Wearable head-mounted light therapy device

Abstract

Systems and methods for the treatment of neurological conditions are described in which transcranial illumination using infrared, near-infrared, and / or red wavelengths of light is delivered into a patient's brain using a portable head-wearable device. An array of light-emitting elements is simultaneously controlled to provide a selected power density and distribution during a therapy session to treat the patient's condition. An external controller, such as a touchscreen tablet or laptop computer, can be used to select lighting parameters for each patient. The system can be used to provide therapy to children, such as those with autism spectrum disorder (ASD).

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims priority to U.S. Provisional Patent Application No. 63 / 033,756, filed June 2, 2020, U.S. Provisional Patent Application No. 62 / 940,788, filed November 26, 2019, and U.S. Provisional Patent Application No. 62 / 915,221, filed October 15, 2019, the entire contents of each of which are incorporated herein by reference. This application also claims priority to U.S. Design Application No. 29 / 728,109, filed March 16, 2020, the entire contents of which are incorporated herein by reference.

[0002] The presently disclosed subject matter generally relates to methods and devices for transcranial illumination for the therapeutic treatment of neurological conditions. Preferred embodiments may include wearable devices that communicate with mobile devices, such as web-enabled phones and tablets, to facilitate system operation and patient data analysis. This may optionally include cross-modal brain stimulation, diagnostic modalities, and more specifically may provide methods and devices that may optionally utilize simultaneous auditory and optical stimulation for treating children suffering from autism. [Background technology]

[0003] Research has shown that there is a powerful combined effect of two separate types of therapy in treating many neurological and psychiatric conditions. For example, in treating depression and anxiety, the combination of both medication and cognitive behavioral therapy (or dialectical behavior therapy) is more effective than either one of these modalities alone.

[0004] Furthermore, music therapy and video games have been used to treat patients with epilepsy. Some results indicate that listening to specific music content in combination with drug therapy reduces both epileptic discharge frequency and seizure frequency. Similarly, combining video games with drug therapy has also been shown to modulate brain neuroplasticity, improve age-related neurological abnormalities, and enhance cognitive function in elderly individuals. Thus, combining two different types of therapy has been shown to improve overall treatment outcomes for neurological and psychiatric conditions across a variety of target areas. Overall, the combined effects of brain stimulation through various channels are likely to be more potent than monomodal stimulation when treating psychiatric or neurological disorders.

[0005] For children diagnosed with autism spectrum disorder (ASD), one of the most common challenges they face is learning language. Research shows that children with ASD struggle with acquiring syntax. As a result, they are unable to parse sentences, understand speech, and / or acquire or produce new words. In particular, learning language (being able to speak complete sentences) by age 5 is critical for future successful integration into the neurotypical community and independent functioning. Furthermore, language learning may only occur during a delicate period (REFS), which ends between the ages of 5 and 7. If a child does not learn language adequately during this period, subsequent learning becomes very challenging, and achieving fluency is unlikely. Furthermore, being able to understand and produce language reduces tantrums and improves behavior in individuals with ASD. Therefore, delays in speech development are one of the most critical symptoms that need to be alleviated.

[0006] Another critical symptom that needs to be alleviated in children with ASD is anxiety. Generalized anxiety is often quite debilitating in children with ASD, particularly affecting their ability to learn and integrate socially. Children with ASD are often prescribed medications to reduce their anxiety, but these medications often have unintended side effects and may be ineffective.

[0007] In the United States, there are currently over 1.5 million children diagnosed with ASD, with approximately 80,000 new children diagnosed annually. Worldwide, approximately 1.5 to 2 million new children are diagnosed with ASD annually. Autism services cost the American public approximately $250 billion annually, including both medical costs (outpatient care, residential treatment, and medications) and non-medical costs (special education services, residential services, etc.). In addition to the obvious costs, there are hidden costs, such as emotional stress and the time required to develop and coordinate treatment. Research indicates that with appropriate early intervention, lifetime treatment costs can be reduced by approximately two-thirds.

[0008] Further research indicates that ASD is often correlated with mitochondrial dysfunction. Mitochondria in the brain cells of individuals with autism do not produce enough adenosine triphosphate ("ATP"). The consequences of mitochondrial dysfunction can be particularly pronounced in the brain, as it uses 20% of all energy produced by the human body, which can lead to neurodevelopmental disorders such as ASD. Encouraging research has shown that infrared and red light may activate mitochondria in children, thereby increasing ATP production.

[0009] Transcranial photobiomodulation of the brain (tPBM) using near-infrared and red light has been shown to be beneficial for treating various psychiatric and neurological conditions, such as anxiety, stroke, and traumatic brain injury. Notably, autism spectrum disorders could potentially be treated with tPBM as a therapy, as some scientists have recently linked the disorder to mitochondrial imbalances. tPBM could potentially affect this by causing mitochondria to produce more ATP. Patients treated with tPBM absorb near-infrared light, which could potentially reduce inflammation, increase oxygen flow to the brain, and increase ATP production. However, devices and methods that enable additional treatment options for various neurological conditions are needed.

[0010] One problem with language acquisition is that many children with ASD are unable to concentrate on language sufficiently to extract syntactic features of words, parse sentences, and / or attend to syntactic and semantic cues in speech, and therefore their word learning may be delayed.

[0011] The problem with anxiety is that children with ASD are often very stressed and do not know how to calm themselves before certain learning or social situations. As a result, they are unable to participate in normal activities (like playdates or classes).

[0012] Therefore, there is a need for improved methods and devices for providing therapy for the treatment of children to specifically provide treatment for neurological disorders. Summary of the Invention

[0013] Preferred embodiments provide devices and methods configured to be worn by a subject, in which a head-wearable device is activated to provide illumination wavelengths of light with sufficient energy to be absorbed by regions of brain tissue during therapy sessions. Transcranial delivery of illumination light may be performed using multiple light-emitting devices attached to the head-wearable device, which may also preferably include control and processing circuitry. Thus, providing brain stimulation with one or more, or a combination of, (i) infrared, near-infrared, and red light to improve brain performance, e.g., by ATP generation in the brain, and (ii) providing additional specific linguistic input for learning syntax, improves language acquisition in children with ASD. Thus, providing brain stimulation with a combination of (i) near-infrared and red light to reduce anxiety and (ii) specialized meditations written for children with ASD reduces anxiety. Reduced anxiety leads to both improved language learning and better social integration. Providing audio language programs specifically designed for children with ASD may focus a child's attention on language, provide them with information about language markers, and improve their ability to communicate. This will likely reduce lifetime treatment costs for affected individuals.

[0014] A preferred embodiment may use multiple laser diodes or light-emitting diodes (LEDs) configured to emit sufficient power through the patient's skull to provide a therapeutic dose during the therapy session. The multiple light-emitting devices may be mounted on a circuit board positioned on a head-wearable device. For the treatment of children, the spacing between the light-emitting elements in each array mounted on the head-wearable device may be selected to improve penetration depth through the skull. As a child's skull increases in thickness with age, the parameters of the light used to penetrate the skull change as a function of age. As the attenuation of illuminating light increases with age, the light frequency, power density, and spot size of each light-emitting element may be selectively adjusted as a function of age. The system may automatically set lighting conditions as a function of the patient's age. The thickness of an individual patient's skull may also be quantitatively measured by X-ray scanning and input into the system to set the desired lighting parameters necessary to deliver the required power density to selected regions of the brain. Skull density may also change as a function of age and may be quantitatively measured by X-ray bone densitometry to generate additional data that can be used to control and adjust the level of radiance applied to different regions of the skull.

[0015] Aspects of the disclosed technology may include methods and devices for cross-modal brain stimulation, which may be used to treat children with ASD. Consistent with disclosed embodiments, systems and methods of their use may include a wearable device (e.g., a bandana) including one or more processors, transceivers, microphones, headphones, LED lights (diodes), or a power source (e.g., a battery). One exemplary method may include placing the wearable device on the head of a patient (a child with ASD). The method may further include transmitting a predetermined amount of light (e.g., red or near-infrared) through the wearable device (e.g., LED light). The method may also include simultaneously outputting linguistic input to the patient, for example, through headphones on the wearable device or other device that can be heard or seen by the patient. The linguistic input may include, for example, an explicit syntactic structure that facilitates learning how to parse sentences. The method may also include outputting a specific meditation written for children with ASD that may help reduce anxiety, allowing the child with ASD to learn language better and integrate socially more easily. In some examples, the method may further include receiving a response to the verbal input from the patient, which the one or more processors may analyze to determine the accuracy of the response and / or generate any follow-up verbal input. Furthermore, in some examples, the frequency and / or type of light output by the wearable device may be adjusted based on the response received from the patient. Also, in some examples, the wearable device may be paired to a user device (e.g., Bluetooth®) that determines and transmits the verbal input to the wearable device or other device including one or more transducer devices, such as a speaker, or a display device that may generate auditory or visual signals / images that can be heard and / or seen by the patient.

[0016] The head-wearable device may comprise a rigid, semi-rigid, or flexible substrate to which the light-emitting elements and circuit elements are attached. Flexible substrates may include woven fabric or polymer threads, molded plastic, or machine-printed components assembled into a band that extends around the patient's head. The circuit boards to which the electrical and optical components are attached and interconnected may be of standard rigid form, or they may be flexible to accommodate bending around the curvature of the patient's head. Because children and adults have heads in different size ranges, it is advantageous to have materials that can adjust to different sizes. More rigid head-wearable devices may use foam materials to provide a comfortable material that interfaces with the patient's head. The head-wearable device may be used in conjunction with diagnostic devices and systems that can be used to select parameters for therapeutic light use as described herein. A computing device, such as a tablet or laptop computer, may be used to control the diagnostic and therapeutic operations of the head-worn device and other devices used in conjunction with a therapy session. Such computing devices may store and manage patient data and generate electronic health or medical records for storage and further use. The computing device may be programmed with software modules such as a patient data entry module, a system operation module, which may include diagnostic and therapy sub-modules, and an electronic medical record module. The system may include a network server to enable communication with remote devices, web / internet operation, and remote monitoring and control over a secure communication link. The computing device may include connections to electroencephalogram (EEG) electrodes to monitor brain activity before, during, or after a therapy session to generate diagnostic data for the patient.The EEG electrodes may be integrated into a head-wearable device, where they may be directly connected to a processor, or alternatively, may communicate via either a wired or wireless connection to an external computing device, such as a touchscreen-operated tablet display device. Optical sensors optically coupled to the patient's head may be used to monitor light transmission into the patient's skull and / or measure light returning from the area of ​​the brain receiving the illuminating light. An array of near-infrared sensors may be mounted, for example, on an LED panel or circuit board that can detect reflected light returning from the tissue or other optical signals that can be used to diagnose the condition of the tissue. Diagnostic data generated by the system sensors may be used to monitor the patient during therapy sessions and, optionally, to control operating parameters of the system during therapy sessions, such as by increasing or decreasing the intensity of light delivered through the skull, or by adjusting the duration or area of ​​the brain illuminated during a therapy session.

[0017] Further features of the disclosed design and advantages offered thereby will be described in more detail below with reference to specific embodiments illustrated in the accompanying drawings, in which like elements are designated with like reference designators. [Brief explanation of the drawings]

[0018] Reference is now made to the accompanying drawings, which are not necessarily drawn to scale, and which are incorporated in and constitute a part of this disclosure, illustrating various implementations and aspects of the disclosed technology and, together with the description, serving to explain the principles of the disclosed technology.

[0019] [Figure 1] 1 is an exemplary head-wearable device according to some examples of the present disclosure.

[0020] [Figure 2A] 2 shows a rear view of a patient with the head-wearable device of FIG. 1. [Figure 2B]2 shows a side view of a patient with the head-wearable device of FIG. 1. [Figure 2C] 2 shows a front view of a patient with the head-wearable device of FIG. 1.

[0021] [Figure 3] Illustrates the use of a mobile phone or tablet device connected to a head-wearable device.

[0022] [Figure 4] 1 shows a schematic representation of the operating elements of the head-wearable device and control features.

[0023] [Figure 5] 1 illustrates schematically the components of a head-wearable device according to a preferred embodiment.

[0024] [Figure 6] 10 shows screenshots of a diagnostic procedure used in conjunction with a preferred embodiment of the present invention.

[0025] [Figure 7] 1 shows a light emitting element for transcranial illumination attached to one side of a circuit board attached to a head-wearable device.

[0026] [Figure 8] 8 illustrates a second side of the circuit board shown in FIG. 7, including a connector to a controller and power source for a head-wearable device.

[0027] [Figure 9] FIG. 10 shows a detailed view illustrating circuit board elements of a head-wearable device of a particular embodiment.

[0028] [Figure 10] 1 shows the circuitry mounted on the circuit board of the head-wearable device for the preferred embodiment.

[0029] [Figure 11] 1 shows the circuitry mounted on the circuit board for control of a preferred embodiment of a head-wearable device.

[0030] [Figure 12] 1 shows circuitry mounted on a circuit board for controlling the operation of a head-wearable device.

[0031] [Figure 13] FIG. 1 is a process flow diagram of a preferred method of operating the head-wearable device and control system.

[0032] [Figure 14] FIG. 1 is a process flow diagram illustrating the use of EEG measurements in conjunction with transcranial illumination of a patient.

[0033] [Figure 15] 1 shows a table with exemplary parameters having a variable range between upper and lower thresholds used for transcranial illumination of a patient, according to a preferred embodiment.

[0034] [Figure 16] FIG. 1 shows a process flow diagram for selecting and optimizing parameters across multiple therapy sessions, including manual and automated selection procedures.

[0035] [Figure 17] FIG. 1 illustrates a process flow diagram for administering a therapy session to a patient, according to various embodiments described herein.

[0036] [Figure 18] FIG. 10 shows a further view of a head-worn device having user-accessible circuit housing elements communicatively connected to a first tablet device for use by a patient during a therapy session and a second tablet for use by an operator to monitor, control, and / or program the system for diagnostic and therapy applications as generally described herein. DETAILED DESCRIPTION OF THE INVENTION

[0037] Some implementations of the disclosed technology are more fully described with reference to the accompanying drawings. However, the disclosed technology may be embodied in many different forms and should not be construed as limited to the implementations described herein. The components described below as forming various elements of the disclosed technology are intended to be illustrative and not limiting. Many suitable components that would perform the same or similar functions as the components described herein are intended to be embraced within the scope of the disclosed electronic devices and methods. Such other components not described herein may include, but are not limited to, components developed after the development of the disclosed technology, for example.

[0038] It should also be understood that the reference to one or more method steps does not imply that the method steps must be performed in a particular order or exclude the presence of additional method steps or method steps between the explicitly identified steps.

[0039] Reference will now be made in detail to exemplary embodiments of the disclosed technology, examples of which are illustrated in the accompanying drawings and disclosed herein. Where convenient, the same reference numerals will be used throughout the drawings to refer to the same or like parts.

[0040] FIG. 1 illustrates an exemplary wearable device 50 that may implement a particular method for cross-modal brain stimulation. As shown in FIG. 1, in some implementations, the wearable device 50 may include, among other things, one or more processors, transceivers, microphones, headphones 52, LED lights 54, and / or a battery. The wearable device 50 may be paired with a user device (e.g., a smartphone, a smartwatch) that may provide instructions that may determine the frequency of transmitted light, the type of light (e.g., red light or infrared), meditation, and / or language input. FIGS. 2A-2C illustrate back and front views of the head-wearable device 50 positioned on a patient's head, having a rear circuit board 56, side lighting panels 56, and a front lighting panel 62 for providing transcranial illumination, as well as earphones 52 for providing audio programming to the patient. The system may store audio or video files that the user can hear or view in conjunction with therapy sessions for the patient.

[0041] FIG. 3 is a diagram of a system 100 for brain stimulation, according to various embodiments described herein. System 100 includes a photobiomodulation device 110 in communication with a remote computing device 150. In an exemplary embodiment, computing device 150 includes a visual display device 152 that can display a graphical user interface (GUI) 160. GUI 160 includes an information display area 162 and user-actuable controls 164. Optionally, computing device 150 also communicates with an external EEG system 120′. Optionally, computing device 150 also communicates with an external optical sensor array 122′. An operating user may operate computing device 150 to control the operation of photobiomodulation device 110, including activation of functions of photobiomodulation device 110 and unidirectional or bidirectional data transfer between computing device 150 and photobiomodulation device 110.

[0042] An operating user can change between operating modes of computing device 150 by interacting with user-actuable controls 164 of GUI 160. Examples of user-actuable controls include controls for accessing program control tools, stored data and / or stored data manipulation and visualization tools, audio program tools, evaluation tools, and any other suitable control modes or tools known to those skilled in the art. Activation of a program control mode causes GUI 160 to display program control information in information display area 162. Similarly, activation of other modes using user-actuable controls 164 may cause GUI 160 to display relevant mode information in information display area 162. The system can be programmed to implement therapy sessions of variable length, for example, between 5 and 30 minutes. The patient's use of language during a session can be recorded by a microphone on the head-wearable device and used separately or stored for later analysis of the language used during the session.

[0043] In program control mode, GUI 160 may display program controls including one or more presets 165. Activation of a preset by an operating user configures photobiomodulation device 110 to use particular pre-set variables appropriate for light therapy for a particular class of patient or for a particular patient. For example, a particular pre-set 165 may correspond to a class of patients of a particular age or condition. In various embodiments, the pre-set variables configured via a pre-set 165 may include an illumination pattern (e.g., a spatial pattern, a temporal pattern, or both spatial and temporal patterns), an illumination wavelength / frequency, or an illumination power level.

[0044] In some embodiments, photobiomodulation device 110 may transmit and / or receive data from computing device 150. For example, photobiomodulation device 110 may transmit data to log information about a therapy session for a patient. Such data may include, for example, lighting patterns, total time, time spent in different phases of the therapy program, electroencephalogram (EEG) readings, and power levels used. Data may be transmitted and logged before, during, and after a therapy session. Similar data may also be received at computing device 150 from an external EEG system 120′ or external optical sensor array 122′ in embodiments utilizing these components. In stored data manipulation and / or stored data visualization modes, an operating user may review data logged from a source and received at computing device 150. In some embodiments, the data may include information regarding the activity used in conjunction with the therapy session (i.e., information related to the tasks presented to the patient during the therapy session, such as task identity and scoring). For example, activity data may be entered by a user operating on an assessment mode screen, as described in more detail below.

[0045] In audio system mode, the user can control audio information delivered to the patient through speaker 116 of photobiomodulation device 110. The audio information, in some embodiments, can include instructions for the patient. In other embodiments, the audio information can include audio programming for different therapy applications.

[0046] In the assessment mode, a user may enter or review data related to patient assessment, such as task identity and scoring. For example, Figure 6 shows a particular assessment test displayed in the information display area 162 of the GUI 160. This assessment test, the Weekly Child Test, includes a rating scale representing scores for various individual measures intended to provide an overall assessment of the severity of autism in a child.

[0047] As described in more detail below, computing device 150 and photobiomodulation device 110 may communicate through a variety of methods. In some embodiments, a direct (i.e., wired) connection 117 may be established between computing device 150 and photobiomodulation device 110. In some embodiments, computing device 150 and photobiomodulation device 110 may communicate directly with each other through a wireless connection 118. In still further embodiments, computing device 150 and photobiomodulation device 110 may communicate through a communications network 505.

[0048] In various embodiments, one or more portions of the communications network 505 may be an ad hoc network, a mesh network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless wide area network (WWAN), a metropolitan area network (MAN), a portion of the Internet, a portion of the public switched telephone network (PSTN), a mobile telephone network, a wireless network, a Wi-Fi® network, a WiMAX® network, an Internet of Things (IoT) network established using Bluetooth® or any other protocol, any other type of network, or a combination of two or more such networks.

[0049] In an exemplary embodiment, system 100 is configured to treat patients with autism, particularly younger patients with autism. Thus, creating a wireless connection between photobiomodulation device 110 and computing device 150 is desirable in many embodiments, as younger patients are less likely to sit quietly for the length of a therapy session. The wireless connection, and the use of a battery to power photobiomodulation device 110, allows for uninterrupted transcranial illumination for the entire length of a single therapy session and further allows the younger patient to move and participate in activities that may or may not be associated with therapy.

[0050] FIG. 4 shows a block diagram of a remote computing device 150 and a photobiomodulation device 110 suitable for use with exemplary embodiments of the present disclosure. The remote computing device 150 may be, but is not limited to, a smartphone, laptop, tablet, desktop computer, server, or network appliance. The remote computing device 150 includes one or more non-transitory computer-readable media for storing one or more computer-executable instructions or software for implementing exemplary embodiments. The non-transitory computer-readable media may include, but is not limited to, one or more types of hardware memory, non-transitory tangible media (e.g., one or more magnetic storage disks, one or more optical disks, one or more flash drives, one or more solid-state disks), and the like. For example, memory 156 included in the remote computing device 150 may store computer-readable and computer-executable instructions or software for implementing exemplary operations of the remote computing device 150. The remote computing device 150 also includes a configurable and / or programmable processor 155 and associated cores 404, and optionally one or more additional configurable and / or programmable processors 402' and associated cores 404' (e.g., in the case of a computer system with multiple processors / cores) for executing computer-readable and computer-executable instructions or software stored in memory 156 and other programs for implementing exemplary embodiments of the present disclosure. The processor 155 and the processor 402' may each be a single-core processor or a multi-core processor (404 and 404'). Either or both of the processor 155 and the processor 402' may be configured to interface with the remote computing device 150 and execute one or more of the instructions described.

[0051] Virtualization may be employed in remote computing device 150 so that infrastructure and resources in remote computing device 150 may be dynamically shared. Virtual machines 412 may be provided to handle processes running on multiple processors so that the processes appear to be using only one computing resource rather than multiple computing resources. Multiple virtual machines may also be used with one processor.

[0052] The memory 156 may include computer system memory or random access memory, such as DRAM, SRAM, EDO RAM, etc. The memory 156 may also include other types of memory or combinations thereof.

[0053] A user may interact with remote computing device 150 through a visual display device 152, such as a computer monitor, which may display one or more graphical user interfaces 160. In an exemplary embodiment, the visual display device includes a multipoint touch interface 420 (e.g., a touchscreen) that may receive tactile input from an operating user. The operating user may interact with remote computing device 150 using multipoint touch interface 420 or pointing device 418.

[0054] The remote computing device 150 may also interact with one or more computer storage devices or databases 401, such as a hard drive, CD-ROM, or other computer-readable medium, for storing data and computer-readable instructions and / or software implementing exemplary embodiments (e.g., applications) of the present disclosure. For example, the exemplary storage device 401 may include modules for implementing aspects of the GUI 160 or control presets, audio programs, activity data, or assessment data. The database 401 may be updated manually or automatically at any suitable time to add, delete, and / or update one or more data items in the database. The remote computing device 150 may send data to or receive data from the database 401, including, for example, patient data, program data, or computer-executable instructions.

[0055] Remote computing device 150 may include a communications interface 154 configured to interface with one or more networks via one or more network devices, such as, but not limited to, a local area network (LAN), a wide area network (WAN), or the Internet through various connections including, but not limited to, a standard telephone line, a LAN or WAN link (e.g., 802.11, T1, T3, 56kb, X.25), a broadband connection (e.g., ISDN, Frame Relay, ATM), a wireless connection (e.g., WiFi or Bluetooth), a controller area network (CAN), or some combination of any or all of the above. In an exemplary embodiment, remote computing device 150 may include one or more antennas that facilitate wireless communication (e.g., via a network interface) between remote computing device 150 and the network and / or between remote computing device 150 and photobiomodulation device 100. Communications interface 154 may include a built-in network adapter, a network interface card, a PCMCIA network card, a card bus network adapter, a wireless network adapter, a USB network adapter, a modem, or any other device suitable for interfacing remote computing device 150 to any type of network capable of communicating and performing the operations described herein.

[0056] Remote computing device 150 may operate an operating system 410, such as multiple versions of Microsoft® Windows® operating systems, different releases of UNIX® and Linux® operating systems, multiple versions of MacOS® for Macintosh® computers, an embedded operating system, a real-time operating system, an open source operating system, a proprietary operating system, or any other operating system capable of running on remote computing device 150 and performing the operations described herein. In an exemplary embodiment, operating system 410 may operate in native mode or in an emulated mode. In one exemplary embodiment, operating system 410 may run on one or more cloud machine instances.

[0057] Photobiomodulation device 110 may include processor board 111, one or more light-emitting panels 115a-115e, one or more speakers 116, and one or more batteries 118. Photobiomodulation device 110 may optionally include optical sensor array 122 and EEG sensor system 120. While five light-emitting panels 115a-115e are described with respect to this disclosure, those skilled in the art will understand that a greater or lesser number of panels may be used. In one exemplary embodiment, light-emitting panels 115a-115e are flexible. In one exemplary embodiment, light-emitting panels 115a-115e are located on the front, top, back, and sides of the user's head. In embodiments in which photobiomodulation device 110 does not have complete coverage on the user's head (i.e., a headband-style device), the top panel may be omitted.

[0058] 5 shows a schematic layout of a photobiomodulation device 110 of the present invention. Processor board 111 is, for example, a printed circuit board that includes components that control the function of photobiomodulation device 110. Processor board 111, in some embodiments, may include a central processing unit 112 and a power management module 114.

[0059] The power management module 114 may monitor and control the use of particular light-emitting panels 115a-115e during a therapy session. In some embodiments, the power management module 114 may take action to control or provide feedback to the patient-user regarding whether a light-emitting panel 115a-115e is not used or is only partially used during a particular therapy session. By reducing the use of a particular panel during a session, longer operation may be achieved. Furthermore, different classes of patients (e.g., patients of different ages) may have different skull thicknesses. As a result, different transmission power (and therefore penetration) may be required as a function of patient age. The power management module 114 may control the power output to the light-emitting panels to provide a therapeutically beneficial dose of illumination while further extending battery life. Shown in FIG. 7 is an LED 202 mounted on a first side of a printed circuit board 200, which may have a connector 208 for wiring to the main circuit panel 270 shown in FIG. 12. The LED 202 may have a fixed spot size 205 as it enters the patient's skull. Alternatively, the spot size can be reduced or increased by a selected amount to either reduce or increase the amount of brain tissue illuminated. The LED panel shown in FIG. 7 may include sensor components, such as EEG electrodes and / or photodetectors, configured to detect light from illuminated tissue within the skull. The circuit panel 270 may include a wireless transceiver for transmitting and receiving data from an external controller within the tablet, as described herein. The circuit panel 270 may also include a wired connector for connecting the system to an external power source and to a tablet used to control the system. As shown in FIG. 12, two manual switches 272, 274 may be used to activate different power levels of the system. In this particular example, the first switch selects between two different levels, and the second switch selects between four different settings or sub-levels for a total of eight different options. These switches may also be controlled remotely from the tablet, as described herein.An LED 276 is used to indicate to the user that power is on. An additional switch 282 may power on the wireless transceiver 280, which in this implementation is a Bluetooth transceiver. An LED 284 may further indicate the status of the transmitter. A central microprocessor 278 is programmed to control the operation of the circuit board 270. The power supply board 250 and controller board 260, shown in FIGS. 10 and 11, control power from one or more batteries to the controller board. An on / off power switch 262 for the head-worn device may be located on board 260, which includes an inductor 264, to prevent fluctuations in the voltage supplied to the LEDs as power is drawn from the battery. These components are mounted on the head-wearable device 110 with earphones 52, which are driven by the main controller board, so that the patient can hear the audio files used during therapy sessions. Alternatively, the electronics shown and described herein may be implemented using integrated circuit components to reduce size, weight, and power requirements. Electronic sensors may monitor the voltage applied to one or more LEDs to record the amount of optical power delivered to the patient. The electronics may be implemented as an application specific integrated circuit (ASIC) or system on a chip (SOC) design.

[0060] Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by reduced social functioning, inattention, and language impairment. Although autism is likely a multicause disorder, research indicates that individuals with ASD often have mitochondrial disease that leads to abnormalities in energy production from dietary protein. However, mitochondria in the brain may be able to generate energy molecules from different sources, such as light.

[0061] Using the wearable device 50, certain methods of the present disclosure may simultaneously perform photobiomodulation (stimulating the brain with light) and language training to treat children with ASD. The wearable device 50 may include several near-infrared and / or red lights to stimulate language areas of the brain. These methods associated with the wearable device 50 may include determining an area of ​​the head (e.g., the temporal lobe, prefrontal cortex, and / or occipital lobe) where the wearable device 50 will output infrared and / or red light. Light absorbed by brain tissue may increase ATP production, which may provide more energy to neurons to communicate with each other and increase brain connections. The wearable device 50 may simultaneously receive language input from a user device application transmitted to the user via headphones on the wearable device 50. Language input may be useful for facilitating language learning. Thus, for example, providing these combined mechanisms (photobiomodulation and language input) to children diagnosed with ASD may significantly improve lifelong outcomes. Additionally, the wearable device 50 may output meditations that may help reduce anxiety in patient users (such as children with ASD), potentially enabling the user to better learn language and integrate socially.

[0062] A method for providing cross-modal brain stimulation may include determining the light frequency, the location of the LED light (e.g., the area of ​​the brain in need of increased ATP, the area of ​​the brain most likely to respond to light therapy, and / or the area of ​​the brain associated with language (e.g., auditory cortex, Broca's area, Wernicke's area)), whether ATP production is increased, and the overall effect of the treatment. Thus, based on the determined overall effect on the brain, the wearable device may be dynamically adjusted specifically for the user.

[0063] The wearable device 50 may be specifically tailored for children with ASD to improve language skills, alleviate anxiety, and / or reduce tantrums. Furthermore, the wearable device 50 may be used daily in the convenience of a family's home, without the need for a specially trained therapist. Furthermore, the wearable device 50 may be non-intrusive, non-prescription, and / or free of side effects.

[0064] Methods for using the disclosed devices may further include determining the location of light-emitting diodes that may be used to stimulate specific brain regions responsible for language, comprehension, energy production, and / or self-regulation (e.g., reducing anxiety). The methods may also include determining total power, power density, pulse, and / or frequency. Total power may be 400 mW to 600 mW (0.4 W to 0.6 W), with 100 mW to 150 mW for each of the four panels. The power for each panel may be selectively reduced to a range of 50 mW to 100 mW or increased to a range of 150 mW to 200 mW, depending on the patient's age or condition. Each of these ranges may be further incremented in 10 mW intervals during or between treatment sessions. The spot size of the light produced by each LED or laser can optionally be controlled by adjusting the spacing between the light-emitting holes of the LEDs, or by using a movable lens for one or more LEDs on each circuit board that can be moved between adjustable positions, for example, by a MEMS actuator.

[0065] Furthermore, the wearable device 50 may be constructed of materials that are comfortable for the expected patient. For example, the wearable device may be constructed of plastic and / or fabric (e.g., cotton, polyether, rayon, etc.). Because ASD patients are particularly delicate, the aforementioned materials may be essential to allow the ASD patient to wear the device for a sufficient length of time without becoming overly sensitive. Of course, the wearable device 50 may need to be both safe and comfortable. Electronic components (e.g., processor, microphone, headphones, etc.) may be sewn to the wearable device 50 and may be difficult to reach, for example, by children. The cloth or fabric covering may include a head-mounted frame and optoelectronic components to the extent possible without interfering with the optical coupling of the LEDs to the skull. Furthermore, the weight of the wearable device 100 may be light enough to allow it to be worn comfortably. Furthermore, the wearable device 100 may require a power source (e.g., one or more replaceable batteries) to allow it to be portable.

[0066] With regard to language input, the patient-user device (e.g., a smartphone or tablet) may have applications that 1) perform language acquisition (e.g., develop and record numerous short vignettes specifically designed to clarify syntactic structures and teach how to parse sentences), 2) include a meditation system specifically designed to alleviate anxiety, and 3) include a music reward system to keep the user (child) interested and engaged.

[0067] Applications may disambiguate the syntactic structure of language. Current research suggests that a growth spurt in word learning occurs after children learn basic syntax (and occurs at the syntax-lexical interface). Furthermore, without syntax, children may not progress beyond speaking 10–15 words that may be used for simple labeling but not to express their needs, desires, and emotions. This means that without first learning syntax, they may not be capable of appropriate communication. Furthermore, syntax may be necessary for children to parse the sound waves or tones they hear into sentences and words. Syntax may also be necessary for certain word learning strategies (e.g., syntactic bootstrapping).

[0068] Syntactic bootstrapping is a mechanism children use to infer the meaning of a verb from syntactic cues. For example, when a child hears "Michael drinks soup," the child infers that "drink" is a transitive verb. A classic example used by renowned psycholinguistics professor Lila Gleitman is the invented verb "Derk." By placing this verb in several syntactic contexts, the meaning of the verb becomes clear: "Dark! Dark up! Dark here! Dark me! Dark what I did!" Dr. Gleitman argued that children infer the meaning of verbs from hearing them in different syntactic contexts. Furthermore, Dr. Pinker argued that children also use semantic bootstrapping (contextual cues) to infer the meaning of words. Thus, there are several mechanisms available (most likely innate) to typical children during language learning. Overall, there is scientific consensus that typical children learn language by focusing specifically on syntactic and semantic cues in speech.

[0069] However, research suggests that children on the autism spectrum cannot always extract syntactic structure and semantic context from the incomplete language input they receive. Normal language input is too messy, incomplete, and confusing for them. People often speak in sentence fragments, switch between topics, use incorrect words, or use words in incorrect forms. Human speech may be too messy to allow for facile learning based solely on this type of speech. Neurotypical children may still extract syntactic structure from this messy input by attending to specific syntactic cues (e.g., looking for nouns and verbs in strings of speech). When children grasp the syntactic structure of language, they acquire more words as they learn to parse sentences. Several studies, including those with children on the spectrum, support this hypothesis that a great deal of word learning occurs at this syntax-lexical interface.

[0070] Many children with ASD appear unable to progress beyond simple labeling and are unable to speak in complete sentences, preventing them from communicating effectively. There are many reasons for this difficulty, one of which is that these children typically do not pay enough attention to speech and communication, so they do not pay sufficient attention to syntactic cues and are unable to parse individual sentences. However, without grasping the syntactic structure of language, word learning beyond simple labeling becomes impossible, and specifically, verb acquisition may be impossible. Because research indicates that the best predictor of future integration into (and normal functioning in) neurotypical communities is speaking complete sentences by age 5, rapid acquisition of verbs (rather than just nouns to label objects around them) may be critical for children with ASD. Specifically, the problem is that children with ASD are unable to concentrate on language sufficiently to extract syntactic features of words, parse sentences, and / or pay attention to syntactic and semantic cues in speech. Thus, their word learning is delayed.

[0071] Thus, the aforementioned application corrects incomplete language input for a child with ASD, making syntactic structure as clear as possible. For example, a child hears the noun "dog," followed by "one dog, two dogs, three dogs, four dogs, five dogs." She then hears "my dog ​​is brown," "my brown dog is cute," "my brown dog is small," "I have a small, cute, brown dog," "my dog ​​barks," "dog barks," "dog chases cat," "dog eats meat," and "I have a dog," among others. By repeatedly placing the same word in different syntactic contexts, the child is inundated with information about linguistic markers (such as syntactic role in a sentence, addition, noun, and animate / inanimate).

[0072] Thus, this application can "awaken" (activate) language learning and encourage the child to pay attention to syntactic cues in language input. Furthermore, this application can be improved by observing the user's behavior and recording their improvements. A method for treatment 450 is described in conjunction with the process flow diagram of FIG. 13. Preset or manually entered parameters 452 can be entered by touch actuation on a tablet touchscreen, allowing the system controller to activate an illumination sequence. These parameters are stored 454 in memory. Software for the system then executes the stored instructions based on the selected parameters to provide transcranial illumination 456 during the therapy session. The system may utilize optional audio or video files 458 in conjunction with the therapy session. The system then communicates recorded data 460 for the therapy session for storage in the patient's electronic medical record. The data can be used for further analysis, such as by the application of machine learning programs to provide training data.

[0073] Below is a description of an example of a battery-powered system as described previously in this specification, with one or two 9-volt batteries inserted into the battery holder, in side and back views showing the LED case design as shown.

[0074] If the LED is not encased, a small tube can be used to ensure it remains centered and securely held in place. This tube can fit through a hole in the foam band for the appropriate location and has an outer diameter of 3 / 8 inch (9.53 centimeters). The PCB acts as a support for the foam and allows clearance for the connecting cables. The same type of construction can be applied to the electronics mounting area, battery, and speaker. Sensors used to measure patient characteristics during use, such as EEG electrodes, photodetectors, and / or temperature sensors, can be mounted on the circuit board that holds the LED or laser diode, generally as described herein. Detected electrical signals from the sensors can be routed to the controller board, stored in local memory, and transmitted to an external tablet device via wireless transmission so that a user or clinician can monitor therapy sessions and control changes to the system's operating parameters during use.

[0075] The electronics may include three or more separate PCB configurations with LED PCBs with (6) variations for associated locations on the head. There may be two LED printed circuit boards on each side (front and back), at least one to illuminate the temporal lobes on each side, and at least one board in the center to illuminate the frontal lobes. One or two boards may fit over one or both of the parietal and occipital lobes.

[0076] The system is fitted to the patient's head and emits energy into the patient's head via infrared LEDs at, for example, 40 Hz. The infrared LEDs are split into six boards, each containing one infrared LED. The LEDs utilized for the preferred embodiment may be SST-05-IR-B40-K850.

[0077] The LED board may illuminate during the on-time of the 40Hz signal. The duty cycle of the 40Hz signal is equal to the power setting. For example, a 25% power setting requires a 25% duty cycle for 40Hz.

[0078] One or more 9V batteries can be the source of power for the system. A buck converter reduces the 9V from the battery to 2.5V for the LEDs. One or more batteries of different voltages can be employed, especially if different batteries are used for the light-emitting elements and to power the circuitry.

[0079] Note that in this section, calculations of the absolute maximum luminous flux output of the LEDs assume they are the only components powered by a single 9V battery.

[0080] Table 1 shows the current limits of critical components. These current limits cannot be violated without risking permanent damage to the components. [Table 1]

[0081] The law of conservation of energy dictates that the current drawn by a buck converter is not the same as the current drawn by the battery. Equation 1 states that the current drawn from the battery (I BATT ) is calculated.

number

[0082] The efficiency of the buck converter varies over the output current range, with the lowest efficiency being 0.85 at the maximum current of 2.5A.

[0083] Note that battery voltage is inversely proportional to battery draw. For a fixed load, the battery draws more current as the battery discharges. Therefore, a minimum battery voltage must be identified and observed by the system microcontroller to avoid exceeding the battery's maximum discharge current. Table 2 shows how battery current draw increases as the battery discharges. Each battery draw value is calculated using Equation 1 with the following values: η = 0.85, V LED_PWR =2.5V, I LED_PWR = 2.5A, and V BATT relative to the battery voltage. [Table 2]

[0084] Absolute minimum battery voltage, V B_AM To calculate I, we use Equation 2. We use the same values ​​as before, but B_MAX = 1. When discharging to a battery voltage of 7.35V, the battery current draw reaches 1.0A, so the LED needs to be powered off to avoid exceeding the L522 battery's maximum discharge specification of 1.0A. A buck converter providing 2.5A at 2.5V with a battery voltage below 7.35V risks permanent damage to the battery.

number

[0085] The absolute minimum battery voltage also affects battery life. The first graph below shows the discharge curve for an (Energiser L522) battery, showing that a lower absolute minimum battery voltage extends battery life. At a 7.35V absolute minimum battery voltage, the LED can be safely powered for roughly 24 minutes (if the battery were drawing 500mA instead of 1.0A). Therefore, a lower absolute minimum battery voltage is beneficial. [Table 3]

[0086] The 2.5A sourced by the buck converter must be shared among the 6 boards (LEDs), so 2.5A / 6 = 416mA from the buck converter per LED.

[0087] The second graph below shows a manufacturer's graph of normalized luminous flux at 350mA. According to the manufacturer's datasheet, the luminous flux at 350mA ranges between 265mW and 295mW. At 416mA, the luminous flux is approximately 110% of the luminous flux at 350mA. Using a worst-case flux output of 265mA, the luminous flux at 416mA is 265mW x 1.1 = 291.5mW or approximately 292mW. [Table 4]

[0088] A 40 Hz duty cycle will attenuate the luminous flux. Equation 3 shows how to calculate the average flux for a single pulsed LED: E e_pulse is the luminous flux during the pulse, and D 40HZ is the 40Hz duty cycle. D 40HZ The range is a number between 0 and 1, inclusive.

number

[0089] As an example, Table 3 lists the luminous flux for each power setting. [Table 5]

[0090] Luminous flux output decreases with temperature and must therefore be de-rated. Heat sources to consider are LED self-heating and heat from the patient's head. For the purposes of this analysis, the patient's head is assumed to be at body temperature of 37°C. [Table 6]

[0091] Table 4 above lists two thermal coefficients. The thermal resistance of an LED can be understood as the 9.2°C rise in temperature for every 1 watt dissipated by the LED. The third graph below shows the normalized VI characteristics of an LED relative to 350mA at 2V (at 350mA, the forward voltage ranges between 1.2V and 2.0V, and we will continue to use the worst-case value of 2.0V here).

[0092] At 416mA (the maximum current available per LED), the third graph below shows that the forward voltage is approximately 2V + 0.04V = 2.04V. Using Equation 4, the temperature rise due to self-heating is 7.8°C at a 40Hz duty cycle of 100%.

number

[0093] The LED can rise to a temperature of TLED = 37°C + 7.8°C = 44.8°C. The luminous flux versus temperature graph (see further graphs below) is normalized to 25°C. Using the temperature coefficient of radiance power from Table 4 and Equation 5, the change in radiance power due to temperature is -5.94%. Therefore, reducing the worst-case luminous flux rating of 292mW obtained above by 5.94% yields approximately 275mW.

number

[0094] Note that the system also provides a temperature coefficient for the forward voltage. The forward voltage decreases with increasing temperature. For a worst-case analysis, the decrease in forward voltage due to temperature can be ignored.

[0095] 275mW luminous flux is the absolute minimum that can be achieved if the buck converter and battery are at their limits, assuming that the battery only supplies power to the LED.

[0096] The LEDs may not draw the 1.0A maximum from the battery because the battery also provides power to digital logic including microcontrollers, Bluetooth modules, or other wireless connections. [Table 8]

[0097] The following steps are an effort to summarize the approach described above. 1. Start by selecting a target current for a single LED 2. The current sourced by the buck converter is I LED_PWR = 6 × If. I LED_PWR If exceeds 2.5A, If must be reduced. 3. Use Equation 2 to calculate the minimum safe battery voltage to ensure the desired battery life and safe operating conditions. For efficiency, use the worst-case value of 0.85 or use the I value from Table 5. LED_PWR Either select the efficiency that is closest to the value of [Table 9] 4. Use the graph to approximate the luminous flux output to If a. Note: The graph is normalized to a luminous flux of 265 mW at 350 mA. 5. Use a graph to approximate the forward voltage to If a. Note: Graphs are normalized to a 2.0V forward voltage at 350mA. 6. Use Equation 4 to calculate the self-heating temperature rise T Δ_LED Calculate the worst case temperature rise for a 100% 40Hz duty cycle. 40Hz Use =1 7. T above ambient temperature Δ_LED De-rating the luminous flux for rising ambient temperature. Use 37°C. This de-rated luminous flux is the maximum flux output for a single LED.

[0098] Table 6 shows an example of target LED currents and resulting system specifications, allowing for a 100mA margin for battery draw for supply logic. The values ​​calculated in Table 6 assume a worst-case efficiency of 0.85. [Table 10]

[0099] The maximum target LED current is 339mA resulting in a temperature regulated flux output of 223mW. Table 7 shows how a 40Hz duty cycle attenuates the LED output flux. [Table 11]

[0100] EEG can be used to enhance the use of tPBM, for example, to reduce symptoms of autism, a procedure described in further detail below.

[0101] The head-wearable device reduces autism symptoms by applying tPBM to stabilize functional brain connectivity, using EEG data as a measure of tPBM effectiveness and as a guide for continued application. The head-wearable device may include EEG electrodes positioned on one or more of the light-emitting element printed circuit boards described herein. Between one and six EEG electrodes may be mounted on one or more of the light-emitting panels, interleaved between or surrounding the light-emitting elements to detect brainwave signals generated during illumination.

[0102] Autism spectrum disorder (ASD) is a lifelong disorder characterized by repetitive behaviors and deficits in verbal and nonverbal communication. Recent studies have identified early biomarkers of autism, including abnormalities in the EEG of infants, toddlers, and children with ASD compared with typical children. For example, children diagnosed with ASD have significantly more epileptiform seizures (even when they do not become seizures), with some researchers reporting that as many as 30% of children with ASD experience epileptiform seizures (e.g., Spence and Schneider, Pediatric Research 65, 599–606 (2009)). A recent longitudinal study (from 3 to 36 months) found abnormal developmental trajectories in delta and gamma frequencies that distinguished children with an ASD diagnosis from other children (Gabard-Durnam et al., 2019). Short-range hyperconnectivity has also been reported in children with ASD. For example, Orekhova et al. (2014) demonstrated alpha-range hyperconnectivity in the frontal cortex at 14 months (and its correlation with repetitive behavior at 3 years of age). Wang et al. (2013) have shown that individuals with ASD exhibit abnormal distributions of various EEG signals. Specifically, researchers claim that individuals with ASD exhibit excessive power in the low-frequency (delta, theta) and high-frequency (beta, gamma) bands, and reduced relative and absolute power in the mid-range (alpha) frequencies across many brain regions, including the frontal, occipital, parietal, and temporal cortices. This pattern suggests a U-shaped profile of electrophysiological power changes in ASD, with abnormally increased power at the ends of the power spectrum while power in the mid-range frequencies is reduced. [Table 12]

[0103] Based on EEG data, Duffy & Als (2019) argued that ASD is not a spectrum but rather a "cluster" disorder (as they identified two distinct clusters of the ASD population). And Bosl et al., Scientific Reports 8,6828 (2018), used nonlinear analysis of infant EEG data to predict autism in babies as young as three months old. Further details regarding the application of Bosl's computational method can be found in U.S. Patent Application No. 2013 / 0178731, filed March 25, 2013, serial number 13 / 816,645, which is a derivative of International Application No. PCT / US2011 / 047561, filed August 12, 2011, the entire contents of which are incorporated herein by reference. This application describes the application of machine learning and computational techniques, including the use of training data stored over time for many patients and conditions, which can be used to train machine learning systems for use with the methods and devices described herein. Neural networks can be used, for example, to adjust the parameters employed for transcranial illumination in children of a specific age range undergoing treatment for autism. Arrays of 32 or 64 EEG channels can be used with electrodes distributed around the child's skull. Overall, the consensus is that ASD is a functionally unconnected disorder with electrophysiological markers that can be detected through EEG systems. Dickinson et al. (2017) showed that, at the group level, peak alpha frequency was reduced in ASD compared to TD children.

[0104] Transcranial photobiomodulation, as described herein, is used to treat many neurological conditions (TBI, Alzheimer's, depression, anxiety) and is uniquely beneficial for autism because it increases functional connectivity and influences brain rhythms (Zombordi, et al., 2019; Wang et al., 2018). Specifically, Zomorrodi et al. Scientific Reports 9(1) 6309 (2019) showed that applying tPBM (an LED-based device) to the default mode network increased alpha, beta, and gamma power while reducing delta and theta power (at resting state). Wang et al. (2018) also showed significant increases in the alpha and beta bands. Finally, Pruitt et al. (2019) showed that tPBM increased cerebral metabolism in the human brain (by increasing ATP generation).

[0105] Thus, a preferred embodiment uses a system that correlates continuously collected EEG data (as reported by the parent) with observable symptoms and uses the EEG to guide the application of LED-based tPBM. The symptoms provided by the parent can provide ranked data that can be used to define parameters for therapy sessions.

[0106] LED-based tPBM can be applied to the default mode network and occipital lobe (while avoiding the central midline), as well as Broca's area (left parietal lobe) and Wernicke's area (left temporal lobe).

[0107] Stimulating the DMN (and simultaneously stimulating the frontal lobe with the occipital lobe) increases long-range coherence. Stimulating language-producing regions (e.g., the DMN, Broca's area, and Wernicke's area) has been shown to facilitate language production in stroke patients with aphasia (Naeser, 2014).

[0108] The device does the following:

[0109] 1. Analyze initial EEG data for epileptiform seizures, long-range coherence, and hemispheric dominance.

[0110] 2. Correlate EEG data with observed symptoms.

[0111] 3. Based on observed symptoms and EEG data, the head-wearable device may apply tPBM. For example, for a child with severe repetitive behaviors and strong delta and theta power in the prefrontal cortex, the device may stimulate the prefrontal cortex to increase power in the alpha and beta frequency bands (and decrease power in the delta and theta bands). For children who struggle with language, the device may stimulate the DMN and Broca's and Wernicke's areas. For children with varying and severe symptoms, the device may stimulate all identified targeted areas (DMN, Broca's, Wernicke's, and occipital lobes).

[0112] 4. The device may gradually adjust the power, increasing it until a minimal change in brain rhythm is detected. This thresholding avoids applying too much power to the developing brain. The device operates at the lowest power that achieves the desired rhythm.

[0113] 5. As symptoms improve and the measured EEG signal stabilizes, the power level of the device can be gradually reduced. This system can be automated to control each therapy session.

[0114] 6. The machine learning algorithm analyzes the EEG data and behavioral data, power changes that are provided by the algorithm to the parent (and therapist) in the form of guidance, as well as suggestions for further improvements in the therapy being given to the patient.

[0115] 7. As symptoms improve sufficiently (expected improvement is within 8 weeks based on Leisman et al., 2018), the device controls discontinuation from tPBM and collects only EEG and behavioral symptoms to monitor for possible symptom relapse.

[0116] 8. If any backsliding is detected, the device may indicate that tPBM is to be gradually resumed.

[0117] The device can apply tPBM to the DMN, occipital lobe, and Broca's and Wernicke's areas. The device collects EEG from the prefrontal, occipital, and temporal cortices (left and right to monitor hemispheric dominance observed in children with ASD). A platform connected to the device can perform an initial assessment of behavioral symptoms (correlated with EEG data) and ongoing collection of symptoms (allowing for ongoing correlation with EEG). Thus, the platform continuously measures the effectiveness of tPBM.

[0118] The process flow diagram in FIG. 14 illustrates a method 500 for performing transcranial illumination in combination with the use of one or more sensors to measure brain properties, monitor treatment, and detect changes in tissue that indicate response during one or more sessions. A preferred embodiment may utilize an EEG sensor array with a head-wearable device to measure brain field conditions, after which manual or preset parameters are selected for a therapy session 502. The system performs transcranial illumination 504, and data, such as EEG sensor data, is recorded. Depending on the measured data and the patient's condition, the system may automatically adjust operating parameters, or they may be manually adjusted by a clinician 506. The data may be communicated 508 to a computing device, such as a control tablet device, and stored in the patient's electronic medical record. This may be transmitted via a communications network to a hospital or clinic server for storage and further analysis as described herein. Shown in FIG. 15 is a table with example values ​​for lighting conditions that may be employed by the system. These parameters typically fall within a range of values ​​that the system may use, spanning between minimum and maximum thresholds. These thresholds may vary by age, as the thickness and density of a child's skull increases with age. This is explained in Smith et al., "Automated Measurement of Cranial Bone Thickness and Density from Clinical Computed Tomography," IEEE conference proceedings Eng Med Biol Soc 2012:4462-4465 (EMBC 2012), the entire contents of which are incorporated herein by reference. Thus, age-specific quantitative rankings used to define the illumination parameters used for a patient may be associated with each patient. Note that the thickness and / or density of different lobes of a child's brain may increase at different rates over time. Thus, the power density delivered to a 4-year-old child may be less than that used for a 5- or 6-year-old child, for example.

[0119] Thus, the software's operational module may be programmed to retrieve a field or data file of data from a patient data entry module, which may include patient information regarding the child's age, condition, medical history, including medications that may affect further diagnostic or therapy programs, and other initial observations by a parent or clinician. FIG. 16 shows a process flow diagram of a method 600 for selecting and optimizing parameters across multiple therapy sessions, including manual and automated selection procedures. Initially, patient data regarding a child or adult patient (such as age or condition) may be entered by a user into the memory of a computing device (step 602). For example, the data may be entered by the user through the GUI 160 of a remote computing device 150 (such as a tablet computing device) and stored in memory 156 as described above in connection with FIG. 4. Method 600 may then follow one of two procedures. In one embodiment, a user may manually select illumination parameters or therapy session parameters for a first treatment dose level or dose sequence based on the patient data (step 604). For example, a user may manually select parameters from a menu or other display on GUI 160 of remote computing device 150. The lighting parameters and / or therapy session parameters (which may include the user-selected parameters and other parameters, whether automatically determined or set by default) may then be displayed on the computer display (step 606). For example, the parameters may be displayed on visual display device 152. The device may also be programmed to operate a verbal message therapy module and / or a visual message therapy module that communicates auditory and / or visual messages to the patient during the therapy session.

[0120] In alternative embodiments, the parameters may be set using an algorithm or automated. The processor of the computing device may process patient data (e.g., including age and condition data) to determine a first treatment dose level or dose sequence (step 620). For example, processor 155 of remote computing device 150 may analyze and process the patient data. The automatically selected lighting parameters and therapy session parameters (as well as other session parameters) may then be displayed on a display associated with the computing device (step 622). Optionally, the setting of the automatically selected parameters may be augmented in this step with additional manual parameters, such as audio or video files used as part of the therapy session.

[0121] Whether the parameter determination is automatic or manual, the head-wearable device may then be positioned on the patient's (e.g., child or adult's) head, and a therapy session may be operated based on the session parameters (step 608). Data regarding the patient or device during the session may be monitored and recorded. Patient data (e.g., age or condition data) may then be adjusted to optimize the session parameters for future (i.e., second, third, or more) therapy sessions (step 610).

[0122] FIG. 17 shows a process flow diagram of a method 700 for administering a therapy session to a patient, according to various embodiments described herein. As an optional first step, patient data may be entered by a user into a computing device and stored in data fields in a patient data entry module resident on the computing device or server device (step 702). Relevant patient data entered in this step may include patient age, weight, physical or mental state, medication history or regimen, and a data map of skull thickness or density as a function of location on the patient's skull. For example, the patient data entry module may reside in memory 156 of remote computing device 150, and patient data may be entered using GUI 160, such as by using a keyboard, mouse, or multipoint touch interface 420. This step may be considered optional, as patient data for a particular patient may already be resident in the patient data entry module (e.g., data may have been entered during a previous session and does not need to be re-entered). The patient data is then retrieved from the data fields in the patient data entry module using the wearable device operation module (step 704). The wearable device operational module may determine, based on the patient data, a power level as a function of time for each illumination LED 115a-115e in the array of photobiomodulation device 110 to achieve a minimum therapeutic effect during the therapy session. Once the power level is determined, the therapy session may be administered to the patient (step 706).

[0123] After completing the therapy session, output data may be exported in a format compatible with standard medical records using a medical record module (step 708). The output data may include illumination time and / or power for each individual illumination LED, data distribution of which areas of the brain were illuminated, cumulative power delivered, or annotations from the user conducting the session, such as a medical professional. The data may be time course data including timestamps recording when observations or other data events occurred within the therapy session.

[0124] 18 shows a further implementation in which a head-wearable device 800 has light-emitting devices 810 at spaced locations around the patient's head connected by a cable 812 to a circuit housing having a first portion with an on / off switch 802 and a second portion with one or more control buttons or actuators 804 for manually selecting the device's operating mode as described herein. A headphone speaker and / or microphone 814 may be attached to the head-worn device 800, or the speaker / microphone may alternatively be in a first tablet 820 that can be used by the patient during therapy sessions. The first tablet or mobile phone 820 may be connected to the device 800 by a wire or cable 806 and may emit sounds or auditory signals to improve the patient's language skills as described herein. The display on the first tablet may also be used to display images or videos to the patient during therapy sessions. A second tablet or mobile phone 840 may also communicate with the head-mounted device 800 and / or the first tablet via a cable or wireless connection 808. The tablet 840 may be used by an operating user to control the operation of one or both of the head-mounted device 800 and the first tablet 820 before, during, or after a therapy session. For example, if an EEG sensor is used during a therapy session, it may serve to monitor the procedure or calibrate the power level used for a particular patient to establish a minimum level treatment dose, optionally also set a maximum dose for each period of illumination during the session, and optionally select which areas of the patient's brain should be illuminated during the session. The first tablet may be programmed only to provide an auditory and / or visual component to the patient, while the second tablet may be programmed only for use by the operator or clinician to manage the therapy provided to one or more patients in separate sessions.

[0125] Throughout the specification and claims, the following terms have at least the meaning expressly associated therewith herein, unless the context clearly dictates otherwise. The term "or" is intended to mean an inclusive "or." Furthermore, the terms "a," "an," and "the" are intended to mean one or more unless otherwise specified or clear from the context to be directed to the singular form.

[0126] In this description, many specific details have been set forth. However, it should be understood that implementations of the disclosed technology may be practiced without these specific details. In other instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure an understanding of this description. References to "one embodiment," "one embodiment," "some embodiments," "exemplary embodiments," "various embodiments," "one implementation," "one implementation," "exemplary implementation," "various implementations," "some implementations," etc., indicate that implementations of the disclosed technology so described may include a particular feature, structure, or characteristic, but not all implementations necessarily include that particular feature, structure, or characteristic. Furthermore, repeated use of the phrase "in one implementation" does not necessarily refer to the same implementation, although it may.

[0127] As used herein, unless otherwise specified, the use of ordinal adjectives "first," "second," "third," etc. to describe a common object merely indicates that different instances of the same object are being referred to and is not intended to imply that the objects so described must be in any given order, either temporally, spatially, ranked, or in any other manner.

[0128] While particular implementations of the disclosed technology have been described in connection with what are presently considered to be the most practical and various implementations, it is to be understood that the disclosed technology is not limited to the disclosed implementations, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.

[0129] This specification uses examples to disclose particular implementations of the disclosed technology, including the best mode, and also to enable any person skilled in the art to practice particular implementations of the disclosed technology, including making and using any device or system and performing any incorporated methods. The patentable scope of particular implementations of the disclosed technology is defined in the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have elements that do not differ from the literal words of the claims, or if they include equivalent elements with insubstantial differences from the literal words of the claims.

[0130] The exemplary flowcharts are provided herein for illustrative purposes and are non-limiting examples of methods. Those skilled in the art will recognize that the exemplary methods may include more or fewer steps than those shown in the exemplary flowcharts, and that the steps in the exemplary flowcharts may be performed in a different order from the order shown in the exemplary flowcharts. According to this specification, the configurations described in the following items are also disclosed. (Item 1) 1. A portable wearable device sized for placement on a patient's head, the portable wearable device having a light emitting device, a processor, a memory, and a battery for powering the portable wearable device, the light emitting device including a near-infrared wavelength for providing an amount of power during a therapy session, the light emitting device operable to control transmission of transcranial illumination light into the patient in response to a controller, the processor executing instructions stored in the memory to control emission of light by the light emitting device during the therapy session. A photobiomodulation neurotherapy device comprising: The device wherein the memory records the power of the transmitted light delivered to the patient during the therapy session. (Item 2) 10. The device of claim 1, further comprising a transducer device that provides auditory signals to the patient during the therapy session. (Item 3) 3. The device of claim 1 or 2, wherein the processor controls the provision of an auditory signal to the patient with headphones on the portable wearable device. (Item 4) 4. The device of any one of items 1 to 3, further comprising a transceiver on the portable wearable device for receiving wireless control signals to control operation of the portable wearable device. (Item 5) 5. The device of any one of items 1 to 4, wherein the light emitting device further comprises a first light emitting device that illuminates the patient at a first wavelength and a second light emitting device that illuminates the patient at a second, different wavelength. (Item 6) 6. The device of any one of items 1 to 5, wherein the lighting device further comprises a plurality of panels that illuminate the patient from a plurality of different angles, each panel including one or more light-emitting diodes (LEDs). (Item 7) 7. The device of any one of items 1 to 6, further comprising a sensor that measures the patient's physiological response to the transcranial illumination light. (Item 8) Item 8. The device of item 7, wherein the processor controls operation of the portable wearable device in response to the measured physiological response from the sensor. (Item 9) 9. The device of any one of items 1 to 8, wherein the portable wearable device has a size, shape, and weight to be worn by a child to treat a neurological condition. (Item 10) 10. The device of claim 9, wherein the processor is programmed to treat the neurological condition, including autism. (Item 11) Item 11. The device of any one of items 1 to 10, further comprising an EEG sensor that measures the patient's EEG signals using EEG electrodes attached to the patient's head. (Item 12) 7. The device of item 6, wherein each panel has an LED circuit board with at least one light-emitting diode mounted thereon, and each LED circuit board is connected to a processor circuit board mounted on the head-wearable device. (Item 13) Item 13. The device of item 12, wherein the battery is connected to the processor circuit board. (Item 14) 14. The device of any one of items 1 to 13, wherein the head-wearable device communicates with an external computing device by cable, wireless transmission, or a combination thereof. (Item 15) Item 15. The device of item 14, wherein the external computing device has a tablet display device including a touchscreen display that operates in response to a plurality of touch gestures made by a user on a surface of the touchscreen display, and the tablet display device includes a processor programmed with one or more software modules to control operation of the tablet display device and the head-wearable device. (Item 16) Item 16. The device of any one of items 1 to 15, further comprising a power management circuit connected to the battery that controls power distribution to the light emitting device. (Item 17) Item 17. The device of any one of items 1 to 16, wherein the processor has a power management module that controls power distribution to the light-emitting device. (Item 18) Item 18. The device of item 17, wherein the power management module includes programmed instructions such that the processor executes a series of steps to illuminate different regions of the patient's brain tissue with selected levels of light. (Item 19) Item 19. The device of item 18, wherein the selected level of light includes a plurality of presets such that a user may select at least one preset including a length of time, a total area of ​​the skull to be illuminated, and a total amount of light to be delivered to the total area of ​​the patient's skull during a therapy session. (Item 20) Item 19. The device of item 18, wherein the selected level of light is manually selected by a user using a user interface. (Item 21) 21. The device of any one of items 1 to 20, further comprising a computing device in communication with the portable wearable device, the computing device having a user interface for controlling operation of the portable wearable device. (Item 22) Item 22. The device of item 21, wherein the portable wearable device is connected to the computing device using a cable. (Item 23) Item 22. The device of item 21, wherein the portable wearable device communicates with the computing device using a wireless connection. (Item 24) 24. The device of any one of items 21 to 23, wherein the user interface has a graphical user interface operable on a display of the computing device. (Item 25) 25. The device of any one of items 21 to 24, wherein the computing device has a tablet display device. (Item 26) Item 26. The device of item 25, wherein the tablet display device has a touchscreen display. (Item 27) 27. The device of claim 26, wherein a graphical user interface is operable on the touchscreen display that responds to a plurality of touch gestures, thereby enabling a user to control one or more operating parameters of the portable wearable device. (Item 28) 28. The device of any one of items 24 to 27, wherein the graphical user interface includes a plurality of windows selectable by the user to perform a plurality of different data management and control functions of the device. (Item 29) 28. The device of claim 26 or 27, wherein the touchscreen display operates in response to a plurality of static or moving gestures, the plurality of static gestures including a plurality of icons displayable on the touchscreen display. (Item 30) Item 12. The device of item 11, wherein the plurality of EEG electrodes includes one or more electrodes on the prefrontal cortex for measuring theta and delta signals, one or more electrodes on the occipital lobe, and one or more electrodes on the temporal lobe for measuring alpha, beta, and gamma signals. (Item 31) 31. The device of claim 11 or 30, wherein the EEG sensor generates EEG diagnostic data that is received by the processor to control transmission of therapy light through the skull. (Item 32) Item 32. The device of any one of items 1 to 31, further comprising a light sensor positioned to measure light from the patient's head in response to illumination light from the portable wearable device. (Item 33) Item 33. The device of item 32, wherein the optical sensor comprises a near-infrared sensor. (Item 34) Item 34. The device of item 32 or 33, wherein the optical sensor has an array of optical sensors mounted on the portable wearable device to measure light from at least one of the patient's skull or brain tissue, and the array of optical sensors optionally generates diagnostic data that is processed to control the transmission of therapy light through the skull. (Item 35) 35. The device of any one of items 1 to 34, further comprising a machine learning program operable to receive data from the portable wearable device and adjust one or more operating parameters of the portable wearable device. (Item 36) 36. The device of claim 35, wherein the machine learning program processes a plurality of different patient data stored in memory. (Item 37) Item 36. The device of item 35, wherein the machine learning program generates quantitative values ​​for adjusting operating parameters of the portable wearable device. (Item 38) 38. The device of any one of items 1 to 37, wherein the device is programmed to emit light having a maximum radiance value and a minimum threshold radiance value during a therapy period, and wherein the total radiance is selected to have a value within a selectable range of values ​​based on the patient's age and / or skull thickness. (Item 39) Item 12. The device of item 11, wherein the processor receives EEG sensor data, selects a modified lighting radiance value based on the EEG sensor data, and activates at least one light-emitting device of the portable wearable device to direct light having the modified radiance value into the patient. (Item 40) 1. A device for cross-modal brain stimulation, said device comprising: a wearable device sized for placement on a patient's head, the wearable device having a light source positioned to transmit light through the patient's skull; and a processor programmed to control a selected amount of light emitted by the light source of the wearable device using a plurality of operating parameters; a user communication device that communicates verbal messages during a therapy session, wherein the light is emitted by the wearable device at a wavelength in combination with the verbal messages communicated to the patient; a memory for storing data including operational parameters of the wearable device; 1. A device comprising: (Item 41) 41. The device of claim 40, further comprising an EEG sensor for measuring electrical signals in the patient's brain. (Item 42) 42. The device of claim 40 or 41, further comprising a sensor for measuring the selected amount of light emitted into the patient's skull. (Item 43) Item 41. The device of item 40, wherein the wearable device has a battery. (Item 44) Item 41. The device of item 40, wherein the user communication device has a tablet including a touchscreen display and a data processor. (Item 45) 45. The device of any one of items 40 to 44, wherein the user communication device is configured to operate a plurality of program modules, including a patient data entry module, a wearable device operation module, and a medical record module, each module generating a record for each patient having a plurality of data fields. (Item 46) Item 46. The device of item 45, wherein the wearable device operation module obtains data fields from the patient data input module for each patient to perform a corresponding therapy session for each patient. (Item 47) Item 46. The device of item 45, wherein the wearable device has a plurality of panels positioned relative to corresponding regions of the patient's skull. (Item 48) Item 48. The device of item 47, wherein each panel has one or more light-emitting diodes (LEDs) connected to a printed circuit board mounted on the wearable device, and the processor and memory are mounted on the printed circuit board. (Item 49) 49. The device of any one of items 40 to 48, wherein the verbal message includes at least one of a word or phrase for treating a patient with autism. (Item 50) Item 41. The device of item 40, wherein the verbal message is communicated to the patient with the user communication device being used by the patient during a therapy session. (Item 51) Item 41. The device of item 40, wherein the verbal message is communicated to the patient with the wearable device. (Item 52) Item 41. The device of item 40, wherein the user communication device has a processor configured to operate a language message program stored in memory. (Item 53) Item 53. The device of item 52, wherein the language message is streamed to the wearable device via a wireless link. (Item 54) 1. A wearable device for cross-modal brain stimulation, the wearable device comprising: A transmitter / receiver, one or more light emitting diodes (LEDs); One or more headphones; one or more processors; a signal processor configured to generate a signal in communication with the transceiver, the one or more LEDs, the one or more headphones, and the one or more processors, the signal processor being ... causing the one or more processors to determine wavelengths of light emitted by the one or more LEDs; receiving, by the transceiver, a language input from a user device; causing the one or more LEDs and the one or more headphones to emit the wavelengths of light and the language input, respectively. Memory for storing instructions and 1. A device comprising: (Item 55) Item 55. The device of item 54, wherein a plurality of the LEDs are mounted on each of a plurality of circuit boards, each LED having a lens to couple emitted light to the patient's skull so that the light is transmitted through the skull and into a portion of the patient's brain tissue, and wherein the wavelength and intensity of the transmitted light comprise parameters of a therapeutic dose of light to treat autism. (Item 56) 56. The device of claim 54 or 55, further comprising a touchscreen tablet in communication with the wearable device, the touchscreen tablet having a data processor and memory, the data processor configured to operate a light-emitting module, a speech therapy module, a patient data entry module, and an electronic medical record module. (Item 57) 57. The device of any one of items 54 to 56, further comprising an EEG sensor configured to be attached to the patient to measure brain activity during a light stimulation therapy session. (Item 58) placing a portable wearable device on the patient's head, the portable wearable device having a light-emitting device, a processor, a memory, and a battery that provides power to the light-emitting device; transmitting transcranial illumination light into the patient, the illumination light comprising a near-infrared wavelength to provide an amount of power during a therapy session, the processor executing instructions stored in the memory to control emission of light by the light-emitting device during the therapy session; storing a record of the transmitted light power delivered to the patient during the therapy session; and 1. A method for photobiomodulation neurotherapy comprising: (Item 59) 59. The method of claim 58, further comprising providing an auditory signal to the patient during the therapy session. (Item 60) 59. The method of claim 58, further comprising providing an auditory signal to the patient with headphones on the portable wearable device. (Item 61) Item 59. The method of item 58, further comprising communicating with a transceiver on the portable wearable device to control operation of the portable wearable device. (Item 62) 59. The method of claim 58, further comprising illuminating the patient with a plurality of different wavelengths. (Item 63) 59. The method of claim 58, further comprising illuminating the patient from a plurality of different angles from a plurality of panels of the lighting device, each panel having a plurality of light emitting diodes. (Item 64) 59. The method of claim 58, further comprising measuring the patient's physiological response to the transcranial illumination light. (Item 65) Item 65. The method of item 64, further comprising controlling operation of the portable wearable device in response to the measured physiological response. (Item 66) Item 59. The method of item 58, wherein the portable wearable device is configured to be worn by a child to treat a neurological condition, and wherein the radiance of the emitted light is selected based on the age of the child to be a total dose of light between a minimum therapeutic dose and a maximum threshold dose. (Item 67) 67. The method of claim 66, wherein the neurological condition comprises autism. (Item 68) 68. The method of any one of items 58 to 67, further comprising measuring EEG signals using EEG electrodes attached to the head of the patient. (Item 69) 69. The method of any one of items 58 to 68, further comprising using a computing device to communicate operating parameters for conducting a therapy session to the portable wearable device, the operating parameters optionally including a radiance level selected from among a plurality of levels based on at least one of an age and a cranial thickness of the patient. (Item 70) Item 69. The method of claim 69, wherein the computing device has a data processor and memory, the data processor is configured to operate an operational module that communicates the operational parameters, a patient data entry module, and an electronic medical record module, and the computing device optionally has a touchscreen tablet display device including a graphical user interface such that a plurality of touch gestures operate each of the operational module, the patient data entry module, and the electronic medical record module. (Item 71) 1. A method for cross-modal brain stimulation, said method comprising: placing a wearable device on the patient's head; determining a wavelength of light emitted by the wearable device; receiving linguistic input from a user device; simultaneously emitting, by the wearable device, the wavelength of light and a verbal message corresponding to the verbal input; storing the data in memory; A method for providing the above. (Item 72) 72. The method of claim 71, further comprising operating an EEG sensor to measure electrical signals in the patient's brain. (Item 73) 72. The method of claim 71, further comprising transmitting the light through the patient's skull. (Item 74) Item 72. The method of item 71, further comprising transmitting the language input from the user device to the wearable device using a wired or wireless connection, the user device optionally having a touchscreen tablet computer including a data processor and memory configured to operate an operating parameter module to control the wearable device, a patient data input module, and an electronic medical record module. (Item 75) 75. The method of any one of items 71 to 74, further comprising conducting a therapy session to treat autism in a child, wherein the radiance of the emitted light has a selectable level between a minimum therapeutic dose of light and a maximum therapeutic dose of light.

Claims

1. 1. A photobiomodulation neurotherapy device, comprising: a portable head-mounted device sized for placement on a patient's head, the portable head-mounted device having a light-emitting device, a memory, and a battery that provides power to the portable head-mounted device, the light-emitting device operable to control transmission of transcranial illumination light through the patient's skull in response to a controller on the portable head-mounted device, the illumination light comprising a near-infrared wavelength to provide an amount of power during a therapy session, the controller executing instructions stored in the memory to control emission of light by the light-emitting device during the therapy session to illuminate the frontal and occipital lobes, thereby treating the patient's neurological condition; a wireless transceiver on the portable head-worn device connected to the controller for receiving wireless control signals to control operation of the portable head-worn device; Equipped with the memory records the power of the transmitted light delivered to the patient during the therapy session. device.

2. The device of claim 1 , further comprising a transducer device that delivers auditory signals to the patient during the therapy session, the controller controlling delivery of the auditory signals to the patient.

3. 3. The device of claim 1 or 2, wherein the lighting device further comprises a plurality of panels for illuminating the patient from a plurality of different angles, each panel including one or more light emitting diodes.

4. 4. The device of claim 1, further comprising a sensor that measures the patient's physiological response to the transcranial illumination light, and wherein the controller controls operation of the portable head-mounted device in response to the measured physiological response from the sensor.

5. 5. The device of claim 1, wherein the portable head-worn device has a size, shape, and weight to be worn by a child to treat a neurological condition, and the controller is programmed to treat the neurological condition, including autism.

6. 6. The device of claim 1, further comprising an EEG sensor for measuring EEG signals of the patient using EEG electrodes attached to the head of the patient.

7. 4. The device of claim 3, wherein each panel has an LED circuit board with at least one light emitting diode mounted thereon, each LED circuit board connected to a controller circuit board mounted on the portable head-worn device, and the battery connected to the controller circuit board.

8. 8. The device of claim 1, further comprising a power management circuit connected to the battery that controls power distribution to the light emitting device.

9. 10. The device of claim 8, wherein the power management circuitry is operated by a module containing programmed instructions such that the controller executes a series of steps to illuminate different regions of the patient's brain tissue with selected levels of light.

10. 10. The device of claim 9, wherein the selected level of light comprises a plurality of presets or the selected level of light is manually selected by the user using a user interface such that the user may select at least one preset comprising a length of time, a total area of ​​the skull to be illuminated, and a total amount of light delivered to the total area of ​​the patient's skull during a therapy session.

11. the EEG electrodes include one or more electrodes on the prefrontal cortex for measuring theta and delta signals, one or more electrodes on the occipital lobe, and one or more electrodes on the temporal lobe for measuring alpha, beta, and gamma signals; 7. The device of claim 6, wherein the EEG sensor generates EEG diagnostic data that is received by the controller to control transmission of therapeutic light through the skull.

12. 12. The device of claim 1, further comprising a light sensor arranged to measure light from the patient's head in response to illumination light from the portable head-mounted device, or the light sensor has an array of light sensors mounted on the portable head-mounted device to measure light from at least one of the patient's skull or brain tissue, the array of light sensors optionally generating diagnostic data that is processed to control the transmission of therapeutic light through the skull.

13. further comprising a machine learning program operable to receive data from the portable head-mounted device and adjust one or more operating parameters of the portable head-mounted device; the machine learning program processes a plurality of different patient data stored in a memory; The device of claim 1 , wherein the machine learning program generates quantitative values ​​for adjusting operating parameters of the portable head-worn device.

14. 14. The device of any one of claims 1 to 13, wherein the device is programmed to emit light having a maximum radiance value and a minimum threshold radiance value during a therapy session, and wherein the total radiance is selected to have a value within a selectable range of values ​​based on the patient's age and / or skull thickness.

15. 7. The device of claim 6, wherein the controller receives EEG sensor data, selects a modified illumination radiance value based on the EEG sensor data, and activates at least one light-emitting device of the portable head-worn device to direct light having the modified illumination radiance value into the patient.

16. 16. A system comprising the photobiomodulation neurotherapy device of any one of claims 1 to 15 and a computing device, the portable head-worn device is configured to communicate with the computing device by cable, wireless transmission, or a combination thereof; The system includes a tablet display device, the tablet display device including a touchscreen display that operates in response to a plurality of touch gestures made by a user on a surface of the touchscreen display, and the tablet display device includes a controller programmed with one or more software modules to control operation of the tablet display device and the portable head-worn device.

17. 16. A system comprising the photobiomodulation neurotherapy device of any one of claims 1 to 15 and a computing device, the computing device is configured to communicate with the portable head-worn device; the computing device has a user interface for controlling operation of the portable head-worn device; the portable head-worn device communicates with the computing device using a wireless or wired connection; The system, wherein the user interface comprises a graphical user interface operable on a display of the computing device.

18. the graphical user interface is operable on a touchscreen display responsive to a plurality of touch gestures by which a user may control one or more operating parameters of the portable head-worn device; 20. The system of claim 17, wherein the graphical user interface includes a plurality of windows selectable by the user to perform a plurality of different data management and control functions of the device.

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