Wearable Extended Reality-Based Neuroscience Analysis Systems

An illustrative system may include an extended reality system and a brain interface system configured to be concurrently worn by a user. The extended reality system may be configured to provide the user with an extended reality experience (e.g., an immersive virtual reality experience or a non-immersive augmented reality experience). The brain interface system may be configured to acquire one or more brain activity measurements while the extended reality experience is being provided to the user.

BACKGROUND INFORMATION

Neuroscience studies that involve the use of brain interface systems (e.g., magnetic resonance imaging (MRI) machines, functional MRI (fMRI) machines, electroencephalography (EEG) equipment, optical signal measurement systems, etc.) are often affected by varying environmental conditions. For example, variations in lighting, peripheral noise, room size, and study parameters used for different participants in a neuroscience study may be difficult or even impossible to account for in the results of the neuroscience study.

DETAILED DESCRIPTION

Wearable extended reality-based neuroscience analysis systems and methods are described herein. For example, an illustrative system may include an extended reality system and a brain interface system configured to be concurrently worn by a user. The extended reality system may be configured to provide the user with an extended reality experience (e.g., an immersive virtual reality experience or a non-immersive augmented reality experience). The brain interface system may be configured to acquire one or more brain activity measurements while the extended reality experience is being provided to the user.

As demonstrated herein, the concurrent use of a wearable extended reality system and a wearable brain interface system may provide various benefits and advantages over conventional neuroscience study configurations. For example, the systems and methods described herein may reduce (e.g., eliminate) study variances due to variable environmental conditions (e.g., lighting conditions, peripheral noise, room size and/or material, etc.); create perceived naturalistic motion for users without too much actual motion; enable safe, remote and simultaneous social interaction between users; improve generalizability to real-world tasks beyond what is possible in the laboratory; and/or standardize task/stimulus design and hardware calibrations to be “plug and play” regardless of the environment in which neuroscience studies may be performed. Moreover, virtual reality in particular has the potential to expand the reach of neuroscience through enabling real-time neurofeedback in a fully immersive environment. This may open up a realm of possibilities in the fields of training, education, and/or general self-improvement. All of these factors contribute to increased replicability, study power, and ecological relevance compared to conventional neuroscience study configurations that do not incorporate the use of extended reality.

Synchronization between a brain interface system and an extended reality system is also described herein. For example, an illustrative system may include an extended reality system and a brain interface system configured to be concurrently worn by a user. The extended reality system may be configured to provide the user with an extended reality experience and output a timing signal (e.g., an audio signal) while the extended reality experience is being provided to the user. The timing signal may represent a plurality of timing events that occur during the extended reality experience. The extended reality system may be further configured to output extended reality event timestamp data representative of a temporal association of extended reality events with the timing events, the extended reality events occurring while the extended reality experience is being provided to the user.

The brain interface system in this example may be configured to receive the timing signal from the extended reality system while the extended reality experience is being provided to the user, acquire brain activity measurements while the extended reality experience is being provided to the user, and output measurement timestamp data representative of a temporal association of the brain activity measurements with the timing events.

Because the measurement timestamp data output by the brain interface system and the extended reality event timestamp data output by the extended reality event timestamp data are based on the same timing signal, a processing system communicatively coupled to the extended reality system and/or the brain interface system may be configured to synchronize the measurement timestamp data with the extended reality event timestamp data. This may allow researchers and/or others to ascertain correlations between extended reality events and brain activity measurements.

Coupled with extremely high-dimensional behavioral data (e.g., eye-tracking, motion tracking, etc., with the possibility of thousands of events logged from the extended reality system every second), a wearable brain interface system configured to function in a time-synchronized manner with a wearable extended reality system may provide a number of benefits and advantages over conventional neuroscience analysis systems. For example, the systems and methods described herein may provide a scalable ecosystem that may be used to facilitate neuroscience studies and experiments that involve users located at any suitable location (e.g., in their homes, in their classroom, in separate laboratories, in laboratories located in various locations, etc.). The systems and methods described herein can also reach subjects/patients who normally cannot be confined in a hospital environment due to limiting health or mobility concerns.

FIG. 1shows an exemplary wearable extended reality-based neuroscience analysis system100(“wearable system100”). As shown, wearable system100includes a brain interface system102and an extended reality system104coupled by way of a communication link106.

To illustrate,FIGS. 2-4, 5A, and 5Bshow various optical measurement systems and related components that may implement brain interface system102. The optical measurement systems described herein are merely illustrative of the many different optical-based brain interface systems that may be used in accordance with the systems and methods described herein.

FIG. 2shows an optical measurement system200that may be configured to perform an optical measurement operation with respect to a body202(e.g., the brain). Optical measurement system200may, in some examples, be portable and/or wearable by a user.

In some examples, optical measurement operations performed by optical measurement system200are associated with a time domain-based optical measurement technique. Example time domain-based optical measurement techniques include, but are not limited to, time-correlated single-photon counting (TCSPC), time domain near infrared spectroscopy (TD-NIRS), time domain diffusive correlation spectroscopy (TD-DCS), and time domain digital optical tomography (TD-DOT).

Optical measurement system200(e.g., an optical measurement system that is implemented by a wearable device or other configuration, and that employs a time domain-based (e.g., TD-NIRS) measurement technique) may detect blood oxygenation levels and/or blood volume levels by measuring the change in shape of laser pulses after they have passed through target tissue, e.g., brain, muscle, finger, etc. As used herein, a shape of laser pulses refers to a temporal shape, as represented for example by a histogram generated by a time-to-digital converter (TDC) coupled to an output of a photodetector, as will be described more fully below.

As shown, optical measurement system200includes a detector204that includes a plurality of individual photodetectors (e.g., photodetector206), a processor208coupled to detector204, a light source210, a controller212, and optical conduits214and216(e.g., light pipes). However, one or more of these components may not, in certain embodiments, be considered to be a part of optical measurement system200. For example, in implementations where optical measurement system200is wearable by a user, processor208and/or controller212may in some embodiments be separate from optical measurement system200and not configured to be worn by the user.

Detector204may include any number of photodetectors206as may serve a particular implementation, such as 2nphotodetectors (e.g., 256, 512, . . . , 26384, etc.), where n is an integer greater than or equal to one (e.g., 4, 5, 8, 20, 21, 24, etc.). Photodetectors206may be arranged in any suitable manner.

Photodetectors206may each be implemented by any suitable circuit configured to detect individual photons of light incident upon photodetectors206. For example, each photodetector206may be implemented by a single photon avalanche diode (SPAD) circuit and/or other circuitry as may serve a particular implementation. The SPAD circuit may be gated in any suitable manner or be configured to operate in a free running mode with passive quenching. For example, photodetectors206may be configured to operate in a free-running mode such that photodetectors206are not actively armed and disarmed (e.g., at the end of each predetermined gated time window). In contrast, while operating in the free-running mode, photodetectors206may be configured to reset within a configurable time period after an occurrence of a photon detection event (i.e., after photodetector206detects a photon) and immediately begin detecting new photons. However, only photons detected within a desired time window (e.g., during each gated time window) may be included in the histogram that represents a light pulse response of the target (e.g., a temporal point spread function (TPSF)). The terms histogram and TPSF are used interchangeably herein to refer to a light pulse response of a target.

Processor208may be implemented by one or more physical processing (e.g., computing) devices. In some examples, processor208may execute instructions (e.g., software) configured to perform one or more of the operations described herein.

Light source210may be implemented by any suitable component configured to generate and emit light. For example, light source210may be implemented by one or more laser diodes, distributed feedback (DFB) lasers, super luminescent diodes (SLDs), light emitting diodes (LEDs), diode-pumped solid-state (DPSS) lasers, super luminescent light emitting diodes (sLEDs), vertical-cavity surface-emitting lasers (VCSELs), titanium sapphire lasers, micro light emitting diodes (mLEDs), and/or any other suitable laser or light source. In some examples, the light emitted by light source210is high coherence light (e.g., light that has a coherence length of at least 5 centimeters) at a predetermined center wavelength.

Light source210is controlled by controller212, which may be implemented by any suitable computing device (e.g., processor208), integrated circuit, and/or combination of hardware and/or software as may serve a particular implementation. In some examples, controller212is configured to control light source210by turning light source210on and off and/or setting an intensity of light generated by light source210. Controller212may be manually operated by a user, or may be programmed to control light source210automatically.

Light emitted by light source210may travel via an optical conduit214(e.g., a light pipe, a single-mode optical fiber, and/or or a multi-mode optical fiber) to body202of a subject. Body202may include any suitable turbid medium. For example, in some implementations, body202is a brain or any other body part of a human or other animal. Alternatively, body202may be a non-living object. For illustrative purposes, it will be assumed in the examples provided herein that body202is a human brain.

As indicated by arrow220, the light emitted by light source210enters body202at a first location222on body202. Accordingly, a distal end of optical conduit214may be positioned at (e.g., right above, in physical contact with, or physically attached to) first location222(e.g., to a scalp of the subject). In some examples, the light may emerge from optical conduit214and spread out to a certain spot size on body202to fall under a predetermined safety limit. At least a portion of the light indicated by arrow220may be scattered within body202.

As used herein, “distal” means nearer, along the optical path of the light emitted by light source210or the light received by detector204, to the target (e.g., within body202) than to light source210or detector204. Thus, the distal end of optical conduit214is nearer to body202than to light source210, and the distal end of optical conduit216is nearer to body202than to detector204. Additionally, as used herein, “proximal” means nearer, along the optical path of the light emitted by light source210or the light received by detector204, to light source210or detector204than to body202. Thus, the proximal end of optical conduit214is nearer to light source210than to body202, and the proximal end of optical conduit216is nearer to detector204than to body202.

As shown, the distal end of optical conduit216(e.g., a light pipe, a light guide, a waveguide, a single-mode optical fiber, and/or a multi-mode optical fiber) is positioned at (e.g., right above, in physical contact with, or physically attached to) output location226on body202. In this manner, optical conduit216may collect at least a portion of the scattered light (indicated as light224) as it exits body202at location226and carry light224to detector204. Light224may pass through one or more lenses and/or other optical elements (not shown) that direct light224onto each of the photodetectors206included in detector204. In cases where optical conduit216is implemented by a light guide, the light guide may be spring loaded and/or have a cantilever mechanism to allow for conformably pressing the light guide firmly against body202.

Photodetectors206may be connected in parallel in detector204. An output of each of photodetectors206may be accumulated to generate an accumulated output of detector204. Processor208may receive the accumulated output and determine, based on the accumulated output, a temporal distribution of photons detected by photodetectors206. Processor208may then generate, based on the temporal distribution, a histogram representing a light pulse response of a target (e.g., brain tissue, blood flow, etc.) in body202. Such a histogram is illustrative of the various types of brain activity measurements that may be performed by brain interface system102.

FIG. 3shows an exemplary optical measurement system300in accordance with the principles described herein. Optical measurement system300may be an implementation of optical measurement system200and, as shown, includes a wearable assembly302, which includes N light sources304(e.g., light sources304-1through304-N) and M detectors306(e.g., detectors306-1through306-M). Optical measurement system300may include any of the other components of optical measurement system200as may serve a particular implementation. N and M may each be any suitable value (i.e., there may be any number of light sources304and detectors306included in optical measurement system300as may serve a particular implementation).

Light sources304are each configured to emit light (e.g., a sequence of light pulses) and may be implemented by any of the light sources described herein. Detectors306may each be configured to detect arrival times for photons of the light emitted by one or more light sources304after the light is scattered by the target. For example, a detector306may include a photodetector configured to generate a photodetector output pulse in response to detecting a photon of the light and a time-to-digital converter (TDC) configured to record a timestamp symbol in response to an occurrence of the photodetector output pulse, the timestamp symbol representative of an arrival time for the photon (i.e., when the photon is detected by the photodetector).

Wearable assembly302may be implemented by any of the wearable devices, modular assemblies, and/or wearable units described herein. For example, wearable assembly302may be implemented by a wearable device (e.g., headgear) configured to be worn on a user's head. Wearable assembly302may additionally or alternatively be configured to be worn on any other part of a user's body.

Optical measurement system300may be modular in that one or more components of optical measurement system300may be removed, changed out, or otherwise modified as may serve a particular implementation. As such, optical measurement system300may be configured to conform to three-dimensional surface geometries, such as a user's head. Exemplary modular optical measurement systems comprising a plurality of wearable modules are described in more detail in one or more of the patent applications incorporated herein by reference.

FIG. 4shows an illustrative modular assembly400that may implement optical measurement system300. Modular assembly400is illustrative of the many different implementations of optical measurement system300that may be realized in accordance with the principles described herein.

As shown, modular assembly400includes a plurality of modules402(e.g., modules402-1through402-3) physically distinct one from another. While three modules402are shown to be included in modular assembly400, in alternative configurations, any number of modules402(e.g., a single module up to sixteen or more modules) may be included in modular assembly400.

Each module402includes a light source (e.g., light source404-1of module402-1and light source404-2of module402-2) and a plurality of detectors (e.g., detectors406-1through406-6of module402-1). In the particular implementation shown inFIG. 4, each module402includes a single light source and six detectors. Each light source is labeled “S” and each detector is labeled

Each light source depicted inFIG. 4may be implemented by one or more light sources similar to light source210and may be configured to emit light directed at a target (e.g., the brain).

Each light source depicted inFIG. 4may be located at a center region of a surface of the light source's corresponding module. For example, light source404-1is located at a center region of a surface408of module402-1. In alternative implementations, a light source of a module may be located away from a center region of the module.

Each detector depicted inFIG. 4may implement or be similar to detector204and may include a plurality of photodetectors (e.g., SPADs) as well as other circuitry (e.g., TDCs), and may be configured to detect arrival times for photons of the light emitted by one or more light sources after the light is scattered by the target.

The detectors of a module may be distributed around the light source of the module. For example, detectors406of module402-1are distributed around light source404-1on surface408of module402-1. In this configuration, detectors406may be configured to detect photon arrival times for photons included in light pulses emitted by light source404-1. In some examples, one or more detectors406may be close enough to other light sources to detect photon arrival times for photons included in light pulses emitted by the other light sources. For example, because detector406-3is adjacent to module402-2, detector406-3may be configured to detect photon arrival times for photons included in light pulses emitted by light source404-2(in addition to detecting photon arrival times for photons included in light pulses emitted by light source404-1).

In some examples, the detectors of a module may all be equidistant from the light source of the same module. In other words, the spacing between a light source (i.e., a distal end portion of a light source optical conduit) and the detectors (i.e., distal end portions of optical conduits for each detector) are maintained at the same fixed distance on each module to ensure homogeneous coverage over specific areas and to facilitate processing of the detected signals. The fixed spacing also provides consistent spatial (lateral and depth) resolution across the target area of interest, e.g., brain tissue. Moreover, maintaining a known distance between the light source, e.g., light emitter, and the detector allows subsequent processing of the detected signals to infer spatial (e.g., depth localization, inverse modeling) information about the detected signals. Detectors of a module may be alternatively disposed on the module as may serve a particular implementation.

In some examples, modular assembly400can conform to a three-dimensional (3D) surface of the human subject's head, maintain tight contact of the detectors with the human subject's head to prevent detection of ambient light, and maintain uniform and fixed spacing between light sources and detectors. The wearable module assemblies may also accommodate a large variety of head sizes, from a young child's head size to an adult head size, and may accommodate a variety of head shapes and underlying cortical morphologies through the conformability and scalability of the wearable module assemblies. These exemplary modular assemblies and systems are described in more detail in U.S. patent applications Ser. No. 17/176,470; Ser. No. 17/176,487; Ser. No. 17/176,539; Ser. No. 17/176,560; Ser. No. 17/176,460; and Ser. No. 17/176,466, which applications have been previously incorporated herein by reference in their respective entireties.

InFIG. 4, modules402are shown to be adjacent to and touching one another. Modules402may alternatively be spaced apart from one another. For example,FIGS. 5A-5Bshow an exemplary implementation of modular assembly400in which modules402are configured to be inserted into individual slots502(e.g., slots502-1through502-3, also referred to as cutouts) of a wearable assembly504. In particular,FIG. 5Ashows the individual slots502of the wearable assembly504before modules402have been inserted into respective slots502, andFIG. 5Bshows wearable assembly504with individual modules402inserted into respective individual slots502.

Wearable assembly504may implement wearable assembly302and may be configured as headgear and/or any other type of device configured to be worn by a user.

As shown inFIG. 5A, each slot502is surrounded by a wall (e.g., wall506) such that when modules402are inserted into their respective individual slots502, the walls physically separate modules402one from another. In alternative embodiments, a module (e.g., module402-1) may be in at least partial physical contact with a neighboring module (e.g., module402-2).

Each of the modules described herein may be inserted into appropriately shaped slots or cutouts of a wearable assembly, as described in connection withFIGS. 5A-5B. However, for ease of explanation, such wearable assemblies are not shown in the figures.

As shown inFIGS. 4 and 5B, modules402may have a hexagonal shape. Modules402may alternatively have any other suitable geometry (e.g., in the shape of a pentagon, octagon, square, rectangular, circular, triangular, free-form, etc.).

As another example, brain interface system102may be implemented by a wearable multimodal measurement system configured to perform both optical-based brain data acquisition operations and electrical-based brain data acquisition operations, such as any of the wearable multimodal measurement systems described in U.S. patent application Ser. No. 17/176,315 and Ser. No. 17/176,309, which applications have been previously incorporated herein by reference in their respective entireties.

To illustrate,FIGS. 6-7show various multimodal measurement systems that may implement brain interface system102. The multimodal measurement systems described herein are merely illustrative of the many different multimodal-based brain interface systems that may be used in accordance with the systems and methods described herein.

FIG. 6shows an exemplary multimodal measurement system600in accordance with the principles described herein. Multimodal measurement system600may at least partially implement optical measurement system200and, as shown, includes a wearable assembly602(which is similar to wearable assembly302), which includes N light sources604(e.g., light sources604-1through604-N, which are similar to light sources304), M detectors606(e.g., detectors606-1through606-M, which are similar to detectors306), and X electrodes (e.g., electrodes608-1through608-X). Multimodal measurement system600may include any of the other components of optical measurement system200as may serve a particular implementation. N, M, and X may each be any suitable value (i.e., there may be any number of light sources604, any number of detectors606, and any number of electrodes608included in multimodal measurement system600as may serve a particular implementation).

Electrodes608may be configured to detect electrical activity within a target (e.g., the brain). Such electrical activity may include electroencephalogram (EEG) activity and/or any other suitable type of electrical activity as may serve a particular implementation. In some examples, electrodes608are all conductively coupled to one another to create a single channel that may be used to detect electrical activity. Alternatively, at least one electrode included in electrodes608is conductively isolated from a remaining number of electrodes included in electrodes608to create at least two channels that may be used to detect electrical activity.

FIG. 7shows an illustrative modular assembly700that may implement multimodal measurement system600. As shown, modular assembly700includes a plurality of modules702(e.g., modules702-1through702-3). While three modules702are shown to be included in modular assembly700, in alternative configurations, any number of modules702(e.g., a single module up to sixteen or more modules) may be included in modular assembly700. Moreover, while each module702has a hexagonal shape, modules702may alternatively have any other suitable geometry (e.g., in the shape of a pentagon, octagon, square, rectangular, circular, triangular, free-form, etc.).

Each module702includes a light source (e.g., light source704-1of module702-1and light source704-2of module702-2) and a plurality of detectors (e.g., detectors706-1through706-6of module702-1). In the particular implementation shown inFIG. 7, each module702includes a single light source and six detectors. Alternatively, each module702may have any other number of light sources (e.g., two light sources) and any other number of detectors. The various components of modular assembly700shown inFIG. 7are similar to those described in connection withFIG. 4.

As shown, modular assembly700further includes a plurality of electrodes710(e.g., electrodes710-1through710-3), which may implement electrodes608. Electrodes710may be located at any suitable location that allows electrodes710to be in physical contact with a surface (e.g., the scalp and/or skin) of a body of a user. For example, in modular assembly700, each electrode710is on a module surface configured to face a surface of a user's body when modular assembly700is worn by the user. To illustrate, electrode710-1is on surface708of module702-1. Moreover, in modular assembly700, electrodes710are located in a center region of each module702and surround each module's light source704. Alternative locations and configurations for electrodes710are possible.

As another example, brain interface system102may be implemented by a wearable magnetic field measurement system configured to perform magnetic field-based brain data acquisition operations, such as any of the magnetic field measurement systems described in U.S. patent application Ser. No. 16/862,879, filed Apr. 30, 2020 and published as US2020/0348368A1; U.S. Provisional Application No. 63/170,892, filed Apr. 5, 2021, U.S. Non-Provisional application Ser. No. 17/338,429, filed Jun. 3, 2021, and Ethan J. Pratt, et al., “Kernel Flux: A Whole-Head 432-Magnetometer Optically-Pumped Magnetoencephalography (OP-MEG) System for Brain Activity Imaging During Natural Human Experiences,” SPIE Photonics West Conference (Mar. 6, 2021), which applications and publication are incorporated herein by reference in their entirety. In some examples, any of the magnetic field measurement systems described herein may be used in a magnetically shielded environment which allows for natural user movement as described for example in U.S. Provisional Patent Application No. 63/076,015, filed Sep. 9, 2020, and U.S. Non-Provisional patent application Ser. No. 17/328,235, filed May 24, 2021, which applications are incorporated herein by reference in their entirety.

FIG. 8shows an exemplary magnetic field measurement system800(“system800”) that may implement brain interface system102. As shown, system800includes a wearable sensor unit802and a controller804. Wearable sensor unit802includes a plurality of magnetometers806-1through806-N (collectively “magnetometers806”, also referred to as optically pumped magnetometer (OPM) modular assemblies as described below) and a magnetic field generator808. Wearable sensor unit802may include additional components (e.g., one or more magnetic field sensors, position sensors, orientation sensors, accelerometers, image recorders, detectors, etc.) as may serve a particular implementation. System800may be used in magnetoencephalography (MEG) and/or any other application that measures relatively weak magnetic fields.

Wearable sensor unit802is configured to be worn by a user (e.g., on a head of the user). In some examples, wearable sensor unit802is portable. In other words, wearable sensor unit802may be small and light enough to be easily carried by a user and/or worn by the user while the user moves around and/or otherwise performs daily activities, or may be worn in a magnetically shielded environment which allows for natural user movement as described more fully in U.S. Provisional Patent Application No. 63/076,015, and U.S. Non-Provisional patent application Ser. No. 17/328,235, filed May 24, 2021, previously incorporated by reference.

Any suitable number of magnetometers806may be included in wearable sensor unit802. For example, wearable sensor unit802may include an array of nine, sixteen, twenty-five, or any other suitable plurality of magnetometers806as may serve a particular implementation.

Magnetometers806may each be implemented by any suitable combination of components configured to be sensitive enough to detect a relatively weak magnetic field (e.g., magnetic fields that come from the brain). For example, each magnetometer may include a light source, a vapor cell such as an alkali metal vapor cell (the terms “cell”, “gas cell”, “vapor cell”, and “vapor gas cell” are used interchangeably herein), a heater for the vapor cell, and a photodetector (e.g., a signal photodiode). Examples of suitable light sources include, but are not limited to, a diode laser (such as a vertical-cavity surface-emitting laser (VCSEL), distributed Bragg reflector laser (DBR), or distributed feedback laser (DFB)), light-emitting diode (LED), lamp, or any other suitable light source. In some embodiments, the light source may include two light sources: a pump light source and a probe light source.

Magnetic field generator808may be implemented by one or more components configured to generate one or more compensation magnetic fields that actively shield magnetometers806(including respective vapor cells) from ambient background magnetic fields (e.g., the Earth's magnetic field, magnetic fields generated by nearby magnetic objects such as passing vehicles, electrical devices and/or other field generators within an environment of magnetometers806, and/or magnetic fields generated by other external sources). For example, magnetic field generator808may include one or more coils configured to generate compensation magnetic fields in the Z direction, X direction, and/or Y direction (all directions are with respect to one or more planes within which the magnetic field generator808is located). The compensation magnetic fields are configured to cancel out, or substantially reduce, ambient background magnetic fields in a magnetic field sensing region with minimal spatial variability.

Controller804is configured to interface with (e.g., control an operation of, receive signals from, etc.) magnetometers806and the magnetic field generator808. Controller804may also interface with other components that may be included in wearable sensor unit802.

In some examples, controller804is referred to herein as a “single” controller804. This means that only one controller is used to interface with all of the components of wearable sensor unit802. For example, controller804may be the only controller that interfaces with magnetometers806and magnetic field generator808. It will be recognized, however, that any number of controllers may interface with components of magnetic field measurement system800as may suit a particular implementation.

As shown, controller804may be communicatively coupled to each of magnetometers806and magnetic field generator808. For example,FIG. 8shows that controller804is communicatively coupled to magnetometer806-1by way of communication link810-1, to magnetometer806-2by way of communication link810-2, to magnetometer806-N by way of communication link810-N, and to magnetic field generator808by way of communication link812. In this configuration, controller804may interface with magnetometers806by way of communication links810-1through810-N (collectively “communication links810”) and with magnetic field generator808by way of communication link812.

Communication links810and communication link812may be implemented by any suitable wired connection as may serve a particular implementation. For example, communication links810may be implemented by one or more twisted pair cables while communication link812may be implemented by one or more coaxial cables. Alternatively, communication links810and communication link812may both be implemented by one or more twisted pair cables. In some examples, the twisted pair cables may be unshielded.

Controller804may be implemented in any suitable manner. For example, controller804may be implemented by a field-programmable gate array (FPGA), an application specific integrated circuit (ASIC), a digital signal processor (DSP), a microcontroller, and/or other suitable circuit together with various control circuitry.

In some examples, controller804is implemented on one or more printed circuit boards (PCBs) included in a single housing. In cases where controller804is implemented on a PCB, the PCB may include various connection interfaces configured to facilitate communication links810and812. For example, the PCB may include one or more twisted pair cable connection interfaces to which one or more twisted pair cables may be connected (e.g., plugged into) and/or one or more coaxial cable connection interfaces to which one or more coaxial cables may be connected (e.g., plugged into).

In some examples, controller804may be implemented by or within a computing device.

In some examples, a wearable magnetic field measurement system may include a plurality of optically pumped magnetometer (OPM) modular assemblies, which OPM modular assemblies are enclosed within a housing sized to fit into a headgear (e.g., brain interface system102) for placement on a head of a user (e.g., human subject). The OPM modular assembly is designed to enclose the elements of the OPM optics, vapor cell, and detectors in a compact arrangement that can be positioned close to the head of the human subject. The headgear may include an adjustment mechanism used for adjusting the headgear to conform with the human subject's head. These exemplary OPM modular assemblies and systems are described in more detail in U.S. Provisional Patent Application No. 63/170,892, previously incorporated by reference in its entirety.

In some examples, one or more components of brain interface system102(e.g., one or more computing devices) may be configured to be located off the head of the user.

Extended reality system104(FIG. 1andFIG. 9) may be implemented by any suitable system configured to worn by a user and provide the user with an extended reality experience. As used herein, extended reality system104may provide a user with an extended reality experience by providing an immersive virtual reality experience, a non-immersive augmented reality experience, and/or any combination of these types of experiences.

While providing an extended reality experience to a user, extended reality system104may present extended reality content to the user. Extended reality content may refer to virtual reality content and/or augmented reality content. Virtual reality content may be completely immersible such that no real-world content is visually presented to the user while the virtual reality content is presented to the user. Augmented reality content adds digital elements to a live view of the user.

FIG. 9shows exemplary components of extended reality system104. As shown, extended reality system104may include memory902, a processor904, a headset906, and a user input device908. Extended reality system104may include additional or alternative components as may serve a particular implementation. Each component may be implemented by any suitable combination of hardware and/or software.

Memory902may be configured to maintain application data910representative of one or more applications that may be executed by processor904. In some examples, an application represented by application data910may be configured to cause extended reality system104to present audio and/or visual stimuli to the user as part of a neuroscience analysis study or experiment. For example, the audio and/or visual stimuli may be configured to produce robust hemodynamic responses within the brain of a user.

Processor904may be configured to perform various operations associated with presenting extended reality content to the user and detecting various events while the user experiences the extended reality content. For example, processor904may track a user's eyes while the user experiences the extended reality content, detect user input provided by the user by way of user input device908, and log events (e.g., by generating timestamp data indicating when certain types of user input are provided by the user and/or when the user performs various actions).

Headset906may be implemented by one or more head-mounted display screens and/or other components configured to be worn on the head (e.g., such that the display screens are viewable by the user).

User input device908may be implemented by one or more components configured to facilitate user input by the user while the user experiences the extended reality content. For example, user input device908may be implemented by one or more joysticks, buttons, and/or other mechanical implementations. Additionally or alternatively, user input device908may be implemented by gaze tracking hardware and/or software configured to detect user input provided by a gaze of the user (e.g., by the user fixating his or her view on a particular option presented within the extended reality content). Additionally or alternatively, user input device908may be implemented by any other combination of hardware and/or software as may serve a particular implementation.

Returning toFIG. 1, communication link106may be implemented by any suitable wired and/or wireless link configured to facilitate transfer of data and/or signals between brain interface system102and extended reality system104. Such communication may include transmission of commands from brain interface system102to extended reality system104, transmission of synchronization data from extended reality system104to brain interface system102, and/or any other transmission of data and/or signals between brain interface system102and extended reality system104.

In some examples, communication link106is bidirectional, as shown inFIG. 1. In other examples, communication link106is unidirectional. For example, communication link106may only allow one or more signals to be transmitted from extended reality system104to brain interface system102.

To illustrate, communication link106may be implemented by an output audio port included within extended reality system104. In this configuration, extended reality system104may output an audio signal by way of the output audio port, which may be transmitted to brain interfaced system102by way of a cable, for example, that plugs into the output audio port.

FIG. 10show an exemplary implementation1000of system100(FIG. 1) in use by a user1002. As shown, user1002is wearing a headgear1004that implements brain interface system102and a headset1006that implements extended reality system104. In implementation1000, headset1006is a virtual reality headset that provides an immersive virtual reality experience for user1002. As shown, user1002is holding a joystick1008that implements user input device908(FIG. 9).

FIG. 11shows an exemplary configuration1100in which a remote neuroscience analysis management system1102(“system1102”) may be used to remotely control a neuroscience experiment performed using brain interface system102and extended reality system104. Configuration1100may be used to remotely control a neuroscience experiment performed on multiple users located in different locations (e.g., in their homes, in their classroom, in separate laboratories, in laboratories located in various locations, etc.). In some examples, configuration1100may also be used by subjects/patients who normally cannot be confined in a hospital environment due to limiting health or mobility concerns.

As shown, system1102is connected to brain interface system102and extended reality system104by way of a network1104(e.g., the Internet or any other suitable network). Alternatively, system1102may be connected to only one of brain interface system102or extended reality system104.

System1102may be used to remotely control a neuroscience experiment performed using brain interface system102and extended reality system104. For example, system1102may transmit experiment data to brain interface system102and/or extended reality system104, where the experiment data is representative of a particular experiment that is to be performed using brain interface system102and extended reality system104. System1102may be further configured to receive results data from brain interface system102and/or extended reality system104, where the results data is representative of one or more results of the particular experiment.

To illustrate, system1102(or any other system configured to control brain interface system102and extended reality system104) may be configured to transmit a first command to extended reality system104for extended reality system104to provide the user with an extended reality experience. System1102may be further configured to transmit a second command to brain interface system102for brain interface system102to acquire one or more brain activity measurements while the extended reality experience is being provided to the user. System1102may be further configured to receive, from brain interface system102, measurement data representative of the one or more brain activity measurements and perform an operation based on the measurement data. The operation may be any of the operations described herein.

In some examples, it may be desirable to synchronize brain activity measurements acquired by brain interface system102with events that occur within the extended reality experience provided to the user by extended reality system104(referred to herein as extended reality events). However, in some configurations, brain interface system102does not have access to an internal clock used by extended reality system104. For example, in an off-the-shelf implementation of extended reality system104(i.e., an implementation that is not specifically customized to integrate with brain interface system102), extended reality system104may not be configured to output an externally-available clock signal.

However, extended reality system104may, in some examples, be configured to output one or more signals that are not representative of an internal clock used by extended reality system104. For example, extended reality system104may be configured to output (by way of a wired communication link and/or a wireless communication link) an audio signal representative of audio used in or otherwise associated with an extended reality experience being provided to a user. This audio signal may be output, for example, by way of an output audio port included in extended reality system104. Additionally or alternatively, extended reality system104may be configured to output an electrical signal, an optical signal, and/or any other type of signal that may be accessed by components external to extended reality system104. In any of these configurations, brain interface system102may be configured to access the signal and use the signal to generate and output data that may be temporally synchronized with data output by extended reality system104. Because the signal may be used for synchronization purposes, it will be referred to herein generally as a “timing signal.”

To illustrate,FIG. 12shows an exemplary configuration1200in which extended reality system104is configured to output a timing signal that may be used to synchronize data output by extended reality system104and data output by brain interface system102. In configuration1200, the timing signal may be an audio signal, an optical signal, an electrical signal, and/or any other type of signal that may be used for synchronization purposes.

For illustrative purposes, it will be assumed herein that the timing signal output by extended reality system104is an audio signal. The audio signal may be audible or inaudible to the user as may serve a particular implementation. An inaudible timing signal, for example, may be in a frequency band that is not in the user's range of hearing.

In some example, characteristics of the audio signal may be specified by application data910, and may therefore be adjusted or otherwise programmed as needed by an external entity (e.g., remote neuroscience analysis management system1102). For example, a characteristic of the audio signal may be configured to modulate between two states or values such that the audio signal represents a plurality of timing events that occur during the extended reality experience that is provided to the user.

To illustrate,FIG. 13shows an exemplary timing signal1300that may be output by extended reality system104. As shown, timing signal1300is configured to periodically change between a low level and a high level. Each change indicates a beginning of a new timing event. For example, as shown, timing signal1300may initially be at a low level, which corresponds to a timing event labeled TE0. Timing signal1300then changes to a high level, at which point a new timing event labeled TE1begins. Timing signal1300continues to modulate between the low and high levels to create timing events TE2through TE8.

The levels shown inFIG. 13may be representative of any characteristic of timing signal1300. For example, the levels shown inFIG. 13may be volume levels (e.g., first and second volume levels). Other characteristics (e.g., frequency, amplitude, etc.) of the timing signal1300may be modulated to indicate timing events as may serve a particular implementation.

The timing signal output by extended reality system104may be analog or digital as may serve a particular implementation. For example, if the timing signal is an analog audio signal, the audio signal may be output by way of an output audio port and transmitted to brain interface system102by way of a cable that is plugged into the output audio port. Brain interface system102may include a digitizer (e.g., an analog-to-digital converter) configured to convert the analog audio signal into a digital audio signal that switches between different values.

By providing the timing signal from extended reality system104to brain interface system102, both extended reality system104and brain interface system102may have access to a signal that coveys the same timing information. As such, brain interface system102and extended reality system104may both use the same timing information to output different types of timestamp data.

To illustrate, as shown inFIG. 12, brain interface system102may acquire brain activity measurements while the extended reality experience is being provided to the user and output measurement timestamp data representative of a temporal association of the brain activity measurements with the timing events represented by the timing signal. For example, brain interface system102may determine that a particular brain activity measurement is acquired during a particular timing event represented by the timing signal and include, in the measurement timestamp data, data indicating that the particular brain activity measurement is acquired during the particular timing event.

Likewise, as shown inFIG. 12, extended reality system104may output extended reality event timestamp data representative of a temporal association of extended reality events with the timing events. For example, extended reality system104may determine that a particular extended reality event occurs during a particular timing event represented by the timing signal and include, in the extended reality event timestamp data, data indicating that the particular extended reality event occurs during the particular timing event.

As used herein, an “extended reality event” may include a user input event provided by the user (e.g., a user input received by way of user input device908), an occurrence a visual event within the extended reality experience (e.g., a display of a particular object within the extended reality experience), an occurrence of an audio event within the extended reality experience (e.g., a playing of a particular sound within the extended reality experience), and/or any other event associated with the extended reality experience.

As both the measurement timestamp data and the extended reality event timestamp data are generated using the same timing signal, they may be synchronized in any suitable manner. For example, as shown inFIG. 12, a processing system1202may be configured to receive both the measurement timestamp data and the extended reality event timestamp data and output, based on both datasets, synchronized data. The synchronized data may represent a time-synchronized version of the measurement timestamp data and the extended reality event timestamp data. Such synchronization may be performed in any suitable manner, such as by determining a timing offset that may need to be applied to the measurement timestamp data such that it is correlated properly with the extended reality event timestamp data.

FIG. 14shows an exemplary synchronization process performed by processing system1202. The synchronization process is represented inFIG. 14by arrow1400.

InFIG. 14, table1402represents measurement timestamp data generated by brain interface system102. As shown, the measurement timestamp data includes data representative of a plurality of brain activity measurements (BAM1through BAM4) and an indication as to when each brain activity measurement is acquired with respect to the timing events of timing signal1300. For example, table1402shows that brain activity measurement BAM1is acquired during timing event TE0, brain activity measurement BAM2is acquired during timing event TE1, brain activity measurement BAM3is acquired during timing event TE4, and brain activity measurement BAM4is acquired during timing event TE6.

Table1404represents extended reality event timestamp data generated by extended reality system104. As shown, the extended reality event timestamp data includes data representative of a plurality of extended reality events (ERE1through ERE9) an indication as to when each extended reality event occurs with respect to the timing events of timing signal1300. For example, table1404shows that extended reality event ERE1occurs during timing event TE0, extended reality event ERE2occurs during timing event TE1, etc.

Processing system1202may synchronize the measurement timestamp data with the extended reality event timestamp data by generating synchronized data, which is represented inFIG. 14by table1406. As shown, the synchronized data may represent a temporal correlation between the brain activity measurements represented by the measurement timestamp data and the extended reality events represented by the extended reality event timestamp data. For example, table1406shows that brain activity measurement BAM1is temporally correlated with extended reality event ERE1, brain activity measurement BAM2is temporally correlated with extended reality event ERE2, brain activity measurement BAM3is temporally correlated with extended reality event ERE5, and brain activity measurement BAM4is temporally correlated with extended reality event ERE7. As mentioned, in some examples, a temporal offset (e.g., one or more timing events) may, in some examples, be applied to the measurement timestamp data and/or the extended reality event timestamp data as may serve a particular implementation to ensure that the brain activity measurements are properly correlated with the extended reality events.

In some examples, processing system1202may synchronize the measurement timestamp data and the extended reality event timestamp data in substantially real time while the extended reality experience is being provided to the user. Additionally or alternatively, processing system1202may synchronize the measurement timestamp data and the extended reality event timestamp data offline (e.g., after the extended reality experience has concluded).

Processing system1202may be implemented by any suitable combination of one or more computing devices. Processing system1202may be separate from brain interface system102and extended reality system104, as shown inFIG. 12. Alternatively, processing system1202may be included in brain interface system102or extended reality system104.

In some examples, processing system1202may be configured to perform an operation based on the synchronized data. For example, processing system1202may present graphical content showing different regions of the brain that are activated in response to an occurrence of various extended reality events, process the synchronized data to output neuroscience experimental results, provide one or more recommendations for the user, control the extended reality experience that is being provided to the user, etc.

To illustrate,FIG. 15shows an exemplary configuration1500in which processing system1202is configured to control a parameter of the extended reality experience that is being provided by extended reality system104based on the measurement timestamp data (and/or the synchronized data). As shown, processing system1202may control the parameter of the extended reality experience by transmitting control data to extended reality system104. The control data is configured to control the parameter of the extended reality experience in any suitable manner. For example, the control data may cause a particular visual and/or audio cue to be provided to the user, adjust a difficulty level of a task that is to be performed within the extended reality experience, and/or otherwise adjust the extended reality experience.

Configuration1500may be used, for example, in a training and/or learning environment. For example, extended reality system104may present an extended reality experience to the user in which the user is to be taught how to perform a particular task. As the user is provided instructions related to the task within the extended reality experience, brain interface system102is configured to acquire brain activity measurements. Such brain activity measurements may, in some examples, be time-synchronized with events that occur within the extended reality experience, as described herein.

Processing system1202may be configured to use the brain activity measurements to monitor a brain state of the user during the extended reality experience. The brain state may indicate whether the user is sufficiently understanding the instructions, be indicative of a mood and/or fatigue level of the user, and/or be indicative of any other brain-related characteristic of the user.

Based on the brain state, processing system1202may generate control data configured to adjust one or more parameters of the extended reality experience. For example, if the brain state indicates that the user is easily understanding the instructions, the control data may be configured to cause additional instructions to be presented within the extended reality experience. Alternatively, if the brain state indicates that the user is having difficulty understanding the instructions, the control data may be configured to cause the same instructions to be repeated and/or explained in a different manner.

In some examples, data representative of and/or associated with neuroscience experiments may be distributed through a centralized platform (e.g., an app store). For example, a study designer may upload an app that users can download and use to either contribute to a larger study (e.g., a distributed neuroscience experiment) or to use to gain some insight about themselves (e.g., a cognition training app).

In some examples, the configurations described herein may provide delivery of insights based on the extended reality environment. For example, brain activity may be visualized in 3D and presented during and/or after the extended reality experience. The visualization could be an interactive and/or exploratory interface for looking at different angles of a 3D brain or zooming in on particular regions of interest. It could also show overlays of some kind of condensed score based on neural activity that shows what a user's brain was doing while the user was interacting in the extended reality experience.

In some examples, the configurations described herein may facilitate a first user viewing a second user's brain activity in virtual reality while the second person is wearing a brain interface system. For example, a medical professional may desire to see real-time responses of a patient's brain activity. The medical professional may accordingly wear the extended reality system while the patient wears the brain interface system. The medical professional may thereby see brain activation within the patient. This configuration could also be used in other situations. For example, two users could both wear a combination of a brain interface system with an extended reality system. Information about the users' brain as determined by the brain interface systems could be shared (e.g., in real-time) between the extended reality systems being worn by the two users such that the two users are aware of what is going on in each other's brains while they talk or otherwise interact.

In some examples, adaptation of an extended reality experience based on brain state may be performed in real-time and/or offline (e.g., for developer tuning of the extended reality experience). Such adaption could be based on the detected brain activity of the user. The measured brain activity could be related to physiological brain states and/or mental brain states, e.g., joy, excitement, relaxation, surprise, fear, stress, anxiety, sadness, anger, disgust, contempt, contentment, calmness, approval, focus, attention, creativity, cognitive assessment, positive or negative reflections/attitude on experiences or the use of objects, etc. Further details on the methods and systems related to a predicted brain state, behavior, preferences, or attitude of the user, and the creation, training, and use of neuromes can be found in U.S. patent application Ser. No. 17/188,298, filed Mar. 1, 2021. Exemplary measurement systems and methods using biofeedback for awareness and modulation of mental state are described in more detail in U.S. patent application Ser. No. 16/364,338, filed Mar. 26, 2019, issued as U.S. Pat. No. 11,006,876. Exemplary measurement systems and methods used for detecting and modulating the mental state of a user using entertainment selections, e.g., music, film/video, are described in more detail in U.S. patent application Ser. No. 16/835,972, filed Mar. 31, 2020, issued as U.S. Pat. No. 11,006,878. Exemplary measurement systems and methods used for detecting and modulating the mental state of a user using product formulation from, e.g., beverages, food, selective food/drink ingredients, fragrances, and assessment based on product-elicited brain state measurements are described in more detail in U.S. patent application Ser. No. 16/853,614, filed Apr. 20, 2020, published as US2020/0337624A1. Exemplary measurement systems and methods used for detecting and modulating the mental state of a user through awareness of priming effects are described in more detail in U.S. patent application Ser. No. 16/885,596, filed May 28, 2020, published as US2020/0390358A1. These applications and corresponding U.S. publications are incorporated herein by reference in their entirety.

In some examples, a common platform may be used to effectuate various neuroscience experiments. For example, a model may include a standard brain imaging device used in the various experiments (e.g., an optical measurement system as described herein). The extended reality systems described herein may provide a controlled environment and standardized platform for providing stimuli used in the experiments. In some examples, the platform may allow various entities to contribute task “apps” to a public database that anyone can access. Any apps in the public repository would be tagged according to standard event configurations and may be used to contribute to larger studies. Any entity may analyze data that is voluntarily provided by participants/users of the standard brain imaging device. Insights may be generated combining the data collected from users that participated in the public repository experiments and other data sources (e.g., sleep trackers, health and fitness trackers, etc.).

FIG. 16illustrates an exemplary method1600that may be performed by a computing device (e.g., a computing device included in remote neuroscience analysis management system1102). WhileFIG. 16illustrates exemplary operations according to one embodiment, other embodiments may omit, add to, reorder, and/or modify any of the operations shown inFIG. 16. The operations shown inFIG. 16may be performed in any of the ways described herein.

At operation1602, a computing device transmits a first command, to an extended reality system configured to be worn by a user, for the extended reality system to provide the user with an extended reality experience.

At operation1604, the computing device transmits a second command, to a brain interface system configured to be worn concurrently with the extended reality system, for the brain interface system to acquire one or more brain activity measurements while the extended reality experience is being provided to the user.

At operation1606, the computing device receives, from the brain interface system, measurement data representative of the one or more brain activity measurements.

At operation1608, the computing device performs an operation based on the measurement data. The operation may include, for example, analyzing the data based on an experiment's objective, e.g., assessment of a user's cognitive performance, assessment of a user's positive or negative reflections/attitude on experiences or the use of objects, assessment of a user's positive or negative reflections/attitude on experiences with food, beverages, drugs, music, sounds, video, etc.

FIG. 17illustrates an exemplary method1700that may be performed by any of the brain interface systems described herein. WhileFIG. 17illustrates exemplary operations according to one embodiment, other embodiments may omit, add to, reorder, and/or modify any of the operations shown inFIG. 17. The operations shown inFIG. 17may be performed in any of the ways described herein.

At operation1702, a brain interface system receives a timing signal from an extended reality system while the extended reality system provides an extended reality experience to the user, the timing signal representing a plurality of timing events that occur during the extended reality experience.

At operation1704, the brain interface system acquires brain activity measurements while the extended reality experience is being provided to the user.

At operation1706, the brain interface system outputs measurement timestamp data representative of a temporal association of the brain activity measurements with the timing events.

FIG. 18illustrates an exemplary method1800that may be performed by any of the processing systems described herein. WhileFIG. 18illustrates exemplary operations according to one embodiment, other embodiments may omit, add to, reorder, and/or modify any of the operations shown inFIG. 18. The operations shown inFIG. 18may be performed in any of the ways described herein.

At operation1802, a processing system receives measurement timestamp data from a brain interface system configured to be worn by a user, the measurement timestamp data representative of a temporal association of brain activity measurements with timing events represented by a timing signal, the timing signal output by an extended reality system configured to be worn by the user concurrently with the brain interface system.

At operation1804, the processing system receives extended reality event timestamp data from the extended reality system, the extended reality event timestamp data representative of a temporal association of extended reality events with the timing events, the extended reality events occurring while the extended reality experience is being provided to the user.

At operation1806, the processing system synchronizes the measurement timestamp data with the extended reality event timestamp data.

At operation1808, the processing system performs an operation based on the synchronizing.

In some examples, a non-transitory computer-readable medium storing computer-readable instructions may be provided in accordance with the principles described herein. The instructions, when executed by a processor of a computing device, may direct the processor and/or computing device to perform one or more operations, including one or more of the operations described herein. Such instructions may be stored and/or transmitted using any of a variety of known computer-readable media.

A non-transitory computer-readable medium as referred to herein may include any non-transitory storage medium that participates in providing data (e.g., instructions) that may be read and/or executed by a computing device (e.g., by a processor of a computing device). For example, a non-transitory computer-readable medium may include, but is not limited to, any combination of non-volatile storage media and/or volatile storage media. Exemplary non-volatile storage media include, but are not limited to, read-only memory, flash memory, a solid-state drive, a magnetic storage device (e.g. a hard disk, a floppy disk, magnetic tape, etc.), ferroelectric random-access memory (“RAM”), and an optical disc (e.g., a compact disc, a digital video disc, a Blu-ray disc, etc.). Exemplary volatile storage media include, but are not limited to, RAM (e.g., dynamic RAM).

FIG. 19illustrates an exemplary computing device1900that may be specifically configured to perform one or more of the processes described herein. Any of the systems, units, computing devices, and/or other components described herein may be implemented by computing device1900.

As shown inFIG. 19, computing device1900may include a communication interface1902, a processor1904, a storage device1906, and an input/output (“I/O”) module1908communicatively connected one to another via a communication infrastructure1910. While an exemplary computing device1900is shown inFIG. 19, the components illustrated inFIG. 19are not intended to be limiting. Additional or alternative components may be used in other embodiments. Components of computing device1900shown inFIG. 19will now be described in additional detail.

Communication interface1902may be configured to communicate with one or more computing devices. Examples of communication interface1902include, without limitation, a wired network interface (such as a network interface card), a wireless network interface (such as a wireless network interface card), a modem, an audio/video connection, and any other suitable interface.

Processor1904generally represents any type or form of processing unit capable of processing data and/or interpreting, executing, and/or directing execution of one or more of the instructions, processes, and/or operations described herein. Processor1904may perform operations by executing computer-executable instructions1912(e.g., an application, software, code, and/or other executable data instance) stored in storage device1906.

Storage device1906may include one or more data storage media, devices, or configurations and may employ any type, form, and combination of data storage media and/or device. For example, storage device1906may include, but is not limited to, any combination of the non-volatile media and/or volatile media described herein. Electronic data, including data described herein, may be temporarily and/or permanently stored in storage device1906. For example, data representative of computer-executable instructions1912configured to direct processor1904to perform any of the operations described herein may be stored within storage device1906. In some examples, data may be arranged in one or more databases residing within storage device1906.

I/O module1908may include one or more I/O modules configured to receive user input and provide user output. I/O module1908may include any hardware, firmware, software, or combination thereof supportive of input and output capabilities. For example, I/O module1908may include hardware and/or software for capturing user input, including, but not limited to, a keyboard or keypad, a touchscreen component (e.g., touchscreen display), a receiver (e.g., a radio frequency or infrared receiver), motion sensors, and/or one or more input buttons.