgh Sleep Quality Index (PSQI). An initial pilot-study test with STN-FUS with fMRI-compatible BrainSonix was performed and indicated a bi-modal effect at the STN dependent on the pulse repetition frequency (PRF), where 10 Hz induced excitatory and 100 Hz induced inhibitory effects (see FIG. 5B). The effects in higher frequencies aligned with the results in the study, where high frequencies

[0059] ,

[0060] (e.g., > 100 Hz) improved symptoms with broadly attenuated betaband power and low frequencies (e.g., < 60Hz) amplified alpha / low-beta power local field potentials in the STN

[0061] ,

[0062] , As such, the CRUTA used 100 Hz PRF throughout the study to promote inhibition of STN. Each participant was subjected to a session having an anatomical scan followed by a pre-FUS resting state functional scan (Pre-Evaluation) to establish baseline and targeting of the STN (see FIG. 4C, subpanels (a) - (b)) before beingAttorney Docket No. 10046-659W018551 WAN subjected to 10 blocks of FUS (see Table 7, pressure: 0.90 MPa, 30s ON 30s OFF, pulse duration = 0.5 ms, pulse repetition frequency = 100 Hz), followed by a post-FUS resting state functional scan for comparison. The study selected a threshold of derated acoustic power that took into account the temporal bone (>0.70 MPa) to ensure biosafety and sufficient intensity

[0017] ,

[0043] ,

[0063] ,

[0064] , The study measured blood oxygen saturation levels, heart rate, and blood pressure throughout the session, indicating changes with STN-FUS using CRUTA on health vitals (see FIG. 4C, subpanels (c) - (d) ).

[0308] FIG. 5B shows the pulse repetition frequency effects of STN-FUS, which were measured by functional magnetic resonance imaging (fMRI). Specifically, FIG. 5B shows the beta coefficient blood oxygen level-dependent (BOLD) signal response across the whole brain with respect to 10 Hz vs 100 Hz STN-FUS, using BrainSonix BX Pulsar 1002 (n = 2).

[0309] Blood oxygen level-dependent (BOLD) time-series extracted from the left STN through region-of-interest (ROI) constrained analyses revealed an increase in resting-state BOLD variability (rsBOLDSD). The rsBOLDSDserved as a biomarker to cognitive states correlating to brain glucose metabolism and inversely correlated to task activations

[0065] ,

[0066] , The increase in rsBOLDSDpost-FUS reflected elevated metabolic demand associated with increased synaptic input and firing rates

[0067] (see FIG. 4C, subpanel (e)). To further evaluate the effects of STN-FUS, the power spectral density of the time series constrained to 0.01-0.10 Hz highlighted changes in the default-mode network (DMN) [67-69], An increase in concentrated energy was observed below 0.03 Hz with STN-FUS, which was connected to lower frequencies of the EEG band correlated to sleep

[0070] (see FIG. 4C, subpanel (f)). These results indicated the effectiveness of STN engagement towards sleep promotion. As the STN plays a key role in the basal ganglia network, the study examined the effects of STN-FUS on cerebral blood flow (CBF) at various associated brain regions (see FIG. 4C, subpanel (g)). An ipsilateral increase in CBF was observed at the left nucleus accumbens (NAc), indicating heightened metabolism and limbic disinhibition downstream of the STN. As a result of the expected inhibition of the STN by FUS, the suppressed output of glutamatergic (Glu) projection to the globus pallidus interna (GPi), globus pallidus externa (GPe), substantia nigra pars reticulata (SNr), substantia nigra pars compacta (SNc), and ventral medial prefrontal cortex (vmPFC) (see FIG. 3A, subpanel (c)) resulted in greater excitatory drive of the Nac

[0071] .

[0310] Resting-state functional connectivity (rsFC) provided a basis for understanding changes in the resting-state network due to brain stimulation

[0072] . To further evaluate the effects of STN-FUS, the study performed a group-level analysis of rsFC with the L-STN as the seed region with linear-mixed model effects and probabilistic threshold-free clusteringAttorney Docket No. 10046-659W018551 WAN enhancement (pTFCE). The ipsilateral (left) GPe, GPi, and Putamen (Pu) were positively connected to the STN, whereas the contralateral (right) GPe, GPi, and Pu remained negatively connected (see FIG. 4C, subpanel (h)). The results aligned with the effects of STN-DBS, where an increase in rsFC in GPe, GPi, and Pu ipsilateral to the stimulation site was induced. As the STN-GPe served as the self-regulating pacemaker to the cortico-basal ganglia-thalamo-cortical (CBGTC) loop

[0073] , the observed increase in positive rsFC between GPe and STN was consistent with known mechanisms, in which the GPe’s tonic GABAergic (GABA) inhibition to the STN reflected an inhibitory dynamic in the STN due to FUS

[0074] . Additionally, the left NAc’s rsFC trending negatively in parallel with increased CBF further suggested that STN-FUS potentially affected the limbic loop, which is important in sleep regulation aside from the basal ganglia network [75 J. The increase in negative rsFC between NAc, where STN inhibition occurred, indicated potential improvements in behavioral impulsivity and decreased reaction time (see FIG. 4L, subpanel (c)) in the context of premature responding through the limbic system [76-78]. The study observed an alteration and elevation in the inhibitory-excitatory regulation between the STN and other basal ganglia and limbic structures. The changes in connectivity patterns following FUS stimulation could indicate the neuromodulatory effects of STN-FUS in support of improving sleep regulation.

[0311] STN-FUS-induced REM sleep enhancement. The study evaluated the efficacy of STN-FUS using the experimental device in two consecutive nights of sleep (see FIG. 4J, subpanel (a)). Two groups of participants, the healthy group and the insomnia group, were screened and enrolled based on Pittsburgh Sleep Quality Index (PSQI) evaluations. Before the sleep session and again the following morning, the participants completed a series of clinical questionnaires (see FIG. 4J, subpanel (b)) and underwent vital sign and heart rate variability assessments using electrocardiography (ECG). The study conducted the vital sign and heart rate variability assessments to monitor any unexpected or adverse effects of STN-FUS (see FIGs. 5C - 5D) on the healthy and insomnia groups (see Tables 5 and 6). The participants in both groups were exposed to the sham condition on the first night and STN- FUS on the second night, followed by fMRI scans in the morning, as discussed above.

[0312] FIGs. 5C - 5D show the secondary outcome of the experimental device on the healthy and insomnia groups, respectively. As shown, the experimental device did not create adverse vital changes in blood pressure, heart, and SpO₂. Quantitative results of participant self-report showed improved wakefulness in both sham and FUS nights, with a more prominent decrease in the Stanford Sleepiness Scale in the healthy groups, and a more prominent decrease in the Epsworth Sleepiness Scale in the insomnia groups.Attorney Docket No. 10046-659W018551 WAN

[0313] The study determined the REM enhancement effects of STN-FUS using polysomnographic evaluation, with EEG data recorded using the experimental device, as discussed above. The study presented 28 participants across polysomnographic data (see FIG.4J, subpanel (c)) of the healthy and insomnia groups. The study omitted the polysomnography data of two participants, 1 and 25, due to extensive noise across all channels. STN-FUS using the experimental device (see Table 1) increased REM duration for both healthy group (15.1 + 7.38%; Sham / 19.4 + 5.25%; FUS) and insomnia group (17.902 + 7.10%; Sham / 23.2 + 6.47%; FUS) (see FIG. 4J, subpanel (d)). The experimental device also decreased REM latency for healthy group (177 + 117 min; Sham / 123 + 57.1 min; FUS) but minimally for insomnia group (176 + 82.2 min; Sham / 146 + 106 min; FUS) (see FIG. 41, subpanel (e)). In addition, STN-FUS did not cause changes to arousals (healthy: 19.1 + 5.56, Sham / 18.7 ± 9.08 min, FUS; insomnia: 14.8 + 5.23, Sham / 14.6 + 6.12 min, FUS) and overall sleep efficiency (healthy: 80.0 + 9.97%, Sham / 81.4 + 10.6%, FUS; insomnia: 81.4 + 15.7%’, Sham / 80.6 + 13.4%, FUS) (see FIG. 41, subpanels (f) - (g)). Overall, the experimental device improved REM sleep performance without altering the sleep architecture in other sleep stages (e.g., Wake, Nl, N2, N3), and most participants responded positively in REM improvement (see FIG. 41, subpanels (h) - (o); Table 8).

[0314] Table 8 shows a summary of sleep performance metrics using the experimental device.Table 8Group Metrics Sham FUS Cohen’s d p-value REM Duration58.9 ± 30. 74.9 + 24.6 058 0.0280* (mm)REM Duration.,. „ „„15.1 + 7.38 19.4 + 5.25 0.67 0.0164* (%)1 Lvixlll 1 _ __,T(n = 15E - ^tency 177 + 117 124 + 57.1 -0.57 0.0165*_ (mm) _Arousals 19.1 + 5.56 18.7 + 9.08 0.05 0.8278SleeP Efficiency 80.0 + 9.97 81.9 + 10.6 0.18 0.6392 (%)REM Durationz,, 70.4 + 29.1 86.1 + 27.6 0.55 0.066 (mm)REM Duration „ „17.9 + 7.10 23.2 + 6.47 0.78 0.0113*T.Insomnia - ) - tn = ll)2 a enCy176 + 82.2 146 + 106 -0.31 0.2090 ' (min)Arousals 14.8 + 5.23 14.6 + 6.12 0.03 0.9325Attorney Docket No. 10046-659W018551 WAN REM Duration63 8 ± 29 9 79.7 ±26.0 0.57 0.0049*** (min)All REM Duration 16.3 + 7.26 20.9 + 5.99 0.71 0.0007**** (%;(Healthy + - ijf rvr i - Insomnia)'.. 177 ± 101 134 + 82.3 -0.46 0.0098*** ra Ill ——2f0o f..Arousals 17.3 + 5.73 16.9 + 8.08 0.04 0.82568(ZZZIZ1 sIZIIl 0 / 7598(%)

[0315] The high-level sleep architecture and dynamics may provide insights into the effects of STN-FUS and differences in healthy and insomnia groups

[0079] . Specifically, sleep stage state transition probability demonstrates changes across sleep apnea

[0081] , aging

[0081] , and insomnia

[0082] , The study computed a collective group-level state transition probability matrix for each condition (sham / FUS) and groups (healthy, insomnia) (see FIG. 4K, subpanels (a) - (c), (d) - (f)). In the healthy group, the likelihood of transitioning from N3 / REM sleep to wakefulness decreased, while transitions to N2 sleep increased (see FIG.4K, subpanel (c)). In contrast, the insomnia group showed the opposite pattern, with an increased likelihood of transitioning from N3 / REM to wakefulness and a decreased likelihood of transitioning to N2 sleep (see FIG. 4K, subpanel (f)). This aligned with the pathology of insomnia, given the susceptibility to arousals of the participants in the insomnia group [83 J. Despite the differences in groups, the N2 to REM probability increased while the remaining transitions remained similar, further supporting the effects of REM enhancement. To evaluate the broad effects of STN-FUS, the Frobenius Distance provided insight into the difference between sham and FUS matrices, where higher values indicated greater effects and / or differences

[0084] . The effects of STN-FUS using the experimental device resulted in a difference compared to sham (see FIG. 4K, subpanel (g)). Furthermore, this difference extended similarly to the healthy and insomnia groups (see FIG. 4K, subpanel (h)). Similarly, to ensure sleep architecture remained unchanged, the study performed stage-specific Chi-squared and Mantel tests, in which the transition matrices remained similar, indicating unchanged sleep architecture. Overall, the effects of STN-FUS did not necessitate an overall change in sleep architecture except for the selective enhancement of REM sleep. Together, these demonstrated the experimental device’s efficacy in utilizing STN-FUS to enhance REM sleep performance while maintaining the general sleep architecture of participants.

[0316] Stress Response of STN-FUS using the Experimental Device. The study further explored the effects of STN-FUS on stress response when using the experimental device. The morning after each of the two consecutive sleeps, participants, each with the experimentalAttorney Docket No. 10046-659W018551 WAN device, were subjected to a sequence of functional magnetic resonance imaging (fMRI) scans in conjunction with the Hariri task, a face-matching task associated with emotional stimuli in adaptive social behavior

[0085] , In addition to fearful and angry facial expressions, other stressors, such as confrontational or life-threatening conditions, elicited amygdala response [861. As such, previous studies implementing FUS for amygdala neuromodulation demonstrated the capability in modulating subcortical brain function, enabling improved mood, anxiety, and trauma-related disorders

[0043] .

[0317] The study performed ROI-constrained analyses to evaluate the effects of FUS (FUS vs. Sham) on task-dependent stimuli (e.g., Anger / Fear / Happy / Neutral / Shapes) on the healthy and insomnia groups. The study observed no significant changes in either left / right amygdala in BOLD signal obtained from beta coefficients due to FUS vs. sham in the healthy group (see FIG. 4L, subpanel (a)). Contrarily, the insomnia group exhibited an overall elevated amygdala activity across all conditions bilaterally with significance, commonly associated with sleep disorders

[0087] . The FUS increased amygdala activity under the anger stimuli. The study extended further ROI-constrained analyses of BOLD signal to localized basal ganglia structures (e.g., STN, SNc / SNr). SNc in the healthy group exhibited ipsilateral attenuation of the BOLD signal in anger stimuli and happy stimuli. Similarly, SNr in the healthy group showed attenuation in anger stimuli, fear stimuli, and happy stimuli.

[0318] Evaluation of interaction between task-dependent stimuli within conditions (e.g., FUS x [Anger vs. Shapes]) was performed and exhausted through a whole-brain analysis using the Harvard-Oxford atlas [91-94], The effects of FUS at the left ipsilateral localized region, including SNc, SNr, and STN, were observed with attenuated activity in the healthy group. Two-way ANOVA with Bonferroni’s multiple correction revealed significant attenuation for fear and happy stimuli (see FIG. 4M). Contrariwise, the insomnia group did not reveal changes at these regions. However, an elevation in activity across all conditions in limbic-associated regions (e.g., amygdala, intracalcarine cortex, lateral occipital cortex, and frontal operculum cortex) is commonly associated with insomnia and sleep disorders due to persistent vulnerability in emotion and arousal regulation [95-98 J.

[0319] Due to the potential inhomogeneity of activation in ROI (e.g., the STN having three anatomical subregions responsible for motor, associative, and limbic connectivity

[0099] ), the ROI-constrained analyses may lack spatial information

[0100] , As such, to further explore the effects of STN-FUS in the whole-brain with statistical significance, voxel-wise analysis conducted with pTFCE was extrapolated to evaluate the main effect of FUS vs Sham. The healthy group demonstrated an increase across the whole brain, apart from left ITG-a, PBP,Attorney Docket No. 10046-659W018551 WAN RN, SNc, SNr, and VTA (see FIG. 5B), whereas the insomnia group had an unclear mixture of increased and decreased activity across the brain (see FIG. 4L, subpanels (b) - (c); FIG.4N). As such, a correlation matrix of left vs. right ipsilateral ROI in response to FUS vs. Sham was investigated, where a suggestion of decreased correlation and disturbance in the overall brain connectivity was observed with more prominence in the contralateral ROI to STN-FUS (see FIG. 5E).

[0320] FIG. 5E show's a correlation analysis of the effects of STN-FUS on the participants. FIG. 5E, subpanel (a) show's correlation matrices of left and right ipsilateral ROI in response to Sham vs FUS conditions of collective beta coefficients from all conditions, during Hariri Tasks in all participants (e.g., from the healthy and insomnia groups). FIG. 5E, subpanel (b) shows the Pearson’s R correlation of beta coefficients with REM duration (%).

[0321] From a pathological perspective, the association of stress impacts on sleep performance caused vulnerability to insomnia and circadian disorders

[0101] , Stress response is complex, whereby being presented with identical stressors could result in different reactions across participants

[0102] ,

[0103] , The primary systems involved in autonomic regulation during psychological stress are the hypothalamic-pituitary -adrenal (HPA) axis and the sympathetic nervous system (SNS). Both play crucial roles in initiating the body's stress response, known as the "fight or flight" reaction

[0104] , This influences the heart rate, so the heart rate variability (HRV) correlates inversely with stress levels

[0105] , Here, the study observed the effects of the experimental device’s efficacy in STN-FUS targeting to modulate and increase HRV in the healthy group (-5.89 + 38.4%, Sham / 41.5 ± 54.7%, FUS).Conversely, the insomnia group did not respond with a decrease in HRV (26.9 ± 38.4%, Sham / 4.79 ± 56.4%, FUS) (see FIG. 4L). The lack of effect of STN-FUS on HRV for the insomnia group aligned with previous studies, indicating no changes in HRV in patients with insomnia [106-108] and even those with successful treatment of cognitive-behavioral treatment

[0109] ,

[0322] In addition, behavioral quantitative measures of response time during the Hariri tasks were measured, as impaired reaction times were identified and associated with sleep- deprived individuals

[0111] ,

[0112] , The healthy group demonstrated a reduction in response time, specifically during anger and fear task-dependent stimulus with FUS (see FIG. 4L, subpanel (e)). However, no improvement in response time w?as observed in the insomnia group. Overall, the results indicated that STN-FUS could down-modulate the ipsilateral basal-ganglia-midbrain-temporal circuit through the SNr / SNc and improve the stress response for healthy participants.Attorney Docket No. 10046-659W018551 WAN

[0323]

[0324] Disclosed are components that can be used to perform the disclosed methods and systems. These and other components are disclosed herein, and it is understood that when combinations, subsets, interactions, groups, etc. of these components are disclosed while specific reference of each various individual and collective combination and permutation of these may not be explicitly disclosed, each is specifically contemplated and described herein, for all methods and systems. This applies to all aspects of this application, including, but not limited to, steps in disclosed methods. Thus, if there are a variety of additional steps that can be performed, it is understood that each of these additional steps can be performed with any specific implementation or combination of implementations of the disclosed methods.

[0325] The references cited below are hereby incorporated by reference to disclose and describe the methods or materials in connection with which the publications are cited or to provide background for the present disclosure. Any incorporation by reference of documents below is limited such that no subject matter is incorporated by reference that is contrary to the explicit disclosure herein. In the event of inconsistent usages between this document and those documents so incorporated by reference below, the use in the incorporated references should be considered supplementary to that of this document; for irreconcilable inconsistencies, the usage in this document controls.[1] Mysliwiec, V. et al. Sleep disorders and associated medical comorbidities in active duty military personnel. Sleep 36, 167-174 (2013).[2] Troxel, W. M. et al. Sleep in the Military: Promoting Healthy Sleep Among U. S.Servicemembers. (Rand Corporation, 2015).[3] Seelig, A. D. et al. Sleep and Health Resilience Metrics in a Large Military Cohort.Sleep 39, 1111-1120 (2016).[4] Adjaye-Gbewonyo, D., Ng, A. E. & Black, L. I. Sleep Difficulties in Adults: United States, 2020. (2022) doi: 10.15620 / cdc:l 17490.[5] Alhola, P. & Polo-Kantola, P. Sleep deprivation: Impact on cognitive performance.Neuropsychiatric Disease and Treatment 3, 553 (2007).[6] Nollet, M., Wisden, W. & Franks, N. P. Sleep deprivation and stress: a reciprocal relationship. Interface Focus (2020) doi:10.1098 / rsfs.2019.0092.[7] Geiser, T. et al. Targeting Arousal and Sleep through Noninvasive Brain Stimulation to Improve Mental Health. Neuropsychobiology 79, 284-292 (2020).[8] Malkani, R. G. & Zee, P. C. Brain Stimulation for Improving Sleep and Memory. Sleep Med Clin 17, 505-521 (2022).Attorney Docket No. 10046-659W018551 WAN [9] Donde, C. et al. The Effects of Transcranial Electrical Stimulation of the Brain on Sleep:A Systematic Review. Front Psychiatry 12, 646569 (2021).

[0010] Grimaldi, D., Papalambros, N. A., Zee, P. C. & Malkani, R. G. Neurostimulation techniques to enhance sleep and improve cognition in aging. Neurobiol Dis 141, 104865 (2020).

[0011] Sonmez, A. I. et al. Accelerated TMS for Depression: A systematic review and meta¬ analysis. Psychiatry Res 273, 770-781 (2019).

[0012] Nuninga, J. O. et al. Immediate and long-term effects of bilateral electroconvulsive therapy on cognitive functioning in patients with a depressive disorder. J Affect Disord 238, 659-665 (2018).

[0013] Lim, A. S. et al. Selective enhancement of rapid eye movement sleep by deep brain stimulation of the human pons. Ann Neurol 66, 110-114 (2009).

[0014] Arnulf, I. et al. Sleep induced by stimulation in the human pedunculopontine nucleus area. Ann Neurol 67, 546-549 (2010).

[0015] Nishida, N. et al. Subthalamic nucleus deep brain stimulation restores normal rapid eye movement sleep in Parkinson’s disease. Mov Disord 26, 2418-2422 (2011).

[0016] Effects of deep brain stimulation of the subthalamic nucleus on sleep architecture in parkinsonian patients. Sleep Medicine 5, 207-210 (2004).

[0017] Legon, W. et al. Transcranial focused ultrasound modulates the activity of primary somatosensory cortex in humans. Nat Neurosci 17, 322-329 (2014).

[0018] Attali, D. et al. Deep transcranial ultrasound stimulation using personalized acoustic metamaterials improves treatment-resistant depression in humans. Brain Stimul. 18, 1004-1014 (2025).

[0019] Darmani, G. et al. Individualized non-invasive deep brain stimulation of the basal ganglia using transcranial ultrasound stimulation. Nat. Commun. 16, 2693 (2025).

[0020] Chou, T. et al. Transcranial focused ultrasound of the amygdala modulates fear network activation and connectivity. Brain Stimul. 17, 12-320 (2024).

[0021] Sarica, C., Darmani, G., Ramezanpour, H., Chen, R. & Lozano, A. M. Subthalamic local field potential dynamics during motor cortex and basal ganglia transcranial ultrasound stimulation. Brain Stimul. 18, 539 (2025).

[0022] Tang, K. W. K. et al. Bioadhesive hydrogel-coupled and miniaturized ultrasound transducer system for long-term, wearable neuromodulation. Nature Communications 16, 1-17 (2025).Attorney Docket No. 10046-659W018551 WAN

[0023] Acharya, U. R. et al. A Novel Depression Diagnosis Index Using Nonlinear Features in EEG Signals. Eur Neurol 74, 79-83 (2015).

[0024] Hsieh, J.-C. et al. Design of hydrogel -based wearable EEG electrodes for medical applications. J Mater Chem B 10, 7260-7280 (2022).

[0025] A highly stable electrode with low electrode-skin impedance for wearable brain¬ computer interface. Biosensors and Bioelectronics 218, 114756 (2022).

[0026] Hsieh, J.-C. et al. Design of an injectable, self-adhesive, and highly stable hydrogel electrode for sleep recording. Device 2, (2024).

[0027] Yuk, H., Lu, B. & Zhao, X. Hydrogel bioelectronics. Chem Soc Rev 48, 1642-1667 (2019).

[0028] Pellow, C., Pichardo, S. & Pike, G. B. A systematic review of preclinical and clinical transcranial ultrasound neuromodulation and opportunities for functional connectomics. Brain Stimul. 17, 734-7 1 (2024).

[0029] Liu, S., Rao, Y., Jang, IL, Tan, P. & Lu, N. Strategies for body-conformable electronics. Matter 5, 1104-1136 (2022).

[0030] Yang, Z., Ma, Z., Liu, S. & Li, J. Tissue adhesion with tough hydrogels: Experiments and modeling. Meeh. Mater. 157, 103800 (2021).

[0031] Xiong, Y. et al. A review of the properties and applications of bioadhesive hydrogels.Polym. Chem. 12, 3721-3739 (2021).

[0032] Jeong, J.-W. et al. Materials and optimized designs for human-machine interfaces via epidermal electronics. Adv. Mater. 25, 6839-6846 (2013).

[0033] Jeong, S. H., Zhang, S., Hjort, K., Hilborn, J. & Wu, Z. PDMS-based elastomer tuned soft, stretchable, and sticky for epidermal electronics. Adv. Mater. 28, 5830-5836 (2016).

[0034] Nishikawa, T., Yamane, H., Matsuhisa, N. & Miki, N. Stretchable strain sensor with small but sufficient adhesion to skin. Sensors (Basel) 23, (2023).

[0035] Xue, H. et al. Hydrogel electrodes with conductive and substrate-adhesive layers for noninvasive long-term EEG acquisition. Microsyst. Nanoeng. 9, 79 (2023).

[0036] Campbell, I. G. EEG recording and analysis for sleep research. Curr. Protoc. Neurosci.Chapter 10, Unitl0.2 (2009).

[0037] Jae Lee, IL, Zhang, S., Meyer, R. J., Sherlock, N. P. & Shrout, T. R. Characterization of piezoelectric ceramics and 1-3 composites for high power transducers. Appl. Phys. Lett. 101, 032902 (2012).Attorney Docket No. 10046-659W018551 WAN

[0038] Ates, H. C. et al. End-to-end design of wearable sensors. Nature Reviews Materials 7, 887-907 (2022).

[0039] Schafer, M. E., Spivak, N. M., Korb, A. S. & Bystritsky, A. Design, Development, and Operation of a Low-Intensity Focused Ultrasound Pulsation (LIFUP) System for Clinical Use. IEEE Trans Ultrason Ferroelectr Freq Control 68, 54-64 (202.1).

[0040] Meng, Y., Hynynen, K. & Lipsman, N. Applications of focused ultrasound in the brain:from thermoablation to drug delivery. Nature Reviews Neurology 17, 7-22 (2020).[41 J Legon, W., Bansal, P., Tyshynsky, R., Ai, L. & Mueller, J. K. Transcranial focused ultrasound neuromodulation of the human primary motor cortex. Sci. Rep. 8, 10007 (2018).

[0042] Neuroniodulation with single-element transcranial focused ultrasound in human thalamus, http: / / dx.doi.org / 10.1002 / hbm.23981 doi: 10.1002 / hbm.23981.

[0043] Barksdale, B. R. et al. Low-intensity transcranial focused ultrasound amygdala neuroniodulation: a double-blind sham-controlled target engagement study and unblinded single-arm clinical trial. Molecular Psychiatry 1-15 (2025).

[0044] Sard, A. & LucaLorini, F. Echocardiography for Intensivists. (Springer Science & Business Media, 2012).

[0045] Li, H. et al. Effects of skull properties on continuous-wave transcranial focused ultrasound transmission. J. Acoust. Soc. Am. 157, 2336-2349 (2025).

[0046] Mueller, J. K., Ai, L., Bansal, P. & Legon, W. Numerical evaluation of the skull for human neuroniodulation with transcranial focused ultrasound. J Neural Eng 14, 066012 (2017).

[0047] Bjerknes, S„ Skogseid, I. M„ Hauge, T. J., Dietrichs, E. & Toft, M. Subthalamic deep brain stimulation improves sleep and excessive sweating in Parkinson’s disease, npj Parkinson’s Disease 6, 1-7 (2020).

[0048] Baumann- Vogel, H. et al. The impact of subthalamic deep brain stimulation on sleep¬ wake behavior: A prospective electrophysiological study in 50 Parkinson patients. Sleep (2017) doi:10.1093 / sleep / zsx033.

[0049] Romigi, A. et al. Pedunculopontine nucleus stimulation influences REM sleep in Parkinson’s disease. Eur. J. Neurol. 15, e64-5 (2008).

[0050] Aviles-Olmos, I. et al. Long-term outcome of subthalamic nucleus deep brain stimulation for Parkinson’s disease using an MRI-guided and MRI- verified approach. J Neurol Neurosurg Psychiatry 85, 1419-1425 (2014).Attorney Docket No. 10046-659W018551 WAN

[0051] Lilleeng, B., Gjerstad, M., Baardsen, R., Dalen, I. & Larsen, J. P. The long-term development of non-motor problems after STN-DBS. Acta Neurol Scand 132, 251- 258 (2015).

[0052] Salatino, J. W., Ludwig, K. A., Kozai, T. D. Y. & Purcell, E. K. Glial responses to implanted electrodes in the brain. Nat Biomed Eng 1, 862-877 (2017).

[0053] Ultrasound Neuromodulation: A Review of Results, Mechanisms and Safety.Ultrasound in Medicine & Biology 45, 1509-1536 (2019).

[0054] Soh, C. et al. The human subthalamic nucleus transiently inhibits active attentional processes. Brain 147, 3204-3215 (2024).

[0055] Ghodrati, M., Alwis, D. S. & Price, N. S. C. Orientation selectivity in rat primary visual cortex emerges earlier with low-contrast and high-luminance stimuli. Eur J Neurosci 44, 2759-2773 (2016).

[0056] Beard, J. L. Iron status and periodic limb movements of sleep in children: a causal relationship? Sleep medicine vol. 5 89-90 (2004).

[0057] Chahine, L. M., Amara, A. W. & Videnovic, A. A systematic review of the literature on disorders of sleep and wakefulness in Parkinson’s disease from 2005 to 2015. Sleep Med Rev 35, 33-50 (2017).

[0058] Benarroch, E. E. Subthalamic nucleus and its connections: Anatomic substrate for the network effects of deep brain stimulation. Neurology 70, 1991-1995 (2008).

[0059] McConnell, G. C., So, R. Q., Hilliard, J. D., Lopomo, P. & Grill, W. M. Effective deep brain stimulation suppresses low-frequency network oscillations in the basal ganglia by regularizing neural firing patterns. J Neurosci 32, 15657-15668 (2012).

[0060] Neumann, W.-. T., Steiner, L. A. & Milosevic, L. Neurophysiological mechanisms of deep brain stimulation across spatiotemporal resolutions. Brain 146, 4456-4468 (2023).

[0061] Blumenfeld, Z. et al. Sixty-hertz stimulation improves bradykinesia and amplifies subthalamic low-frequency oscillations. Mov Disord 32, 80-88 (2017).

[0062] 62. Su, D. et al. Frequency-dependent effects of subthalamic deep brain stimulation on motor symptoms in Parkinson’s disease: a meta-analysis of controlled trials.Scientific Reports 8, 1-9 (2018).

[0063] Stern, J. M. et al. Safety of focused ultrasound neuromodulation in humans with temporal lobe epilepsy. Brain Stimul. 14, 1022-1031 (2.021).Attorney Docket No. 10046-659W018551 WAN

[0064] Yaakub, S. N. et al. Transcranial focused ultrasound-mediated neurochemical and functional connectivity changes in deep cortical regions in humans. Nat. Commun.14, 5318 (2023).

[0065] He, B. J. Scale -free properties of the functional magnetic resonance imaging signal during rest and task. J Neurosci 31, 13786-13795 (2011).

[0066] Garrett, D. D., Kovacevic, N., McIntosh, A. R. & Grady, C. L. The Modulation of BOLD Variability between Cognitive States Varies by Age and Processing Speed. Cereb Cortex 23, 684-693 (2012).

[0067] Oswal, A. et al. Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson’s disease. Brain 139, 1482- 1496 (2016).

[0068] Fransson, P. How default is the default mode of brain function? Further evidence from intrinsic BOLD signal fluctuations. Neuropsychologia 44, 2836-2845 (2006).

[0069] Fukunaga, M. et al. Large-amplitude, spatially correlated fluctuations in BOLD fMRI signals during extended rest and early sleep stages. Magn Reson Imaging 24, 979-992 (2006).

[0070] Horovitz, S. G. et al. Low frequency BOLD fluctuations during resting wakefulness and light sleep: a simultaneous EEG-fMRI study. Hum Brain Mapp 29, 671-682. (2008).

[0071] Rouaud, T. et al. Reducing the desire for cocaine with subthalamic nucleus deep brain stimulation. Proc. Natl. Acad. Sci. U. S. A. 107, 1196-1200 (2010).

[0072] Fox, M. D. et al. Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases. Proc. Natl. Acad. Sci. U. S. A. Ill, E4367-75 (2014).

[0073] Wichmann, T. & DeLong, M. R. Oscillations in the basal ganglia. Nature vol. 400 621-622 (1999).

[0074] Bevan, M. D., Hallworth, N. E. & Baufreton, J. GABAergic control of the subthalamic nucleus. Prog Brain Res 160, 173-188 (2007).

[0075] Goldstein, A. N. & Walker, M. P. The role of sleep in emotional brain function. Annu.Rev. Clin. Psychol. 10, 679-708 (2014).

[0076] Winter, C. et al. High frequency stimulation of the subthalamic nucleus modulates neurotransmission in limbic brain regions of the rat. Exp Brain Res 185, 497-507 (2008).Attorney Docket No. 10046-659W018551 WAN

[0077] Christakou, A., Robbins, T. W. & Everitt, B. J. Prefrontal cortical-ventral striatal interactions involved in affective modulation of attentional performance: implications for corticostriatal circuit function. J Neurosci 24, 773-780 (2004).

[0078] Sesia, T. et al. Deep brain stimulation of the nucleus accunibens core and shell:opposite effects on impulsive action. Exp Neurol 214, 135-139 (2008).

[0079] Laffan, A., Caffo, B., Swihart, B. J. & Punjabi, N. M. Utility of sleep stage transitions in assessing sleep continuity. Sleep 33, 1681-1686 (2010).

[0080] Bianchi, M. T., Cash, S. S., Mietus, J., Peng, C.-K. & Thomas, R. Obstructive sleep apnea alters sleep stage transition dynamics. PLoS One 5, el 1356 (2010).

[0081] Schlemmer, A., Parlitz, U., Luther, S., Wessel, N. & Penzel, T. Changes of sleep-stage transitions due to ageing and sleep disorder. Philos. Trans. A Math. Phys. Eng. Sci.373, 20140093 (2015).

[0082] Wei, Y. et al. Sleep stage transition dynamics reveal specific stage 2 vulnerability in insomnia. Sleep 40, (2017).

[0083] Di Marco, T. et al. Hyperarousal features in the sleep architecture of individuals with and without insomnia. J. Sleep Res. 34, e!4256 (2025).

[0084] Sun, II. et al. Large-scale automated sleep staging. Sleep 40, (2017).

[0085] Hariri, A. R., Tessitore, A., Mattay, V. S., Fera, F. & Weinberger, D. R. The amygdala response to emotional stimuli: a comparison of faces and scenes. Neuroimage 17, 317-323 (2002).

[0086] Davis, M. & Whalen, P. J. The amygdala: vigilance and emotion. Mol. Psychiatry 6, 13-34 (2001).

[0087] Baglioni, C. et al. Insomnia disorder is associated with increased amygdala reactivity to insomnia-related stimuli. Sleep 37, 1907-1917 (2014).

[0088] Walker, H. C. et al. Activation of subthalamic neurons by contralateral subthalamic deep brain stimulation in Parkinson disease. J. Neurophysiol. 105, 1112-1121 (2011 ).

[0089] Farokhniaee, A., Marceglia, S., Priori, A. & Lowery, M. M. Effects of contralateral deep brain stimulation and levodopa on subthalamic nucleus oscillatory activity and phase-amplitude coupling. Neuromodulation 26, 10-319 (2023).

[0090] Hasegawa, H. et al. The effect of unilateral subthalamic nucleus deep brain stimulation on contralateral subthalamic nucleus local field potentials. Neuromodulation 23, 509- 514 (2020).

[0091] Makris, N. et al. Decreased volume of left and total anterior insular lobule in schizophrenia. Schizophr. Res. 83, 155-171 (2006).Attorney Docket No. 10046-659W018551 WAN

[0092] Frazier, J. A. et al. Structural brain magnetic resonance imaging of limbic and thalamic volumes in pediatric bipolar disorder. Am. J. Psychiatry 162, 1256-1265 (2005).

[0093] Desikan, R. S. et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31, 968-980 (2006).

[0094] Goldstein, J. M. et al. Hypothalamic abnormalities in schizophrenia: sex effects and genetic vulnerability. Biol. Psychiatry 61, 935-945 (2007).[95 J Van Someren, E. J. W. Brain mechanisms of insomnia: new perspectives on causes and consequences. Physiol. Rev. 101, 995-1046 (2021).

[0096] Buysse, D. J., Germain, A., Hall, M., Monk, T. H. & Nofzinger, E. A. A neurobiological model of insomnia. Drug Discov. Today Dis. Models 8, 129-137 (2011).

[0097] Gong, L. et al. Amygdala changes in chronic insomnia and their association with sleep and anxiety symptoms: Insight from shape analysis. Neural Plast. 2019, 8549237 (2019).

[0098] Nofzinger, E. A. et al. Functional neuroimaging evidence for hyperarousal in insomnia.Am. J. Psychiatry 161, 2126-2128 (2004).

[0099] Prasad, A. A. & Wallen-Mackenzie, A. Architecture of the subthalamic nucleus.Commun. Biol. 7, 78 (2024).

[0100] Poldrack, R. A. Region of interest analysis for fMRI. Soc. Cogn. Affect. Neurosci. 2, 67-70 (2007).

[0101] Kalmbach, D. A., Anderson, J. R. & Drake, C. L. The impact of stress on sleep:Pathogenic sleep reactivity as a vulnerability to insomnia and circadian disorders. J. Sleep Res. 27, el2710 (2018).

[0102] Ellis, B. J., Jackson, J. J. & Boyce, W. T. The stress response systems: Universality and adaptive individual differences. Developmental Review 26, 175-212 (2006).

[0103] Pacak, K. & Palkovits, M. Stressor specificity of central neuroendocrine responses:implications for stress-related disorders. Endocr. Rev. 22, 502-548 (2001).

[0104] Rotenberg, S. & McGrath, J. J. Inter-relation between autonomic and HP A axis activity in children and adolescents. Biol. Psychol. 117, 16-25 (2016).

[0105] Kim, H.-G., Cheon, E.-J., Bai, D.-S., Lee, Y. II. & Koo, B.-H. Stress and heart rate variability: A meta-analysis and review of the literature. Psychiatry Investig. 15, 235- 245 (2018).Attorney Docket No. 10046-659W018551 WAN

[0106] Maes, J. et al. Sleep misperception, EEG characteristics and autonomic nervous system activity in primary insomnia: a retrospective study on polysomnographic data. Ini. J. Psychophysiol. 91, 163-171 (2014).

[0107] Monroe, L. J. Psychological and physiological differences between good and poor sleepers. J. Abnorm. Psychol. 72, 255-264 (1967).

[0108] Varkevisser, M., Van Dongen, II. P. A. & Kerkhof, G. A. Physiologic indexes in chronic insomnia during a constant routine: evidence for general hyperarousal? Sleep 28, 1588-1596 (2005).

[0109] Johann, A. F. et al. Cognitive behavioural therapy for insomnia does not appear to have a substantial impact on early markers of cardiovascular disease: A preliminary randomized controlled trial. J. Sleep Res. 29, el3102 (2020).

[0110] Harvey, A. G. & Tang, N. K. Y. (Mis)perception of sleep in insomnia: a puzzle and a resolution. Psychol. Bull. 138, 77-101 (2012).

[0111] Huang, Y. et al. Insomnia and impacts on facial expression recognition accuracy, intensity and speed: A meta-analysis. J. Psychiatr. Res. 160, 248-257 (2023).

[0112] Motomura, Y. et al. Sleep debt elicits negative emotional reaction through diminished amygdala-anterior cingulate functional connectivity. PLoS One 8, e56578 (2013).

[0113] Krause, A. J. et al. The sleep-deprived human brain. Nat. Rev. Neurosci. 18, 404-418 (2017).

[0114] Lazarus, M., Chen, J.-F., Urade, Y. & Huang, Z.-L. Role of the basal ganglia in the control of sleep and wakefulness. Curr. Opin. Neurobiol. 23, 780-785 (2013).

[0115] Taber, K. H. & Hurley, R. A. Functional neuroanatomy of sleep and sleep deprivation. J. Neuropsychiatry Clin. Neurosci. 18, 1-5 (2006).

[0116] Bishir, M. et al. Sleep deprivation and neurological disorders. Biomed Res. Int. 2020, 5764017 (2020).

[0117] Wu, J. C. et al. Frontal lobe metabolic decreases with sleep deprivation not totally reversed by recovery sleep. Neuropsychopharmacology 31, 2783-2792 (2006).

[0118] Lazarus, M., Huang, Z.-L., Lu, J., Grade, Y. & Chen, J.-F. How do the basal ganglia regulate sleep-wake behavior? Trends Neurosci. 35, 723-732 (2012).

[0119] Cole, E. J. et al. Stanford neuromodulation therapy (SNT): A double-blind randomized controlled trial. Am. J. Psychiatry 179, 132-141 (2022).

[0120] Nakajima, K. et al. A causal role of anterior prefrontal-putamen circuit for response inhibition revealed by transcranial ultrasound stimulation in humans. Cell Rep. 40, 111197 (2022).Attorney Docket No. 10046-659W018551 WAN

[0121] Mehta, D. D. et al. A systematic review and meta-analysis of neuromodulation therapies for substance use disorders. Neuropsychopharmacology 49, 649-680 (2024).

[0122] Fan, J. M. et al. Thalamic transcranial ultrasound stimulation in treatment resistant depression. Brain Stimul. 17, 1001-1004 (2024).

[0123] Matt, E. et al. Ultrasound neuromodulation with transcranial pulse stimulation in Alzheimer disease: A randomized clinical trial. JAMA Netw. Open 8, e2459170 (2025).

[0124] Matt, E., Radjenovic, S., Mitterwallner, M. & Beisteiner, R. Current state of clinical ultrasound neuromodulation. Front. Neurosci. 18, 1420255 (2024).

[0125] Visvanathan, V. & Morrissey, M. S. C. Anatomical variations of the temporal bone on high-resolution computed tomography imaging: how common are they? J. Laryngol. Otol. 129, 634-637 (2015).

[0126] Martin, E. et al. Ultrasound system for precise neuromodulation of human deep brain circuits. Nat. Commun. 16, 8024 (2025).

[0127] Beisteiner, R., Hallett, M. & Lozano, A. M. Ultrasound neuromodulation as a new brain therapy. Adv. Sci. (Weinh.) 10, e2205634 (2023).

[0128] Samoudi, M. A., Van Renterghem, T. & Botteldooren, D. Computational modeling of a single-element transcranial focused ultrasound transducer for subthalamic nucleus stimulation. J Neural Eng 16, 026015 (2019).

[0129] Fjield, T., Fan, X. & Hynynen, K. A parametric study of the concentric-ring transducer design for MRI guided ultrasound surgery. J Acoust Soc Am 100, 1220- 1230 (1996).

[0130] Creton, C. & Ciccotti, M. Fracture and adhesion of soft materials: a review. Rep Prog Phys 79, 046601 (2016).

[0131] Kendall, K. Thin-film peeling-the elastic term. J. Phys. D Appl. Phys. 8, 1449-1452 (1975).

[0132] Pennes, H. H. Analysis of tissue and arterial blood temperatures in the resting human forearm. 1948. J Appl Physiol (1985) 85, 5-34 (1998).

[0133] Sudhyadhom, A., Haq, I. U„ Foote, K. D„ Okun, M. S. & Bova, F. J. A high resolution and high contrast MRI for differentiation of subcortical structures for DBS targeting: the Fast Gray Matter Acquisition T1 Inversion Recovery (FGATIR).Neuroimage 47 Suppl 2, T44-52 (2009).Attorney Docket No. 10046-659W018551 WAN

[0134] MacLean, A. W., Fekken, G. C., Saskin, P. & Knowles, J. B. Psychometric evaluation of the Stanford Sleepiness Scale. J Sleep Res 1, 35—39 (1992).

[0135] Subjective and Objective Assessment of Hypersomnolence. Sleep Medicine Clinics 12, 313-322. (2017).

[0136] Johns, M. W. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 14, 540-545 (1991).

[0137] Julian, L. J. Measures of anxiety: State-Trait Anxiety Inventory (STAI), Beck Anxiety Inventory (BAI), and Hospital Anxiety and Depression Scale-Anxiety (HADS-A). Arthritis Care Res (Hoboken) 63 Suppl 11, S467-72 (2011).

[0138] Oostenveld, R. & Praamstra, P. The five percent electrode system for high-resolution EEG and ERP measurements. Clin Neurophysiol 112, 713-719 (2001).

[0139] Kawada, T. & Suzuki, S. Sleep induction effects of steady 60 dB (A) pink noise. Ind Health 31, 35-38 (1993).

[0140] Messineo, L. et al. Broadband Sound Administration Improves Sleep Onset Latency in Healthy Subjects in a Model of Transient Insomnia. Front. Neurol. 8, 288775 (2017).

[0141] Capezuti, E. et al. Systematic review: auditory stimulation and sleep. Journal of Clinical Sleep Medicine (2022) doi:10.5664 / jcsm.9860.

[0142] The influence of white noise on sleep in subjects exposed to ICU noise. Sleep Medicine 6, 423-428 (2005).

[0143] Afshar, P. F., Bahramnezhad, F., Asgari, P. & Shiri, M. Effect of White Noise on Sleep in Patients Admitted to a Coronary Care. Journal of Caring Sciences 5, 103-109 (2016).

[0144] State transitions between wake and sleep, and within the ultradian cycle, with focus on the link to neuronal activity. Sleep Medicine Reviews 8, 473-485 (2004).

[0145] intrashort sleep-waking schedule. I. Evidence of ultradian rhythmicity in ‘sleepability.’ Electroencephalography and Clinical Neurophysiology 52, 163-174 (1981).

[0146] RMSSD, a measure of vagus-mediated heart rate variability, is associated with risk factors for SUDEP: The SUDEP-7 Inventory. Epilepsy & Behavior 19, 78-81 (2010).

[0147] Shaffer, F. & Ginsberg, J. P. An Overview of Heart Rate Variability Metrics and Norms. Front. Public Health 5, 290215 (2017).

[0148] Cortical functional connectivity indexes arousal state during sleep and anesthesia.NeuroImage 211, 116627 (2020).Attorney Docket No. 10046-659W018551 WAN

[0149] McHugh, M. L. The Chi-square test of independence. Biochem Med 23, 143-149 (2013).

[0150] Iglesias, T. L., Boat, J. G., Frank, M. G., Zeil, J. & Hanlon, R. T. Cyclic nature of the REM sleep-like state in the cuttlefish Sepia officinalis. J Exp Biol 222, jeb 174862 (2019).

[0151] Pauli, W. M., Nili, A. N. & Tyszka, J. M. A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei. Scientific Data 5, 1-13 (2018).

[0152] Grady, C. L. & Garrett, D. D. Understanding variability in the BOLD signal and why it matters for aging. Brain Imaging Behav 8, 274-283 (2014).

[0153] An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF. Journal of Neuroscience Methods 172, 137— 141 (2008).

[0154] Biswal, B., Yetkin, F. Z., Haughton, V. M. & Hyde, J. S. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34, 537-541 (1995).

[0155] Lowe, M. J., Mock, B. J. & Sorenson, J. A. Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 7, 119- 132 (1998).

[0156] Zang, Y.-F. et al. Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev 29, 83-91 (2007).

[0157] Smith, S. M. Fast robust automated brain extraction. Hum Brain Mapp 17, 143-155 (2002).

[0158] Alsop, D. C. et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magnetic Resonance in Medicine 73, 102-116 (2015).

[0159] Fonzo, G. A. et al. Cognitive-behavioral therapy for generalized anxiety disorder is associated with attenuation oflimbic activation to threat-related facial emotions. J Affect Disord 169, 76-85 (2014).

[0160] Fonzo, G. A. et al. Common and disorder- specific neural responses to emotional faces in generalised anxiety, social anxiety and panic disorders. Br J Psychiatry 206, 206- 215 (2015).

[0161] Tottenham, N. et al. The NimStim set of facial expressions: judgments from untrained research participants. Psychiatry Res 168, 242-249 (2009).Attorney Docket No. 10046-659W018551 WAN

[0162] Peirce, J. et al. PsychoPy2: Experiments in behavior made easy. Behav Res Methods 1, 195-203 (2019).

[0163] Spisak, T. et al. Probabilistic TFCE: A generalized combination of cluster size and voxel intensity to increase statistical power. Neuroimage 185, 12-26 (2019).

Claims

Attorney Docket No. 10046-659W018551 WAN What is claimed:

1. A Non-invasive EEG / Ultrasound Stimulation Electronic Patch (NEUSleeP) device configured to be worn in proximity to a subject’s head or for facial feature conformation, the device configured to:obtain, via one or more hydrogels, electroencephalogram (EEG) data from the subject; andprovide, via a wearable ultrasound transducer and a long-term stable bioadhesive acoustic couplant, non-invasive ultrasound stimulation to the subject’s subthalamic nucleus (STN) to enhance rapid eye movement (REM) sleep, wherein the wearable ultrasound transducer is adjustable for focal depth targeting of the STN.

2. The device of claim 1, further comprising at least one of:an integrated Concentric Ring Array Transducer (CRUTA) for adjustable focal depth in targeting STN for non-invasive neuromodulation of STN in REM sleep enhancement, and one or more two-dimensional (2D) array transducers configured for beamsteering and beamfocusing to target the subject’s STN.

3. The device of claim 1 or 2, wherein the device is operatively coupled to a controller configured to:determine a plurality of STN stimulation parameters and / or a stimulation protocol; andprovide the non-invasive ultrasound stimulation according to the determined stimulation parameters.

4. The device of any one of claims 1-3, wherein the device is operatively coupled to an external ultrasound generator or a wireless ultrasound device.

5. The device of any one of claims 1-4, wherein the one or more hydrogels are fixably attached to a bioadhesive elastomer substrate.

6. A wearable device comprising:a bioadhesive elastomer substrate;one or more acoustic hydrogel couplants fixably attached to the bioadhesive elastomer substrate; andAttorney Docket No. 10046-659W018551 WAN an ultrasound transducer or device operatively coupled to an ultrasound generator, wherein the wearable device is configured to adhere to a subject’s skin and provide non- invasive ultrasound stimulation to the subject.

7. The wearable device of claim 6, wherein the wearable device is in electronic communication with a controller configured to:determine a target area of the subject’s brain;determine a plurality of stimulation parameters and / or a stimulation protocol corresponding with the target area; andcause the wearable device to deliver the non-invasive ultrasound stimulation to the target area in accordance with the determined plurality of stimulation parameters and / or the stimulation protocol.

8. The wearable device of claim 7, wherein the controller is further configured to:control or direct ultrasound stimulation from the ultrasound transducer or device, and control the ultrasound stimulation based, at least in part, on analysis of EEG data obtained via the one or more acoustic hydrogel couplants.

9. The wearable device of claim 7 or 8, wherein the plurality of stimulation parameters includes at least one of Center frequency (fo), Pulse Duration (PD), Pulse Repetition Frequency (PRF), Pulse Duty, Burst Duty, Cycles per pulse, Cycles per burst, Peak Pressure (P), Spatial peak pulse average intensity (Isppa), Spatial peak temporal average intensity (Ispta), Mechanical Index (MI), acoustic intensity, and focal depth.

10. The wearable device of any one of claims 6-8, further comprising one or more two- dimensional (2D) array transducers, wherein the one or more two-dimensional array transducers are used for beamsteering and beamfocusing to target the target area of the subject’s brain.

11. The device of any one of claims 1-5 or wearable device of any one of claims 7-10, wherein each hydrogel of the one or more acoustic couplants is formed from:a) a first monomer comprising one or more ion-forming moieties;b) a polyol; andc) water.Attorney Docket No. 10046-659W018551 WAN wherein the first monomer and water have a ratio by weight from about 1: 1 to about 1:4; andwherein the polyol is present in an amount from about 10% to about 40% by weight based on the weight of the hydrogel.

12. The device or wearable device of claim 11, wherein:the first monomer comprises 2-acrylamido-2-methylpropane sulfonic acid or a salt thereof; andthe polyol comprises glycerol.

13. The device or wearable device of claim 11 or claim 12, wherein the hydrogel is formed a), b), and c), and further from:d) a crosslinker (such as N, N-methylenebis(acrylamide), N, N-dimethylacrylamide (DM A A), poly (ethylene glycol) diacrylate (PEGDA), or a combination thereof); and / ore) an initiator (such as ammonium persulfate in combination with a catalyst, for example tetramethylethylenediamine (TMEDA)).

14. The device of claim 5 or the wearable device of any one of claims 6-13, wherein the bioadhesive elastomer substrate is formed from:a) a polysiloxane (such as polydimethylsiloxane);b) a polyamine (such as polyethyleneimine); andc) optionally one or more additives.

15. The device or wearable device of any one of claims 1-14, wherein the device is used for treatment of at least one of:Parkinson’s disease, epilepsy, Alzheimer’s disease, stroke, traumatic brain injury, psychiatric disorders, pain, peripheral chronic joint pain, overactive bladder syndrome, sleep disorders, carpal tunnel syndrome, visual prosthetics and / or blindness, or mood disorders, or any combination thereof.

16. A bioadhesive elastomer formed from:a) a poly siloxane;b) a polyamine; andAttorney Docket No. 10046-659W018551 WAN c) optionally one or more additional additives.

17. The bioadhesive elastomer of claim 16, wherein the polysiloxane is selected from polydimethylsiloxane (PDMS), polymethylhydrosiloxane (PMHS), polymethylphenyl siloxane (PMPS), polydiphenylsiloxane, polydiethylsiloxane, an amino-functionalized polysiloxane, an epoxy-functionalized polysiloxane, an acrylate- or methacrylate-functionalized polysiloxane, or combinations thereof, more particularly wherein the polysiloxane is polydimethylsiloxane (PDMS).

18. The bioadhesive elastomer of claim 16 or claim 17, wherein the polyamine is selected from polyethylenimine (PEI), polypropyleneimine (PPI), poly (amidoamine) (PAM AM), or combinations thereof, more particularly wherein the polyamine is polyethyleneimine (PEI).

19. An article comprising a bioadhesive elastomer of any one of claims 16-18.

20. The article of claim 19, wherein the article is a device, such as a medical device.

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