Temporomandibular joint sensing system and methods

Abstract

The invention described herein is directed to Temporomandibular Joint (TMJ) Sensing Systems and methods of use. Specifically, a TMJ Sensing System that is capable of detecting various outputs from the TMJ joint. The system and methods described herein can be used to detect, diagnosis and treat a variety of physical and mental diseases. The TMJ Sensing System can be used to communicate and / or operate external devices.

Description

TEMPOROMANDIBULAR JOINT SENSING SYSTEM AND METHODSCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application is being filed on November 13, 2024 as a PCT Patent International Application and claims priority to and the benefit of United States Provisional Patent Application No. 63 / 598329, filed on November 13, 2023 and United States Provisional Patent Application No 63 / 571,615, filed on March 29, 2024, the entire contents of each of which are incorporated by reference herein.FIELD OF THE INVENTION

[0002] This application relates to the fields of Temporomandibular Joint (TMJ) Sensing System. Specifically, a TMJ Sensing System that is capable of detecting various outputs from the TMJ joint. The system and methods described herein can be used to detect, diagnosis and treat a variety of physical and mental diseases. The TMJ Sensing System can be used to communicate and / or operate external devices.BACKGROUND OF THE INVENTION

[0003] Wearable devices such as wristwatch devices and ear buds can provide enhanced freedom of movement. For example, wireless ear buds can be used to play audio content for a user of an electronic device such as a cellular telephone or computer without cumbersome cables.

[0004] Other type of external devices, such as U.S. Pat. No. 6,446,742 Bi a motor-driven platform vehicle for physically disabled people is known, in which the person can move around motor-driven standing on a platform. However, it is a disadvantage of this vehicle, that like with common wheelchairs, the user can enter the vehicle only with difficulties and that it is very space consuming since it is designed for the outdoor use. Therefore, the device has limited use for operating conveniently throughout the day. This is particularly true as a user desires to operate throughout the day without needing to disengage from the motor-driven platform. Thus, a convenient system that can operate devices without being bulky or cumbersome to operate is needed.

[0005] US 10,285,636 is directed to an apparatus and method of detecting bruxism.The method includes the steps of: capturing a video of a subject, performing by circuitry included in the apparatus, spatial filtering of each image frame included in the captured video.Further, the method includes generating by circuitry, a filtered image by temporally filtering the spatially filtered image frames, the temporally filtered image including data belonging in a first frequency range, and wherein a subset of data is associated with a predetermined color variation to indicate presence of bruxism in the subject. However, this device is large and would be challenging to wear beyond simple diagnosis. Thus, there is a need for a device that can be worn in a discreet manner that can help reduce bruxism in a patient.

[0006] SUMMARY OF THE INVENTION

[0007] The temporomandibular joint (TMJ) is located between the mandible (also referred to as the jaw) and the temporal bones of the skull. It is the most active joint in the body. There are three main components of the joint, the mandibular condyle (superior aspect of the mandibular bone), the mandibular fossa (a concave aspect of the temporal bone) and the articular disk which lies between the mandibular condyle and mandibular fossa. The joint lies anterior to the outer ear canal. Mandibular condyle movement is a surrogate for detecting mandible movement. It slides and rotates in during mastication. Changes in the mandibular condyle’s position correlate to the following mandibular movements: mandibular depression, elevation, lateral deviation (both the right and left), retrusion and protrusion.

[0008] The TMJ sensing system may be positioned completely in the ear canal and store mandibular condyle movement information that is downloaded onto a computer or smart device for analysis. The TMJ sensing system may have an inner ear canal component and an external component. The inner ear component may transmit movement information to the external device. The external device may be a smart device (i.e., smart phone or tablet) or a computer. Bluetooth technology may be used to send information from the inner ear device to the external device. The external device may have an app to display mandibular condyle movement information and analytics, which may or may not include artificial intelligence (Al) and / or machine learning, used to determine the behavior of the mandible such as different types of mastication activity, disease states or behavior.

[0009] BRIEF DESCRIPTION OF DRAWINGS

[0010] FIG. 1 is an illustration of the skull and external view of the TMJ.

[0011] FIG. 2 is an illustration of the anatomy of the TMJ and location relative to the ear canal.

[0012] FIG. 3 is an illustration of TMJ anatomical movements.

[0013] FIG. 4 is an illustration of one example embodiment of a TMJ sensing system.

[0014] FIG. 5 is an illustration of one example embodiment of a TMJ sensing system.

[0015] FIG. 6 is a graphical illustration of mastication episodes.

[0016] FIG. 7 is a graphical illustration of the components of a mastication episode.

[0017] FIG. 8 is a graphical illustration of bite amplitude when comparing soft and hard food.

[0018] FIG. 9 is a graphical illustration of chewing amplitude when comparing soft and hard food.

[0019] FIG. 10 is a graphical illustration of differences in swallowing amplitude that occurs following chewing events and may differ between food consistencies, d.

[0020] FIG. 11 is a graphical illustration of bite rise and decay kinetics when comparing what type of food is being consumed.

[0021] FIG. 12 is a graphical illustration of chewing rise and decay kinetics when comparing what type of food is being consumed.

[0022] FIG. 13 is a graphical illustration of swallowing rise and decay kinetics when comparing what type of food is being consumed.

[0023] FIG. 14 is a graphical illustration of mastication episode frequency.

[0024] FIG. 15 is a graphical illustration of an eating episode.

[0025] FIG. 16 is a graphical illustration comparing ingestion of liquid and solids.

[0026] FIG. 17 is a graphical illustration comparing ingestion of liquid and solids.

[0027] FIG. 18 is a graphical illustration comparing ingestion of multiple liquid drinks.

[0028] FIG. 19 is an illustration indicating methods of use for TMJ sensing system for weight loss management.

[0029] FIG. 20 is process flow of potential collaborative technologies that can be used with TMJ sensing system.

[0030] FIG. 21 A is a graphical illustration comparing right and left lateral deviation in TMJ patterns.

[0031] FIG. 21B is a graphical illustration comparing right and left mandibular elevation in TMJ patterns.

[0032] FIG. 22 is a graphical illustration of TMJ force movements associated with snoring: A) Sensor detecting snoring by increased breathing magnitude, B) Detecting snoring by increased breathing magnitude and C) Sensor detecting snoring by increased breathing magnitude and softpalate vibrations.

[0033] FIG. 23Ais a graphical illustration of TMJ sensing system to determine obstructive sleep apnea (OSA) events.

[0034] FIG. 23B is a graphical illustration of TMJ sensing system to determine obstructive sleep apnea (OSA) events.

[0035] FIG. 23C is a graphical illustration of TMJ sensing system to determine obstructive sleep apnea (OSA) events.

[0036] FIG. 24A is a graphical illustration of TMJ sensing system used to predict and measure smoking behavior.

[0037] FIG. 24B is a graphical illustration of TMJ sensing system used to predict and measure smoking behavior with the absence of elevation forces.

[0038] FIG. 25Ais a graphical illustration of TMJ sensing system used to control devices such as a cursor on screen.

[0039] FIG. 25B is a graphical illustration of TMJ sensing system used to control devices such as a cursor on screen.

[0040] FIG. 25C is a graphical illustration of TMJ sensing system used to control devices such as a cursor on screen.

[0041] FIG. 25D is a graphical illustration of TMJ sensing system used to control devices such as a cursor on screen using quick series mandibular movements.

[0042] FIG. 26A is a graphical illustration of TMJ sensing system used to control devices with binary control.

[0043] FIG. 26B is a graphical illustration of TMJ sensing system used to control devices with binary control.

[0044] FIG. 27A is an illustration of TMJ sensing system including a force transducer.

[0045] FIG. 27B is an illustration of TMJ sensing system in a subject monitoring changes in force over time during mandibular movements on a computer screen.

[0046] FIG. 28A is a graphical illustration of clenching, swallowing, vertical movement, horizontal movement, and chewing activities using the TMJ sensing system.

[0047] FIG. 28B is a graphical illustration of protrusion, retrusion, smoking, and speaking activities using the TMJ sensing system.

[0048] FIG. 29 is a graphical illustration of TMJ sensing system performing navigational controlusing two TMJ sensing system.DEFINITIONS

[0049] Artificial intelligence (Al) is defined as a concept that encompasses many different approaches and algorithms making machines more human-like, such as through reasoning, sensing, acting, or adapting.

[0050] Bite amplitude is defined as the force required to bite an object.

[0051] Bite rise is defined as the slope of the force versus time between the start of the negative force of the condyle depression to the peak force of the condyle elevation or in some cases the start of the neutral force to the peak force of the condyle elevation during s bite event.

[0052] Chewing amplitude is defined as the force required to chew a particular foodstuff.

[0053] Chewing rise is defined as the slope of the force versus time between the start of the condyle depression to the peak of the condyle elevation during a chewing event.

[0054] Eating episode is defined as eating, in a discrete period of time.

[0055] Machine Learning (ML) is defined as a subset of Al that uses algorithms and statistical models to teach machines how to perform specific tasks by identifying patterns in data.

[0056] Mastication episode is defined as the process of breaking down food into smaller particles with the use of teeth and jaw muscles.

[0057] Swallowing amplitude is defined as force required to swallow a particular foodstuff or beverage.

[0058] Swallowing rise is defined as is the slope of the force versus time between the neutral condyle force and the peak of the condyle force during a swallowing event.

[0059] Telemedicine is defined as remote diagnosis and treatment of patients by means of telecommunications technology.DETAILED DESCRIPTION

[0060] Referring now to Fig. 1, where the temporomandibular joint (TMJ) is located between the mandible (also referred to as the jaw) of the skull 5, and the temporal bones of the skull (10). It is the most active joint in the body. There are three main components of the joint, the mandibular condyle 14 (superior aspect of the mandibular bone), the mandibular fossa 11 (a concave aspect of the temporal bone) and the articular disk 12 which lies between the mandibular condyle 14 and mandibular fossa 11 (see FIG. 2). Referring still to Fig. 2, the joint lies anterior to the outer ear canal (16). Mandibular condyle 14 movement is a surrogate fordetecting mandible movement. It slides and rotates in during mastication. Referring now to Fig. 3, which depicts changes in the mandibular condyle’s position correlate to the following mandibular movements: mandibular 17, depression 19, elevation 18, lateral deviation (both the right 20 and left 22), retrusion 24 and protrusion 26.

[0061] The electronic device (29), housing the device sensor, may be positioned completely in the ear canal and store mandibular condyle movement information that is downloaded onto a computer or smart device for analysis. The electronic device (29) may have an inner ear canal component and an external component. The inner ear component may transmit movement information to the external device. The external device may be a smart device (i.e., smart phone or tablet) or a computer. Bluetooth technology may be used to send information from the inner ear device to the external device. The external device may have an app to display mandibular condyle movement information and analytics, which may or may not include Al and / or machine learning (from an individual and / or population), used to determine the behavior of the mandible such as different types of mastication activity, disease states or behavior.

[0062] The mandibular condyle 14 distorts the anterior wall of the outer ear canal during mandibular movements. Referring to Figs. 4-5, where an electronic device 29 is shown in two embodiments. A mandibular condyle movement detection with the electronic device (29), housing a device sensor 30, can be placed into the outer ear canal to detect mandibular condyle movement that indirectly measures jaw movement during activities such as mastication. The TMJ is located in an easily accessible location for a movement detection device to be placed with the advantage of concealment in the outer ear canal to minimize device sensor visibility (or additional system functionality electronic component’s visibility) and to hold the device in position without sensor stabilization methodologies such as adhesives (as required with, for example EMG or ECG electrodes). Sliding of the device against the anterior aspect of the outer ear canal during mandibular condyle movements may create sound and a microphone may be the device sensor used to detect mandibular condyle movement. A strain gauge or force gauge may be the device sensor 30 used to detect movement of the mandibular condyle by measuring tensile (positive), torsion or compression (negative) stress forces exerted on it by the mandibular condyle. The sensor 30 could also comprise at least one fdament. The device sensor 30 may also consist of a force transducer. The sensor 30 may be a Hall-Effect sensor. The device sensor may be a piezoelectric sensor. The device sensor may be a capacitive sensor. Also, multiplesensors (microphone, strain gauge, force transducer, Hall-Effect sensor, and piezoelectric sensor) or any combination thereof may be utilized to measure movement of the mandibular condyle. The electronic device (29) tracking system can be integrated into existing systems that are positioned in the outer ear canal such as ear buds (FIG. 4) and hearing aid devices (FIG. 5) such as, but not limited to, behind-the-ear (BTE) 36, in-the-ear (ITE), receiver-in-the-ear (RITE), in- the-canal (ITC) or CROSZBiCROS configurations. The ear bud type design may have functional capability as a sound producing device and / or verbal communication device with a speaker and / or microphone (FIG. 4) and the hearing aid design may have functional capability to magnify and filter sound (FIG. 5). Still referring to Figs. 4-5 where external electronics (32) are shown. The electronics that are external may not be able to provide detailed analytics relating to the force of the TMJ, but can use other signals (light, sound, movement) to detect TMJ activity.

[0063] The electronic device (29), housing 28 the device sensor 30, may be positioned completely in the ear canal and store mandibular condyle movement information that is downloaded onto a computer or smart device for analysis. The electronic device (29) may have an inner ear canal component and an external component. The outer ear component may transmit movement information to the external device. The external device may be a smart device (i.e., smart phone or tablet) or a computer. Bluetooth technology may be used to send information from the inner ear device to the external device. The external device may have an app to display mandibular condyle movement information and analytics, which may or may not include Al and / or machine learning (from an individual and / or population), used to determine the behavior of the mandible such as different types of mastication activity or mandible position.

[0064] The electronic device (29) may need to be calibrated to the user’s mandibular movements. This may involve moving the mandible to different positions (mandibular depression, elevation, lateral deviation (both the right and left), retrusion and protrusion) and entering the position into a smart device. Mandible movement may be measured by optical means, for example a camera and / or LiDar on the smart device may also be utilized to detect jaw movements with or without a visual tracker (an example of a tracker may be a sticker) on the chin. The visual (or LiDar) analysis of the position of the jaw may be interpolated with information from the electronic device (29) to calibrate jaw position with forces at or around the TMJ. Optical measurements may detect changes in position of the device in the ear canal associated with TMJ movement. TMJ movement may also be tracked by means of a multi-axisaccelerometer or gyroscope. Electromyography (EMG) signals or electrical impedance changes detected within the ear canal associated with jaw movement may be used to determine jaw position. Force may be transduced and measured through a microfluidic system, hydraulic system or pneumatic systems.

[0065] The electronic device (29) may detect mastication of food which can be broken down into mastication episodes 59. A mastication episode is defined by multiple (2 or greater) chewing events (see FIG. 6). A chewing event 52 consists of a mandibular depression followed by a mandibular elevation. The mandibular depression 55 causes a decreased force exerted on the device sensor by the mandibular condyle. The mandibular elevation 50 causes an increased force exerted on the device sensor by mandibular condyle. Mastication episodes may be separated by inter-mastication episode delay 57(FIG. 6). The mastication episode duration is the length of time of the mastication episode. The chewing amplitude 51 is proportional to the degree of the positive force exerted on the device sensor by the mandibular condyle. The intra-chew duration 65 is the time from the start of the mandibular depression to the end of the mandibular elevation. If a mastication episode only consists of chewing events then the mastication episode duration is the same as the chewing duration 60 (FIG. 7). Chewing frequency = (number of chews in a mastication episode) / (chewing duration 60). Differences in the number of mastication episodes, the inter-mastication episode delay 83, the mastication episode duration 45, chewing amplitude, chewing duration 60 and chewing frequency may be correlated with different food consistency and food type. The system may learn, with or without Al and / or machine learning (from an individual and / or population), the correlation between mastication episodes, the inter-mastication episode delay 83, the mastication episode duration, chewing amplitude, chewing duration 60 and chewing frequency and food consistency and food type being consumed as well as predict negative feeding behavior associated with obesity and metabolic disorders (metabolic disorders include obesity, high blood pressure, dyslipidemia, type 2 diabetes and nonalcoholic steatohepatitis (NASH)).

[0066] A mastication episode may consist of a bite event preceding chewing events and a swallow event following the chewing events (FIG. 7). The bite event is the first change in force due to condyle elevation or depression during a mastication episode (FIG. 7). A bite duration is the time from the initial mandibular depression to the end of the peak of the mandibular elevation or if a negative force is not detected it is the duration of the positive force (FIG. 7). A bite isfollowed by chewing events (FIG. 7). Chewing events consists of mandibular depressions followed by mandibular elevations. The mandibular depression causes a decreased force exerted on the device sensor by mandibular condyle which may or may not be detected by the electronic device (29). The mandibular elevation causes an increased force exerted on the device sensor by mandibular condyle. The chewing amplitudes may decrease in amplitude during the chewing duration (FIG. 7). The rate of decrease in the amplitude of chewing events may differ by the consistency of the food being consumed. The swallowing event may cause an increased force exerted on the device sensor and is the swallowing amplitude (FIG. 7).

[0067] The bite amplitude 75 may change due to the consistency of the food being consumed (FIG. 8). Chewing amplitudes may differ due to the consistency of the food being consumed (FIG. 9). Swallowing amplitudes 72 may differ due to the consistency of the food being consumed (FIG. 10). The system may learn, with or without Al and / or machine learning (from an individual and / or population), the correlation between bite amplitude 75, chewing amplitude, rate of chewing amplitude decrease and swallowing amplitude and the food consistency and food type being consumed as well as predict negative feeding behavior associated with obesity and metabolic disorders. As shown in Fig. 9, the variety of food types being consumed can provide a delta between a harder food (left graphical data) and softer foods (right graphical data). This difference in bite amplitude 81, further discuses how the use of the machine described here can be used to assess real-time consumption, especially for the end user.

[0068] The kinetics of the condyle movement during the bite event are as follows. The rate of condyle elevation at the start of the bite event is the slope of the force versus time between the start of the negative force of the condyle depression to the peak force of the condyle elevation (FIG. 11) or in some cases the start of the neutral force to the peak force of the condyle elevation. The decay rate of condyle elevation at the end of the bite event is the slope of the force versus time between the peak of the condyle elevation to the end of the bite event (FIG. 11). The slope may be linear or non-linear. The kinetics of the bite event may differ with different food consistencies or food type. The system may learn, with or without Al and / or machine learning (from an individual and / or population), the correlation between the bite kinetics and food type being consumed as well as predict negative feeding behavior associated with obesity and metabolic disorders.

[0069] The kinetics of the condyle movement during chewing events are as follows. The rate ofcondyle depression at the start of the chew event is the slope of the force versus time between the start of the condyle depression to the peak of the condyle elevation (FIG. 12). The decay rate of condyle elevation at the end of the chew event is the slope of the force versus time between the peak of the condyle elevation to the end of the chew event (FIG. 12). The slope may be linear or non-linear. The kinetics of the chewing events may differ with different food consistencies and food types. The system may learn, with or without Al and / or machine learning (from an individual and / or population), the correlation between the chewing kinetics and food type being consumed and predict negative feeding behavior associated with obesity and metabolic disorders.

[0070] The kinetics of the condyle movement during swallowing event are as follows. The rate of the condyle elevation of the swallow event is the slope of the force versus time between the neutral condyle force and the peak of the condyle force (FIG. 13). The slope may be linear or non-linear. The decay rate of condyle elevation at the end of the swallow event is the slope of the force versus time between the peak of the condyle elevation to the end of the swallow event (FIG. 13). The slope may be linear or non-linear. The kinetics of the swallowing events may differ with different food consistencies, food types and if a liquid or solid is being consumed. The system may learn, with or without Al / or and machine learning, the correlation between the swallowing kinetics and food type being consumed or the difference between consumption of a solid or liquid as well as predict negative feeding behavior associated with obesity, dysplasia and metabolic disorders.

[0071] The system may track mastication episode frequency during a mastication event 90 (FIG. 14). A mastication event 90 is composed of multiple (greater than 1) spaced mastication episodes (FIG. 14). At least in this example embodiment, spacing of mastication episodes, or the inter-mastication episode delay 83 (FIG. 6), is about 0.1-5 seconds. A mastication event duration 85 is about 5 to 60 seconds. A skilled artisan should appreciate that the range of time is effected by a number of variable including user, foot type, etc. Mastication Episode Frequency = (l / (mastication episode duration 85 + inter-mastication episode delay 83)). It has been reported that faster mastication episode frequency and decreased number of chews is correlated with obesity (Okubo The Relationship of Eating Rate and Degree of Chewing to Body Weight Status among Preschool Children in Japan: A Nationwide Cross-Sectional Study, Nutrients. 2018 Dec 29; 11(1):64. doi: 10.3390 / nul 1010064.). Mastication episode frequency may differ between different food types. The system may learn, with or without Al and / or and machine learning, thecorrelation between mastication frequency and the food type being consumed as well as predict negative feeding behavior associated with obesity and metabolic disorders.

[0072] An eating episode 95 (FIG. 15) is composed of greater than 1 mastication event 90 and consists of a meal eating event (typically 10-30 min) or a snack eating event (typically less than 10 min). The system may leam, with or without Al and / or machine learning, the correlation between eating episode duration 100 and negative feeding behavior associated with obesity and metabolic disorders.

[0073] The system can detect and record temporal aspects of eating (or snacking) or mastication behaviors that include chewing rate (l / (intra-chew duration + inter-chew episode delay)), length of mastication episodes, rate of mastication episodes (1 / (mastication episode duration + intermastication episode delay 83)), mastication event duration 85, rate of mastication events 90(l / (mastication event duration + inter-mastication event delay 98)), number of eating episodes per day, time between eating episodes and the time of day of snacking or meal events and predict negative feeding behavior associated with obesity and metabolic disorders. As it relates to at least the aforementioned method of use, the prediction of behavior can be obtained with or without artificial intelligence (Al).

[0074] Patterns of the temporal and kinetic aspects of mastication described above may differ between the consistency of the food being consumed which may require mastication learning sessions to correlate mandibular condyle movement with food type and / or consistency.Examples of chewing various items are shown in FIG. 28a. Learning sessions may use Al and / or machine learning (from an individual and / or population). A user can input into a smart device app what food is being consumed (examples are, but not limited to fruit, vegetable, meat, fat, carbohydrate rich foods such as bread, rice and pasta) during mastication events for system learning. Learning may also include the time of day of eating episodes occur and patterns of the type of food being consumed during these eating episodes. An app can make correlations, with or without Al and / or machine learning (from an individual and / or population), with mastication behavior and health states of the subject such as, but not limited to, blood oxygen levels, heart rate, blood pressure, heart rhythm, sleep quality (such as, but not limited to amount of sleep, time spent in different sleep stages, snoring, obstructive sleep apnea, sleep bruxism and / or nasal versus mouth breathing or any combination thereof), physical activity, use of addictive drugs, severity of psychiatric disorders (in this patent psychiatric disorders can include, but not limitedto, depression, bipolar disorder, anxiety disorder, schizophrenia, psychosis and / or eating disorders), obesity or metabolic syndrome or any combination thereof.

[0075] There is a need for assessment of eating behaviors in persons with dementia (such as, but not limited to frontotemporal dementia and Alzheimer’s disease) (or predementia, or persons with high risk of dementia development (example age, genetics, family history and / or social isolation) to determine if, but not limited to, there is malnourishment and / or an unhealth loss of weight (Fostinelli 2020 Eating Behavior in Aging and Dementia: The Need for a Comprehensive Assessment). Changes in eating / mastication behaviors may also assess development of dementia, the stage of dementia, cognitive decline during dementia and the need for a caregiver. These assessments of eating / mastication behaviors may involve measuring changes in swallowing function, appetite, eating habits, food preference and food cramming. Changes in eating behavior may be detected by changes in the durations of mastication episodes or intermastication episodes delay 57 (FIG. 6), changes in number of mastication event 90 in an eating episode (FIG. 15), changes in the number of eating episodes (meals or snacking) throughout a day, changes in bite amplitude 75 (FIGs. 7-10), changes in chewing rate ((number of chews between a bite event and swallow event) / (chew duration), FIGs. 7-10)), changes in the kinetics (or rate) of chew amplitude decline in between a bite event and a swallow event (FIGs. 7-10), changes in bite rise and decay kinetics (FIG. 11), changes in chewing rise and decay kinetics (FIG. 12), changed in swallow rise and decay kinetics (FIG. 13) changes in duration between a bite event and chewing events (FIGs. 7-10) and changes in duration between chewing events and a swallow event (FIGs. 7-10) and may be detected through the electronic device (29) (examples of a electronic device (29) assessment of eating and swallowing shown in FIG. 28a). Al and / or machine learning may or may not be utilized to access changes in eating / mastication behavior (from an individual and / or population). Assessment of eating behavior can help to plan preventive intervention strategies for heathy aging.

[0076] Since hearing aids are predominantly used with persons in a population that is likely to develop dementia (such as the elderly, or persons at or above the age of about 60 years) and since hearing aids have been shown to slow the cognitive decline with persons with dementia (Jiang 2023 Association between hearing aid use and all-cause and cause-specific dementia: an analysis of the UK Biobank cohort), incorporating a electronic device (29) in to a functioning hearing aid device (FIG. 5) has significant utility.

[0077] The system may also be utilized to track oral medication use in, but not limited to, the elderly, persons with dementia, persons with disabilities and / or persons with psychiatric disorders (as well as a person diagnosed with any disease state requiring oral medication use). The oral mechanical processes of swallowing an oral medication may be distinct and separable than other swallowing events involved with daily drinking or eating activities. For example, a difference in the kinetics of the swallow event, or duration of the swallow event, may be separatable during oral medication ingestion than other oral / mandibular activities. The sizes of the oral medication (i.e. the size of the pill) may be differentiated. The numbers of oral medications taken during one swallow event may be differentiated. The time of day of taking oral medications may be differentiated. Information regarding oral medication use, and patterns of use, can be sent to a physician to determine if strategies need to be implemented to improve compliance. Information can also be analyzed, with or without Al and / or machine learning (from an individual and / or population), on correlations between medication use and health outcomes over time. Oral medication information can be taken from individuals or populations to improve drug development for the particular disease of interest or information into new uses of the medication for other disease indications. Al and / or machine learning may be used for population oral medication use analytics.

[0078] Oral medication use can be used during medication / drug clinical trials to determine compliance of subjects during the trial, daily temporal profiles of oral medication / drug ingestion (such as, but not limited to, time of day of medication / drug ingestion, consistency of time of day of medication / drug ingestion, relationships between eating and / or drinking activities and medication / drug (such as the food type / consistency being consumed during the clinical trial, changes in nutrient type consumption during the clinical trial, the temporal relationship between eating and / or drinking and oral medication / drug ingestion, changes in daily patterns (or mechanics (i.e. biting, chewing, swallowing during a mastication episode or swallowing events during drinking)) of eating and / or drinking during the clinical trial and / or non-conscious activities of the TMJ (or any combination thereof). Al and / or machine learning (from an individual and / or population) may or may not be utilized for analytics between TMJ activities and oral medication / drug clinical trial outcomes and / or guidance for future development of the medication / drug (in terms of changes in the molecular structure of the drug for optimal pharmacodynamics and / or pharmacokinetics (for improved effectiveness or improved safety ordecreased negative side / off target effects), optimal time of medication / drug use, optimal temporal relationships between oral medication / drug use and food and / or drink consumption and / or optimal endogenous circadian time / rhythm relationships between medication / drug effectiveness). TMJ activity information may also be used to assess clinical outcomes for medical devices (that may not be directly related to TMJ function or metabolic disorders). These analytics may be utilized outside of clinical trials for physicians to optimize oral medication / drug and / or medical device efficacy or decrease unwanted side effects of a prescribed oral medication / drug and / or medical device due to longitudinal (i.e. over multiple days or weeks or months or years) TMJ movement information.

[0079] The system may also track taking pills that are drugs of abuse for assessment of recreational drug use for screening purposes or assessment of rehabilitation therapies.

[0080] The system may also distinguish between ingestion of solid or liquid substances. Liquid ingestions are only composed of swallow events (FIG. 16). Liquids and solid ingestion may have different mandibular condyle forces (typically higher force or height of condyle mandibular elevation for a swallow event than a bite or a chew) and temporal profiles (slower rise and decay times for a swallow event as well at a longer sallow duration than a bite or chew duration, FIG. 16). For example, Table 1 includes various food and drink definitions, which include various TMJ movements when consumed.

[0081] Table 1

[0082] There may be post-ingestion shallow swallows (smaller mandibular condyle movement than chewing) following the initial swallowing of the liquid (FIG. 17). There may be differencesbetween liquid content or taste (such as but not limited to glucose, fats of carbohydrates in the liquid compared to water) that correspond to the number post-ingestion shallow swallows’ (FIG. 18) or tongue movement that will translate to movement of the mandibular condyle. For example, there may be increased swallowing or jaw movement events when drinking a sweet beverage than water. This may be due to a feedback loop between the lingual and hypoglossal nerve (Fitzgerald, The Peripheral Connexions Between the Lingual and Hypoglossal Nerves, J Anat. 1958 Apr;92(2): 178-88) and called the linguo-hypoglossal reflex (Yamamoto, Linguo- hypoglossal reflex: effects of mechanical, thermal and taste stimuli. Brain Research, 92 (1975) 499-504). The lingual nerve is activated by taste receptors on the anterior aspect of the tongue. Sweet receptors are located on the anterior aspect of the tongue. The lingual nerve forms connections with the hypoglossal nerve (Fitzgerald, The Peripheral Connexions Between the Lingual and Hypoglossal Nerves, J Anat. 1958 Apr;92(2): 178-88) which controls tongue movement. When a sweet beverage is being consumed the feedback loop causes different tongue motions than a non-sweet beverage. There also may be increased post-ingestion shallow swallows. These tongue movements and extra swallowing events translate to movements of the mandibular condyle and detected by the device. When consuming a sweet beverage not every drinking event may have differences to water or non-sweet drinking events. However, throughout the consumption of the sweet beverage there may be enough differences in mandibular condyle movement compared to consumption of water for the device to predict which type of substance is being consumed. The device would have the ability to predict a sweet beverage versus water. The system may learn, with or without Al and / or machine learning (from an individual and / or population), the type of liquid being consumed (for example sweet versus non-sweet). Detecting sweet beverages has utility in weight management apps and data can be used by a weight loss coach to help change drinking behavior. It should be noted that beverages with artificial sweeteners also are linked to weight gain (Yang, Gain weight by “going diet?” Artificial sweeteners and the neurobiology of sugar cravings, yale journal of biology and medicine 83 (2010), pp. 101-108). Thus, there is utility in detecting beverages that are sweet due to sugar or due to artificial sweeteners. This system gives objective data to report to, for example, but not limited to a clinician or weight management coach rather than answering, for example, a questionnaire with possible subjective information given by the subject.

[0083] An app can make correlations, with or without Al and / or machine learning (from anindividual and / or population), with ingestion of liquid behavior and health states of the subject such as, but not limited to, blood oxygen levels, heart rate, blood pressure, heart rhythm, sleep quality (such as, but not limited to amount of sleep, time spent in different sleep stages, snoring, obstructive sleep apnea, sleep bruxism and / or nasal versus mouth breathing or any combination thereof), physical activity, use of addictive drugs, severity of psychiatric disorders or obesity or metabolic syndrome or any combination thereof.

[0084] One objective of detection of liquid ingestion is for tracking binge alcoholic drinking behavior (typically five or more drinks in a drinking episode within about 1-2 hours). Binge consumption of alcohol may have different force and temporal profiles than non-alcoholic beverages. For example, a temporal profile for binge drinking may involve changes in drinking frequency over the course of a binge drinking episode. The length of swallowing events may be different during binge drinking and the length of swallowing events may change during a binge drinking episode. The frequency of drinking episodes may increase during a binge drinking occurrence. During a binge drinking event the frequency between drinking episodes may increase over time (i.e. low frequency of drinking episodes at the start of the binge with frequency of drinking episodes increasing over time). Time of day may be of particular importance to track binge drinking. The system can learn, with or without Al and / or machine learning (from an individual and / or population), which times of day binge drinking occurs to help predict this behavior. The system can learn, with or without Al and / or machine learning (from an individual and / or population), correlations between temporal aspects of drinking, frequency of drinking, changes in frequency of drinking and / or swallowing characteristics and binge drinking. These alcoholic drinking behaviors can be stored and accessed by users on smart devices or computers or addiction specialists to help (for example with cognitive behavioral therapy) to decrease binge alcohol drinking behaviors. Bing drinking episodes detected by the device may also be used in a closed loop system to deliver deep brain stimulation that induces the cessation of binge drinking.

[0085] The system may be used to track eating behavior to determine the likelihood of successful weight loss following bariatric surgery. Twenty to thirty percent of patients experience sub-optimal weight loss following bariatric surgery. The optimal bariatric procedure (sleeve gastrectomy, Roux-en-Y gastric bypass or duodenal switch (standard and loop or SADI- S)) for the patient may be determined by preoperative eating behavior. It may also helpdetermine if medications or lifestyle modifications should be further explored prior to surgery. Current preoperative screening has limitations. For example, patients may not report binge eating behavior. Accorded to the DSM-5 binge eating is defined by 1) eating much more rapidly than normal, 2) eating until feeling uncomfortably full, 3) eating large amounts of food when not feeling physically hungry, 4) eating alone because of being embarrassed by how much one is eating and 5) feeling depressed, or very guilty after overeating.

[0086] Referring now to Fig. 19, which depicts various remedies 150 for non-binge and binge eating. Subjects that binge eat are less likely to have success with bariatric surgery and more likely to have success with medications such as GLP-1 receptor agonists (FIG. 19). Use of the TMJ movement tracking system for a period during preoperative screening processes would give objective information regarding binge eating behaviors as well as other possible eating disorders / behaviors (such as anorexia and bulimia) that a patient may not report to a physician. The TMJ movement tracking system may improve a desired standardization screening process prior to bariatric surgery (Benalcazar, Obesity Surgery Preoperative Assessment and Preparation, 2023, NCBI Book, Obesity Surgery Preoperative Preparation). Also, the TMJ movement tracking system may be used following bariatric surgery where eating behaviors can be sent to a physician to help surgery aftercare. Determining the optimal weight loss strategy may include Al and / or machine learning (from an individual and / or population).

[0087] The TMJ movement system may also be utilized to determine the state of the gut microbiome and changes of the gut microbiome over time. The TMJ system may be utilized to determine the state of inflammatory bowel diseases or incontinence or over active bladder or changes in these states over time. The TMJ system may be utilized (with or without Al and / or machine learning from an individual and / or population) to determine the state of acid reflux and changes in acid reflux over time (including nocturnal / sleep acid reflux which may affect sleep quality). Eating different food or drink type or consumption patterns may effect the above diseases (which correlates to different mandibular activities described above).

[0088] Detecting binge eating behavior may also be an initial screen for psychiatric disorders (or the severity of a psychiatric disorder). Binge eating is associated with an increased risk for mental health comorbidities including anxiety, depression, and substance use disorders (Sheehan, The Psychological and Medical Factors Associated With Untreated Binge Eating Disorder, Prom Care Companion CNS Disord. 2015; 17(2)). These mental health disorders are also associatedwith bruxism (grinding of the teeth, an example of bruxism is shown in FIG. 28a). The combination of monitoring eating behavior such as, but not limited to, binge eating, and nocturnal (or diurnal) bruxism may be a method to screen for psychiatric disorders. TMJ data for screening for psychiatric disorders may or may not include Al and / or machine learning (from an individual and / or population).

[0089] The system may have the ability to detect, or screen, (through TMJ movement) for sleep disorders such as, but not limited to, sleep bruxism (SB, grinding of the teeth), sleep-breathing disorders such as snoring and / or obstructive sleep apnea (OSA) as well as nocturnal seizures. There is a need for novel screening tools for these sleep disorders that are more readably accessible to individuals compared to current options such as polysomnographic (PSG) recordings with advanced features that current at home sleep test by assessing multiple sleep disorders such as, but not limited to a combination of SB and / or OSA and / or sleep seizures. PSG recordings are not ideal to screen for sleep disorders in that they are not at home tests, they are conducted in a lab with sleep technicians or clinicians. This limits accessibility to various populations such as those that are under resourced, rural communities, the elderly and persons with physical disabilities such as Down Syndrome. Pediatric patients may also benefit from such a device. PSG recordings involve much equipment to measure EEG, eye movements, EMG, heart rhythm and respiratory airflow. The electronic device (29) may also include all or any combination of the following (FIG. 20): accelerometers in the electronic device (29), electrodes on the electronic device (29) to measure EEG, communication with a device that can measure heart rate, ECG heart rhythms oxygen saturation of arterial hemoglobin (SpO2) using a device such as a watch, communicate with an ancle bracelet with accelerometers to measure such events as restless leg syndrome. The device may also work cooperatively with a smart watch to detect SpO2, heart rate, ECG, photoplethysmography (PPG) and accelerometer(s) and learn sleep patterns with Al and / or machine learning (from an individual and / or population)

[0090] The earpiece device may also have a temperature probe to aid in the determination of, but not limited to, sleep stage as well as a probe to measure blood oxygen saturation. With these additional sensors the system may have the ability to measure many aspects of sleep similar to PSG recording such as sleep onset latency (SOL), REM-sleep onset latency, the number of awakenings during the sleep period, the total sleep duration, percentages and durations of every sleep stage, the number of arousals, OSA, SB and nocturnal seizures. In related embodiments,the TMJ device may be added to standard PSG recording equipment to detect such things as nasal breathing versus mouth breathing. Alternatively, the TMJ device as described herein could be used to replace, or work in combination with PSG recording equipment.

[0091] The temperature sensor in the device may be used to indicate the onset of a disease, disease severity or efficacy of a disease treatment with or without the use of Al and machine learning (from an individual and / or population).

[0092] Bruxism can decrease sleep quality and lead to damaged teeth and cause jaw pain and headache. Up to 8% of the US population experiences SB. Currently, there are limitations for treatment of nocturnal bruxism which include mouth guards and Botox injections which are not ideal for many patents. Bruxism behavior may involve right and left mandibular lateral deviations with distinct movements of the right and left TMJ (FIG. 21a) or prolonged mandibular elevations (21b). As shown, right lateral deviation 260 is compared to left lateral deviation 270. This is similarly true for the left 280 and right 290 of the Bruxism behavior may be detected by force exerted between the TMJ and TMJ sensor and distinct from that of other mandibular activities. Either one or two electronic devices (29) may be used to detect bruxism. Al and / or machine learning (from and individual and / or population) may be utilized to learn bruxism behavior / TMJ signals. An electronic device (29) may work in a closed loop system working with an implantable pulse generator to stimulate the hypoglossal nerve to induce protrusion of the tongue, to prevent or stop a SB event. The system may be used as a screen for SB.

[0093] Bruxism is also associated with other distinct disease states such as, but not limited to Parkinson’s disease and diabetes. Bruxism can be used to detect the use of addictive substances such as, but not limited to, alcohol, heroin, methamphetamine, nicotine, and piperazines (de Baat, Medications and addictive substances potentially inducing or attenuating sleep bruxism and / or awake bruxism. J Oral Rehabil. 2021;48:343-354). The system may utilize the detection of bruxism to screen for disease states or use of addictive substances.

[0094] During an awake bruxism event a sound may be delivered to the ear device to alert the user of the bruxism event to aid in behavioral therapy.

[0095] Obstructive Sleep Apnea (OSA) disease is associated with pauses in breathing during sleep and leads to multiple negative health problems including increased cardiovascular disease, stroke, metabolic disease, excessive daytime sleepiness, work-place errors, traffic accidents and death. It is caused by over relaxation of muscles of your mouth and pharynx resulting in yourtongue dropping onto the soft tissue of the roof of the mouth and pressing it against the back of the throat blocking air to the lungs (a OSA event). In some embodiments, during these events the device may detect distinct movements of the TMJ associated with mandibular retrusion. In some embodiments detection of OSA events may be enhanced by the electronic device (29) tracking breathing cycles that involve snoring. Snoring may produce distinct movements of the TMJ which may include rhythmic increases and decreases of force on the electronic device (29) that are in sync with breathing (an increase in breathing magnitude meaning an increased magnitude of elevation and depression of the mandible compared to non-snoring, (FIG. 22a) and / or increases and decreases of force on the electronic device (29) that are synced with the snoring vibrations of the soft palate (FIG. 22b). In some embodiments the electronic device (29) may use both increases in breathing magnitude and snoring vibrations to optimally detect snoring (FIG. 22c). Al and / or machine learning (from and individual and / or population) may be used to learn snoring behavior. Breathing events that precede snoring may, but not limited to, occur through the nose during the initiation of sleep (FIG. 23 a-c). At this stage there would be a positive force exerted onto the device by the TMJ. As sleep continues breathing may transition to include mouth breathing and at this transition there would be a TMJ movement which cause a prolonged negative force on the device (or neutral force). Next during the snoring stage OSA events are likely to occur (FIG. 23 a-c). During the OSA event the tongue will drop to the back, or roof, of the mouth causing a mandibular retrusion which would be detected by the device by an increase in force. At this point a brief awake event will occur to open up airways to breath and a the retrusion would cease (with no force (FIG. 23a) or possible protrusion (FIG. 23b)). Also, during the awake events gasping for air is likely to occur to reestablish airflow (FIG. 23c) also called the rescue from the OSA event. This may cause one or multiple mandibular elevations and depressions, and / or one or more mandibular protrusions and retrusions, and / or one or more mandibular deviations or any combination thereof. Despite the type of mandibular motions during gasping events there would be much movement of the mandibular condyle and positive and negative forces on the force transducer (or sensor) pressing against the electronic device (29). In some embodiments OSA is only detected by gasping events that are detected by the electronic device (29). These snoring, OSA events, wake events and / or gasping events may occur multiple times during sleep. The electronic device (29) can track the number of these distinct TMJ cycles and with the greater number of these cycles there is a greater probability thatthe subject suffers from OSA (FIGs. 23a, b and c). Al and / or machine learning (from an individual and / or population) may be utilized for the system to learn and detect these changes in condyle force patterns to predict if a person has OSA. The proposed system holds the potential for early detection of OSA using a relatively inexpensive and simplistic technique compared to PSG recordings. The electronic device (29) may also work in a closed loop system working with an implantable pulse generator to stimulate the hypoglossal nerve to induce protrusion of the tongue, to stop OSA. The mandibular condyle movement detection device may be used to detect both SB and OSA events. The device may participate in a closed loop system working with an implantable pulse generator to stimulate the hypoglossal nerve to induce protrusion of the tongue, to prevent both OSA and SB in a subject.

[0096] The electronic device (29) may be utilized to track circadian behavior that manifests through mandibular movements throughout the circadian day. This includes many behaviors such as, but not limited to, eating, drinking, use of addictive substances, bruxism, sleep activities, mouth versus nasal breathing, general mandibular movements such as elevations, depressions, deviations and protrusions and retrusions. Al and / or machine learning (from and individual and / or population) may or may not be utilized to predict circadian rhythms.

[0097] The system may be utilized to screen for the one set or the severity of dementia by tracking and analyzing sleep patterns and / or sleep disorders. Changes in sleep pattern or sleep disorders may occur at the onset of dementia and effects 25% of persons with mild dementia and 50% of persons with moderate dementia. The system may be utilized to screen for the onset or the severity of dementia by combining tracking an analyzing changes in eating behavior as well as changes in sleep patterns and / or sleep disorders. Al and / or machine learning (from and individual and / or population) may or may not be utilized to predict onset or severity of dementia.

[0098] The system may detect 2 important breathing types which includes nasal breathing and mouth breathing. Determining the duration of sleep that is spent breathing through the nose or mouth has great value. It has been shown that breathing through your mouth at night puts you at higher risk for sleep disorders including hypopnea, snoring and sleep apnea (J Allergy Clin Immunol . 1997 Feb;99(2):S757-62. doi: 10.1016 / s0091-6749(97)70124-6.) as well as daytime sleepiness and decreased quality of life (Am J Rhinol . 2007 Sep-Oct;21(5):564-9. doi: 10.2500 / ajr.2007.21.3087.) There currently is no test to determine duration of sleep that is spent nasal versus mouth breathing. The electronic device (29) will be able to determine the durationof sleep that is spent nasal versus mouth breathing. This will determine if frequent mouth breathing may be a factor in decreased sleep quality and guide clinicians to proper treatment options.

[0099] An app can make correlations, with or without Al and / or machine learning (from an individual and / or population), with the proportion of time spent sleep nasal or mouth breathing with health states of the subject such as, but not limited to, blood oxygen levels, heart rate, heart rhythm, blood pressure, other aspects of sleep quality (such as, but not limited to amount of sleep, time spent in different sleep stages, snoring, obstructive sleep apnea and / or sleep bruxism or any combination thereof), use of addictive drugs and / or severity of psychiatric disorders or any combination thereof.

[0100] During nasal breathing the mouth is closed, and the mandible is in an elevated position which increases force on the electronic device (29). When breathing is transitioned to the mouth the force decreases. These forces can be calibrated to the user by entering the type of breathing into an app which is recording the force exerted by the electronic device (29) and correlating force to breathing type. FIG. 28a is an example of the detection of vertical jaw / mandible movements using an electronic device (29). The ability to measure vertical jaw / mandible movements gives the system the ability to measure mouth versus nasal breathing.

[0101] Diurnal mouth breathing occurs when people do not or cannot breathe through their nasal passageway during the day and is associated with numerous health consequences. Prolonged untreated mouth breathing may lead to dentofacial development issues (The impact of mouth breathing on dentofacial development: A concise review Lin 2022) , cognitive function (Investigation on the Effect of Oral Breathing on Cognitive Activity Using Functional Brain Imaging Jung 2021), and is linked to the progression of chronic disease in humans (German 2023 Mouth Breathing: Understanding the Pathophysiology of an oral habit and its consequences DOI: https: / / doi.org / 10.18103 / mra.vllil.3478 ). This electronic device (29) may be able to detect the presence or absence of mouth breathing by determining jaw position while awake. An app on a smart device may alert (via a visual display on the app, vibration of a smart device or audio alert from the ear device and / or the smart device) a user at a certain frequency (for example every 15 min or 30 min or 60 min or 120 min or 240 min) if they have been breathing through their mouth for a determined proportion of time amount time (for example 10%, or 20% or 30% or 40% or 50% or 60% or 70% or 80% or 90%). A user may access the app to keep track of the proportionof time spent nasal or mouth breathing. An app can make correlations, with or without Al and / or machine learning (from an individual and / or population), with the proportion of time spent nasal or mouth breathing with health states of the subject such as, but not limited to, blood oxygen levels, heart rate, heart rhythm, blood pressure, sleep quality (such as, but not limited to amount of sleep, time spent in different sleep stages, snoring, obstructive sleep apnea, sleep bruxism and / or sleep nasal versus mouth breathing or any combination thereof), use of addictive drugs and / or severity of psychiatric disorders or any combination thereof.

[0102] Tracking TMJ movement also has the potential of detecting smoking of tobacco and / or other inhaled addictive drugs. The distinct mandibular movements associated with the inhalation of smoking tobacco translate to distinct movements of the TMJ. These movement patterns can be tracked and quantified by the proposed device. An example of mandibular condyle behaviors that are associated with smoking includes the mandibular condyle with a mandibular depression followed by a mandibular elevation or jaw protrusion movements associated with inhalation (examples of a electronic device (29) detecting these mandibular movements is demonstrated in FIGs. 28a and b). During inhalation events there can be, but not limited to, prolonged (around 1- 5 seconds) depressions of the mandible which decreases mandibular condyle depression force on the device sensor correlating with an inhalation followed by a prolonged (around 1-5 seconds) increase in mandibular condyle elevation force (FIG. 24a). However, in some instances there may be an absence of the increase in mandibular condyle elevation force (24b). In other embodiments jaw protrusion movements are associated with inhalation. There may be pauses between a smoking event (inhalation followed by exhalation) that are longer than the smoking events. An example of the ability to detect smoking is shown in FIG. 28b. Time of day can also be linked to smoking. These smoking behaviors can be stored and accessed by users on a smart device or computer to help improve negative smoking habits (for example with cognitive behavioral therapy). The smoking information can also be sent to an addiction specialist to determine smoking patterns to help with smoking cessation therapy. Al and / or machine learning (from and individual and / or population) may or may not be utilized to predict smoking behavior.

[0103] Smoking behavior may also be used for assessment of the development of dementia, the stage of dementia and cognitive decline during dementia due to the fact that increase smoking is associated with cognitive decline in persons with dementia (Ahmed 2014 Quantifying the Eating Abnormalities in Frontotemporal Dementia). Changes in smoking behavior may consist of thenumber of inhalations during the smoking of a single tobacco smoking product (i.e. the number of inhalations during the smoking of a single cigarette, cigar or pipe), the rate of inhalations during the smoking of a single tobacco smoking product, the frequency of use of smoking products and any combinations of thereof. Al and / or machine learning (from an individual and / or population) may or may not be utilized to access changes in smoking behavior.

[0104] Many disorders that are detected with the device associated with behavior may be treated with cognitive behavioral therapy (CBT) by a specialist or an app on a smart device and delivered through a speaker on the device. The CBT may utilize Al and / or machine learning.For example, an Al and or machine learning app may be used to combine large data sets(from an individual and / or population) involved with a particular behavioral disorder to offer therapy.This is advantageous in that it does not involve a therapy session and CBT can be deployed, via, for example earphones / ear buds, quickly during a negative detected behavior by the electronic device (29). A CBT app may not use Al and / or machine learning but rather a preprogrammed recording by a specialist that is generalized or tailored to the patient. The CBT may only include preprogrammed sounds. For example, during a smoking event a soothing sound may be applied to earphones / ear buds to reinforce cessation of smoking.

[0105] The system may also sweep through various sound cues (sound frequency, music therapy) and access facial expressions to determine a pleasurable sound cue that may be used to treat drug addiction. Calibration of facial expressions may be performed by asking the users to make different facial expressions that are shown on the screen of a smart device (examples: phone or tablet). Also, various sound cues can be used in learning sessions to correlate TMJ activity with the sound cues. The sound cues may be used for CBT for drug addiction and improvements in mental health of the user.

[0106] The system may also be used as a therapy for persons with autism in a closed loop system to deliver sound cues during and / or following different facial expressions. The sound cues may induce a pleasurable response. Successful sound cues may utilize Al and or machine learning (from and individual and / or population).

[0107] The system may be used as a closed loop system between sound cues and facial expression to positively change behavior. Music sound cues can change (such as change in key, speed, polyphonic or cacophonic, or completely different song) due to changes in facial expression. Sounds can change from polyphonic to cacophonic due to changes in facialexpression for improvements in mental health or drug addition. Different sounds may be played differently in either ear. Example a polyphonic sound in one ear and a cacophonic sound in the other ear. The intent of differential sounds may be to induces different plasticity between the right and left brain as a therapy for improved mental health or drug addiction. The delivery of different sounds to different ears may produce differential plasticity of the left and right brain. Sound cue examples: single frequency sound pulses, tonal patterns and other auditory pulses or signals. Successful sound cues may utilize Al and or machine learning (from and individual and / or population).

[0108] The system may also work with a heart rate monitor to measure changes in heart rate variability to determine TMJ activities that influence autonomic tone (i.e. upregulated or down regulated parasympathetic or sympathetic tone). Al and / or machine learning (from and individual and / or population) may be utilized to predict automimic tone.

[0109] Seizure detection may be an additional target for this device. During an epileptic seizure, jaw clenching is common. An example of jaw clenching is shown in FIG. 28a. Tracking seizures can be particularly challenging, as they are often amnestic events, and seizure journals are notoriously unreliable for clinical diagnostic purposes. This device may provide an accurate seizure journal indicating seizure duration, frequency, and severity. Al and / or machine learning (from and individual or population) may or may not be utilized to detect or predict seizures (nocturnal or diurnal).

[0110] The electronic device (29) may be used to diagnosis the cause, and determine the severity, of temporomandibular joint dysfunction (TMD, TMJD), and / or the source or severity of orofacial pain. It can also be used to access longitudinal (i.e. days / weeks / months / years) assessment during treatments for TMDs and determination if changes in treatment strategy are warranted. EMG sensors can be incorporated into the ear device to assist in TMD diagnosis of its cause, determine the severity of TMD, and / or the severity or source of orofacial pain. Note: EMG information can also be used for screening of diseases, and other device uses, that are not TMDs ( for example, but not limited to sleep disorders, eating / nutritional disorders / assessments, seizure detection, bruxism, breathing route, psychiatric disorders and control of devices and fitting of dental devices). It can be used to quantify restricted mandibular movement, locking of the jaw, detecting of pooping of the TMJ, assessment of upper and lower jaw alignment and eating / mastication behaviors that is associated with TMD or orofacial pain (examples of theseeating / mastication behaviors include, but not limited to, changes in the durations of mastication episodes or inter-mastication episode delays (FIG. 6), changes in number of mastication event 90 in an eating episode (FIG. 15), changes in the number of eating episodes (meals or snacking) throughout a day, changes in bite amplitude 75 (FIGs. 7-10), changes in chewing rate ((number of chews between a bite event and swallow event) / (chew duration), FIGs. 7-10)), changes in the kinetics (or rate) of chew amplitude decline in chews between a bite event and a swallow event (FIGs. 7-10), changes in bite rise and decay kinetics (FIG. 11), changes in chewing rise and decay kinetics (FIG. 12), changes in duration between a bite event and chewing events (FIGs. 7- 10) and changes in duration between chewing events and a swallow event (FIGs. 7-10) and may be detected through the electronic device (29) (examples of an electronic device (29) assessment of eating and swallowing shown in FIG. 28a). Al and / or machine learning (from an individual and / or population) may or may not be utilized to access changes in eating / mastication behavior. [OUl] The system is not limited to treating diseases. It may be used to track negative behavior prior to developing a disease (a condition that negatively effects normal daily activities). An example, but not limited to, would be infrequent binge eating or binge drinking episodes. An app can be used to track behaviors and offer feedback to the user of the development of the behaviors and suggestions and motivation to improve the negative behavior. Another example is assessment of TMJ / condyle movement that may develop into a TMD. This can be done during standard preventative dental examinations. TMJ / condyle movement would be performed longitudinally over time and recorded to determine TMJ health that may lead to TMDs. The device would be a simple easy to use device as a standard procedure in dental and orthodontic practices. Calibration of the device to TMJ movement to mandibular movement may be used with a camera or LiDar during the dental examination. Al and / or machine learning (from an individual and / or population) may or may not be utilized to access changes in TMJ assessment during dental examination.

[0112] This system may also detect undesirable off-target effects from treatments. For example, tardive dyskinesia associated with antipsychotic medications may be detected with this device, as it manifests as lateral jaw movements and also jaw protrusion and retrusion. An example of tracking horizontal and vertical jaw movements associated with tardive dyskinesia are shown in FIG. 28a and an example of protrusion and retrusion jaw movements associated with tardive dyskinesia are shown in FIG. 28b. 1

[0113] Devices may also be controlled by the electronic device (29) and can be used for disabled individuals to control the selection of words on a device for speech and control of smart devices, computers and / or headphones. It may also be used for the movement of wheelchairs. The electronic device (29) may also control systems of motor vehicles which include, but not limited to, aspects of driving the vehicle such as cruise control, lane assist, autopilot features, steering, headlights (on off and intensity), gears (such as park, drive and reverse), head lights (on off, automatic on off and intensity), reverse lights (on off and intensity), windshield wipers (on off, speed and activation of windshield wiper fluid), defrost features (on off, temperature and fan speed) as well as aspects not required to operate driving the vehicle such as, but not limited to, stereo control (on off, volume level and selection of audio source), heating and cooling of the car (on off, temperature level, fan speed and sources of the climate control), internal lights (on off, intensity and light source), seat positions and heating or cooling of seat features (on off, intensity and temperature). Devices may also be used for military applications to free the use of hands (example when handling a weapon) to control devices. It may, but is not limited to, be used in controlling night vision system settings, controlling head lamps, controlling drones or other external robotics. It may also be used to control military vehicles. It may be used to aim and shoot guns (military or non-military), aim and shoot artillery and aim and shoot missiles. Al and / or machine learning (from an individual and / or population) may or may not be used to train the system for device control.

[0114] Examples of TMJ movement to control a cursor on a screen such as a computer or a smart device are as follows. In some cases, two ear devices are utilized (utilization of two ear devices for device for a navigation task is demonstrated in FIG. 28c). For the user to move the cursor to the right they may use a right mandibular deviation which will cause an increase in condyle force on the right ear sensor and a negative (or in some cases neutral) condyle force on the left ear sensor (FIG. 25a). For the user to move the cursor to the left they may use a left mandibular deviation which will cause an increase in condyle force on the left ear sensor and a negative (or in some cases neutral) condyle force on the right ear sensor (FIG. 25b). For the user to move the cursor up they may use a mandibular elevation and / or mandibular retrusion which will cause an increase in condyle force on the left and right ear sensors (FIG. 25c). For the user to move the cursor down they may use a mandibular depression and / or mandibular protrusion which will cause a decreased in condyle force on the left and right ear sensors (FIG. 25c). Forscreen selection of an object the user may, for example, use a defined number or pattern of mandibular elevations (which may be quick in succession, such as 3-4 elevations (in about a second or two) which will select the object, open a program / app or open a menu. For deselection of an object exit from program / app or return to previous menu the user, for example, use a defined number or pattern of mandibular elevations (FIG. 25d, which may be quick in succession, such as 5-6 elevations in about a second or two). In some embodiments, a smart phone is activated to enter a TMJ app selection and activation mode by use of the phone’s rear facing camera or using a number or pattern of mandibular movements to enter the mode. In terms of camera use, the user would face the rear facing camera and make a facial expression or position their mandibular in a predetermined position for the phone to scan and make a determination to enter a TMJ app selection and activation mode. Once the phone is in the TMJ app selection and activation mode a, but not limited to, dot appears on the screen and its movement is controlled by the TMJ movement tracking system ear devices. Above methods, with patterns of mandible movements to activate or open apps and another pattern of mandible movements to close out an app (or return to the previous window of an app). When the phone has been put to sleep or put down into a predetermined position or not interacted with for a predetermined of time (example: 5-60 seconds), or a determined number or pattern of mandibular movements are executed or a facial expression is made or position their mandibular in a predetermined position is viewed by the phone’s camera, the phone will exit the TMJ app selection and activation mode. These actions may also control external devices such as, but not limited to, robotic limbs or wheelchairs or air or land or sea drones. Calibration of mandibular movements, their action on TMJ forces and the control of the device may be calibrated prior to use by imaging of the chin with a camera, and / or LiDar with or without a visual tracker (an example of a tracker may be a sticker) on the chin.

[0115] The TMJ device could also be used for controls in space flight. This includes but is not limited to space shuttle operations within the space shuttle, rocket or lunar vehicle. Alternatively, the device could be used for missions external to a space or lunar craft. For example, the use of the electronic device (29) could be used to assist an astronaut in moving a robotic arm during routine maintenance missions or repairs in order to allow for more mobility with external extremities (i.e. arms and legs).

[0116] The electronic device (29) can be utilized to control devices with binary control (FIG.26a and b). For example, numbers or patterns of mandibular elevations may be used to send binary commands to a device. The mandibular elevations may be sensed by increased force by the condyle on one (FIG. 26a) or two (FIG. 26b) ear devices. An example may be, but not limited to, controlling the settings on a head lamp or night vision goggles hands free. One elevation turns on the light or night vision goggles, two mandibular elevations increase the light level of the lamp or night vision goggles, and three mandibular elevations further increase the light level of the lamp or night vision goggles. A number or pattern of mandibular elevations may also turn down the level of the lamp or night vision goggles.

[0117] Binary control may also be utilized to control a smart device. Objects (such as apps on a home screen) may be sequentially automatically selected through a screen when the device enters an automated selection mode (through facial recognition patterns or mandibular patters of movement). Indication of the selected object may be, but not limited to, a cursor or dot over the object or change in intensity or color of the object. When the object is selected the user may use a pattern or type of mandibular movement to indicate selection of the object. Object selection may be on the users home screen or during the running of the app. Moving back on a screen may be done by a different pattern of mandibular activities or a single mandibular movement.

[0118] Mandibular movements for object selection may also have differentiating features than other mandibular activity (for example from speaking or eating or drinking). This includes kinetics of the mandibular activity or the inter-mandibular movement interval. An example of this may be fast (less then about a second, or a half of a second or a quarter of a second or less) successive mandibular elevations and / or depressions. The number of fast successive elevations and / or depressions may be used to indicate the desire for the selection of the object. The force of the mandibular movements may also differentiate it from speech as in Fig. 28b.

[0119] In the canal (ITC), completely in the canal (CIC), invisible in the canal (IIC) and middle ear hearing aids may take advantage of using mandibular condyle movement for volume control by use of binary control commands. In low profile hearing aids, the knob to change volume is not ideal. Mandibular condyle movement, detected by the electronic device (29), to change volume would have advantages for hands free control. Mandibular condyle movement detection can also be used to change different modes of the hearing aid such as input from different devices such as phones, car phone systems, televisions or modes for different situations such as to decrease crowd noise. To note: using the mandibular condyle movement device may be ofparticular importance in hands free changing settings of middle ear canal hearing aids. Examples of volitional horizontal and vertical jaw movements that may be used for hands-free control are shown in FIG. 28a and an example of protrusion and retrusion jaw movements that may be used for hands-free control are shown in FIG. 28b.

[0120] The system may be used in the fitting of dental devices to access TMJ position and movements. For example, but not limited to, mandibular advancement devises for treatments of, for example but not limited to, OSA, orthodontic devices for dental realignment, devices to treat bruxism, devices to treat TMDs, deices to treat oral facial pain and devices to assist in jaw surgery alignment. The system may be also used longitudinally (i.e. daily / weekly / monthly / yearly) to assess dental device fitting accuracy, stability and successfulness in treating the disease of interest.

[0121] The system may also work in conjunction with continuous glucose monitoring device technology to better predict changes in plasma glucose (PG) throughout the day. The system may learn correlations between mastication behavior and changes in PG to better inform a diabetic subject on dosing of insulin. The system may learn (with or with our Al and / or machine learning (from an individual or population) to correlate information from a continuous glucose monitoring system and patterns of TMJ activity / movements). The electronic device (29) may also work in a closed loop system with implanted devices that regulate PG. PG regulation devices may be initiated at the onset of mastication, detected by the electronic device (29). PG regulation devices may include neuromodulation devices that alter activity of nerves such as the Vagus nerves or its branches including the cervical Vagus nerve, the sub-diaphragmatic vagal trunks (posterior and / or anterior), hepatic branch innervating the liver, the celiac branch innervating the pancreas or any combination thereof. Modulation can include the application of low frequency stimulation signals (199 Hz or below) or high frequency alternating current (HFAC, at frequencies above 199 Hz). Ranges of low frequency signals can be from 0.01 Hz to 1 Hz, 1 Hz to 10 Hz, 10 Hz to 30 Hz, 30 Hz to 100 Hz or 100 Hz to 199 Hz. High frequency signal ranges can be from 200 Hz to 500 Hz, 500 Hz to 1,000 Hz, 1,000 Hz to 10,000 Hz or 10,000 Hz to 80,000 Hz. Current amplitude can range from 0.01 mA to 20 mA or 0.1 to 20 volts. For low frequency stimulation pulse width can vary from 0.01 milliseconds to 10 milliseconds.

[0122] The system may also work in conjunction with devices involved with the treatment of obesity. This may be involved with stomach restriction devices or devices involved withneuromodulation. The system would act in a closed loop fashion applying obesity therapy during mastication event 90. The obesity treatment devices may be activated at the initiation of mastication, or the initiation may be delayed for a period of time following the initiation of mastication. Restriction devices may decrease the volume of the stomach. Neuromodulation devices may electrically modulate parasympathetic or sympathetic nerves involved with satiety. Vagus nerve electrical modulation is an example of parasympathetic modulation. Modulation can include the application of low frequency stimulation signals (199 Hz or below) or high frequency alternating current (HF AC, at frequencies above 199 Hz). Ranges of low frequency signals can be from 0.01 Hz to 1 Hz, 1 Hz to 10 Hz, 10 Hz to 30 Hz, 30 Hz to 100 Hz or 100 Hz to 199 Hz. High frequency signal ranges can be from 200 Hz to 500 Hz, 500 Hz to 1,000 Hz, 1,000 Hz to 10,000 Hz or 10,000 Hz to 80,000 Hz. Current amplitude can range from 0.01 mA to 20 mA or 0.1 to 20 volts. For low frequency stimulation pulse width can vary from 0.01 milliseconds to 10 milliseconds.

[0123] The system may also work in conjunction with a transcutaneous auricular vagus nerve stimulator for stimulation (parameters^ frequencies 199 Hz and below, stimulation amplitudes 0.1 mA to 20 mA (or 0.1 to 20 volts) , 0.1 to 10 ms pulse width), or high frequency conduction block (parameters=frequencies 200 Hz or above, stimulation amplitudes 0.1 mA to 20 mA (or 0.1 to 20 volts)), or burst stimulation (parameters=burst stimulation frequency 1-199 Hz, burst length 0.1 to 10 seconds, inter-burst interval 0.1 to 20 seconds, number of busts ranging from 1 to 200, bust pulse amplitude 0.1 to 20 mA (or 0.1 to 20 volts), burst pulse width 0.1 to 20 ms) of the auricular branch of the vagus nerve (ABVN). The system can work in a continuous closed loop fashion to deliver different stimulation parameters, high frequency conduction block parameters or burst stimulation parameters on demand depending on mandibular movements or activities. Mandibular movements include tracking mandibular elevations, depressions, deviations retrusions and / or protrusions. Mandibular activities are those associated with mastication, eating behavior, an eating event, sleeping, nasal versus mouth breathing, detection of the use of addictive substances and / or detection of psychiatric disorders. During or following the systems detection of predetermined mandibular movements and / or activities predetermined stimulation parameters, high frequency conduction block parameters or burst stimulation parameters can be delivered to the ABVN through the transcutaneous auricular vagus nerve stimulator to treat disorders such as, but not limited to, obesity, metabolic disorders, sleepdisorders, seizures, migraine, disorders involved with inflammation, lupus erythematosus, dysmenorrhea, cognitive impairment and / or psychiatric disorders. The system can work in a non-continuous closed loop fashion to deliver predetermined stimulation parameters, high frequency conduction block parameters or burst stimulation parameters during a therapy session depending on mandibular movements and / or activities throughout a determined amount of time. For example, the system can record mandibular movements and / or activities over a 24 hour period or throughout the day / awake time or thorough out the night / sleep time to adjust transcutaneous auricular vagus nerve stimulator stimulation parameters, high frequency conduction block parameters or burst stimulation parameters to treat disorders such as, but not limited to, obesity, metabolic disorders, sleep disorders, seizures, migraine, disorders involved with inflammation, lupus erythematosus, dysmenorrhea, cognitive impairment and / or psychiatric disorders.

[0124] The system may also be used in a closed-loop system involved in neuromodulation of the perception of taste and / or smell. Examples of nerves that could be modulated are the Vagus nerve, the chorda tympani, the glossopharyngeal nerve and / or the olfactory nerve. The neuromodulation can induce dysgeusia, hypogeusia and / or ageusia. Neuromodulation may be the delivery of electric signals. Neuromodulation electrical signals can include the application of low frequency stimulation signals (199 Hz or below) or high frequency alternating current (HFAC, at frequencies above 199 Hz). Ranges of low frequency signals can be from 0.01 Hz to 1 Hz, 1 Hz to 10 Hz, 10 Hz to 30 Hz, 30 Hz to 100 Hz or 100 Hz to 199 Hz. High frequency signal ranges can be from 200 Hz to 500 Hz, 500 Hz to 1,000 Hz, 1,000 Hz to 10,000 Hz or 10,000 Hz to 80,000 Hz. Current amplitude can range from 0.01 mA to 20 mA or 0.1 to 20 volts. For low frequency stimulation pulse width can vary from 0.01 milliseconds to 10 milliseconds. . Modulation can include the application of low frequency stimulation signals (199 Hz or below) or high frequency alternating current (HFAC, at frequencies above 199 Hz). High frequency signal ranges can be from 200 Hz to 500 Hz, 500 Hz to 1,000 Hz, 1,000 Hz to 10,000 Hz or 10,000 Hz to 80,000 Hz. Current amplitude can range from 0.01 mA to 20 mA or 0.1 to 20 volts. For low frequency stimulation pulse width can vary from 0.01 milliseconds to 10 milliseconds. Directional conduction block and stimulation can be utilized. Neuromodulation may be burst stimulation (parameters=burst stimulation frequency 1-199 Hz, burst length 0.1 to 10 seconds, inter-burst interval 0.1 to 20 seconds, number of busts ranging from 1 to 200, bust pulseamplitude 0.1 to 20 mA (or 0.1 to 20 volts), burst pulse width 0.1 to 20 ms

[0125] The TMJ sensor would be utilized in the closed-loop system to apply taste modulating neuromodulation during mastication and / or swallowing events. The start of neuromodulation may be at the initiation of mastication or at a determined duration following the initiation of mastication and / or swallowing. The neuromodulation may occur during a meal or snack. Mastication behavior in response to the application of neuromodulation may be recorded and analyzed (with or without Al / or and machine learning) to determine optimal neuromodulation parameters (frequency, burst, current amplitude, voltage amplitude, pulse width, monopolar pulse shape, bipolar wave shape and / or different pulse rise times and decay times) to achieve a desired effect such as cessation of eating and / or drinking. Al and / or machine learning (for an individual or population) may or may not be utilized to determine how TMJ activity relates to taste modulation.

[0126] When taste modulation neuromodulation occurs an audio signal may be applied to a speaker in the earpiece. This audio signal may be a tone or a voice recording indicating that taste modulation has been initiated. The same may be done at the cessation of an eating episode 95. An audio signal may also be applied without neuromodulation

[0127] An app on a smart device may display force vs time in real time and highlight waveforms associated with mandibular movement / positions or predicted events of mandibular activity such as, for example, swallowing, chewing, smoking, bruxism or mouth or nasal breathing. This will give the user an opportunity to interact with the device and its ability to track and predict certain activities of the mandible as well as enter information into an app on if the device is predicting the correct mandibular movement / position or mandibular event. Also, the app may display a 3D model of the mandible and move with the movements of the users TMJ that are detected by the system.

[0128] The electronic device (29) may be utilized to determine the cause of temporomandibular disorders (TMDs) and may or may not incorporate EMG sensing electrodes to work concurrently with the force transducers. TMDs are disorders of the jaw muscles, temporomandibular joints, and the nerves associated with chronic facial pain. Any problem that prevents the complex system of muscles, bones, and joints from working together in harmony may result in TMDs and is classified by myofascial pain, internal derangement of the joint and / or degenerative joint disease. Outside of degenerative joint disease a major cause of TMDs is bruxism. The systemmay replace the need for imaging in TMD source diagnosis. The system may collect longitudinal data (i.e. over multiple days, weeks, months or years) to determine the source of TMDs. The system may be used to determine the success of TMD treatments acutely or longitudinally.

[0129] The TMJ movement system may also be used to aid in telemedicine for disease diagnosis or treatment success. Diseases include diseases directly or indirectly are caused by pathophysiological of the TMJ. TMJ movement information may be sent to a physician in real time during the telemedicine session or previous longitudinal data. Telemedicine may be used for medical device adjustments in real time. Medical devices may be for oral use or non-oral use. An example of non-oral use would be for programming of active implantable (electrical or non-electrical).

[0130] The system may be utilized to build TMJ movement Al classifiers (from an individual and / or population) used to predict future behavior. This includes discussions based on perceived reward value and predicting the perception of the value of the reward. Behavior changes also include changes in decision strategy from procedural to deliberative or vice versa. This also includes predicting changes in delayed discounting behavior. Analysis of this behavior may be used to predict present or future purchasing decisions. TMJ system data to predict behavior may be from individuals or human populations (including sub-populations).

[0131] Examples

[0132] Experiments were performed to test the ability of an electronic device (29) to detect types of mandibular movements as well as discern between various mandibular activities such as mastication of different foods, swallowing, bruxism and smoking tobacco. This device utilized a force transducer, but similar detectors of mandibular movements and activities may include a microphone, a strain gauge, a force gauge a piezoelectric sensor a multi-axis accelerometer or gyroscope or an combination thereof. Force may be transduced and measured through an electrical measurements, a microfluidic system, a hydraulic system or a pneumatic systems or any combination thereof.

[0133] Data collection methods:

[0134] TMJ data was collected using a custom-built device. A 3.8 mm diameter FlexiForce A101 Sensor (Tekscan, Norwood, MA, USA) was affixed to a conical polypropylene earpiece that fits conformally in the outer ear canal (FIGs. 27a and 27b). The FlexiForce sensor was thenconnected via flexible copper wire in series with a lOkOhm resistor and a 5V voltage source. An Arduino UNO (Arduino, Somerville, MA, USA) measured the electrical potential drop across the FlexiForce sensor associated with varying force sensed through the TMJ joint. The voltage signal was sampled at 100Hz sampling rate through the Arduino Serial Monitor on a PC running Microsoft Windows (FIG. 27b). The signal was smoothed using a 50-point gaussian smoothing filter and plotted using MATLAB. Signal to noise ratio (SNR) was used as a descriptive statistic to discern between various mandibular movements and was calculated as the mean signal of each activity divided by the baseline rest signal during which no activities were performed.

[0135] Results:

[0136] In a first set of experiments, after approximately 20 seconds of rest, four bouts of 5- second duration isometric jaw clenching maneuvers resembling bruxism or epileptic seizures were performed (SNR=5.2, green, FIG. 28a), separated by approximately 5-second rest periods. Five bouts of swallowing with an empty mouth were then performed (SNR=11.5, red, FIG. 28a). Isotonic vertical jaw movements were performed at approximately 1 s intervals (SRN=6, FIG. 28a), with the signal peaks representing the jaw maximally closed and the nadirs representing the jaw maximally open. A handful of popcorn, representing food that requires minimal mastication, was then chewed (SNR=5.4, FIG. 28a) and swallowed (red, FIG. 28a). A handful of peanuts, representing food that requires a moderate amount of mastication, was then chewed (SNR=6.3, gray, FIG. 28a) and swallowed (red, FIG. 28a). Note the decrease in normalized force required for each successive bite as the food is masticated as well as the increased normalized force of the swallowing event compared to the chewing events for eating popcorn as well as eating peanuts (FIG. 28a also depicted in FIGs. 7 through 11). Isotonic horizontal jaw movements were performed at approximately Is intervals (SRN=8.3, pink, FIG. 28a), with the signal peaks representing the jaw position maximally ipsilateral to the ear in which the sensor was located and nadirs representing the jaw position maximally contralateral to the sensor ear.

[0137] In a second set of experiments, nine bouts of approximately 3-second duration isotonic jaw retrusion (SNR=2.3, green, FIG. 28b), and protrusion (SNR=1.9, FIG. 28b) were performed. After a rest period of approximately 15 seconds, tobacco was smoked from a pipe (SNR=1.7, FIG. 28b), with downward deflections in the signal representing jaw protrusion movements associated with inhalation. Speaking was performed for approximately 25 seconds (gray, FIG. 28b), though no SNR was calculated. For negative signals (i.e. maximal retrusion and smokingtobacco, FIG. 28b), signal was defined as the baseline signal plus the absolute difference between baseline signal and rest signal, all divided by rest signal.

[0138] Referring to Figs. 27A and 27B, where in Fig. 27 the housing 28 and sensors 30 and shown in a wired formation. Referring specifically to Fig. 27B where the device is a behind the ear 36 configuration. As shown, the device can be in communication with an external device 300 for retrieving data, performing therapeutic regimens, or acting on a movement initiated by the user.

[0139] Referring now to FIG. 28a, that during eating of popcorn or peanuts (FIG. 28a, with unique SNRs) there is a decrease in normalized force required for each successive bite as the food is masticated as well as the increased normalized force of the swallowing event compared to the chewing events for eating popcorn as well as eating peanuts (which is depicted in FIGs. 7 through 11). Also, note that there is an increased in normalized force of the first waveform in the peanut chewing versus popcorn chewing which indicates a difference in the force of condyle elevation during the bite event between what food type is being consumed which is demonstrated in FIG. 8. Also, note the increase in normalized force of the waveforms, starting at the second, prior to the swallowing event in the peanut chewing versus popcorn chewing which indicates a difference in the force of condyle elevation during chewing events between what food type is being consumed which is depicted in FIG. 9. The event segment of chewing of the popcorn or the event segment of chewing the peanuts in FIG. 28a represents a mastication episode as depicted in FIG. 6.

[0140] It should be appreciated that the large increase in normalized force of the final waveform in the chewing popcorn and peanut events in FIG. 28a which is a swallowing event demonstrating the systems ability to detect swallowing also depicted in FIGs. 7 through 13 and FIGs. 16 through 18. The absence of bite and chewing events with the presence of swallowing events indicates drinking of a liquid (depicted in FIGs. 16 and 18).

[0141] Note in FIGs. 28a and 28b that the changes in normalized force from resting to peak force during various mandibular activities have different slopes which is also depicted in FIGs. 11 to 13. The change in slope may differ between different foods being consumed, liquids being consumed, and activities such as, but not limited to, bruxism, seizures smoking, binge drinking and sleeping events.

[0142] The differences in waveforms and SNR during a jaw clenching resembling bruxism orseizure (FIG. 28a, with a unique SNR) compared to other mandibular movements and activities (FIGs. 28a and 28b, with other unique SNRs). During the bruxism or seizure like activity there is a sustained increased in normalized force compared to swallowing, chewing, smoking, speaking or rest (all with unique SNRs). This is similar to what is depicted in FIGs. 21a and 21b for force detection of either the right and / or left TMJ with prolonged force of condyle elevations due to lateral deviations (FIG. 21a) and / or vertical mandibular movement (FIG. 21b).

[0143] Referring now to FIG. 28a which demonstrates the system’s ability to detect vertical jaw movement (i.e. mandibular depressions and elevations, with a unique SNR). The detection of the vertical position of the jaw / mandible allows the system to determine snoring shown in FIG. 22, mouth versus nasal breathing shown in FIG. 23a through 23c as well as detection of OSA also shown in FIGs. 23a through 23c.

[0144] Turning to FIG. 28b which demonstrates the system’s ability to detect retrusion and protrusion (with a unique SNRs) which are movements of, but not limited to, smoking activity depicted in FIGs. 24a and 24b.

[0145] The differences in waveforms, maximal normalized force and SNR between vertical jaw movements (i.e. mandibular elevation and depression, with unique SNRs), horizontal jaw movements (i.e. mandibular deviations, with unique SNRs) and maximal retrusion and protrusion (with unique SNRs) found in FIGs. 28a and 28b. These examples of discerning types of mandibular movements demonstrate, but not limited to, the ability of the system to control devices as depicted by using different types of mandibular movements, for example, to control a mouse on a screen and the selection of objects on the screen depicted in FIGs. 25a through 25d as well as binary device control depicted in FIGs. 26a and 26b. This same methodology may be used to control multiple other devices, but not limited to, wheelchairs, control settings of a vehicle (military or non-military), a gun (aiming and firing for military or non-military applications), artillery control, missile control, control of land, air and sea drones, control of exoskeletons, settings of a headlamp or settings of night vision systems. FIG. 28c demonstrates the ability of two TMJ movement sensor systems, one in each ear, ability for navigational control by successfully tracking movement of an object on a display. This control can be translated to a multitude of digital or physical devices

[0146] Referring now to FIG. 29, data demonstrating TMJ sensor controllability for navigation tasks. A TMJ sensor was placed both in right and left ears while a volunteer moved their jawlaterally right and left following a 0.48Hz sine wave. The normalized force from two TMJ sensors correlates strongly with the sine wave cue during three repetitions of maximal lateral mandible deviation, with a maximal left deviation beginning at t=4s (FIG. 29). Jaw deviations ipsilateral to the sensor ear appear as an increase in normalized force (FIGs. 29) while deviations contralateral to ear sensor (FIG. 29) or jaw retrusion (FIG. 29) appear as a decrease in normalized force.

[0147] FIG. 29 demonstrates normalized force recorded from TMJ sensors placed in right ear (330) and left ear (350) recorded simultaneously while moving jaw laterally left and right following a sine wave (370). Maximal left deviation at peaks of deviation (330) and maximal right deviation at peaks of deviation 350.

[0148] In the context of the present description, all publications, patent applications, patents and other references mentioned herein, if not otherwise indicated, are explicitly incorporated by reference herein in their entirety for all purposes as if fully set forth and shall be considered part of the present disclosure in their entirety.

[0149] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skilled in the art to which this disclosure belongs. In case of conflict, the present specification, including definitions, will control.

[0150] The descriptions of the various embodiments of the present disclosure have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others or ordinary skill in the art to understand the embodiments disclosed herein.

[0151] Except where expressly noted, trademarks are shown in upper case.

[0152] Unless stated otherwise, all percentages, parts, ratios, etc., are by weight.

[0153] When an amount, concentration, or other value or parameter is given as a range, or a list of upper and lower values, this is to be understood as specifically disclosing all ranges formed from any pair of any upper and lower range limits, regardless of whether ranges are separately disclosed. Where a range of numerical values is recited herein, unless otherwise stated, the range is intended to include the endpoints thereof, and all integers and fractions within the range. It isnot intended that the scope of the present disclosure be limited to the specific values recited when defining a range. Further, where a numerical limit or range is stated herein, the endpoints are included. Also, all values and subranges within a numerical limit or range are specifically included as if explicitly written out.

[0154] Further, unless otherwise explicitly stated to the contrary, when one or multiple ranges or lists of items are provided, this is to be understood as explicitly disclosing any single stated value or item in such range or list, and any combination thereof with any other individual value or item in the same or any other list.

[0155] When the term “about” is used, it is used to mean a certain effect or result can be obtained within a certain tolerance, and the skilled person knows how to obtain the tolerance. When the term "about" is used in describing a value or an endpoint of a range, the disclosure should be understood to include the specific value or endpoint referred to.

[0156] As used herein, the terms "comprises," "comprising," "includes," "including," "has," "having" or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0157] The transitional phrase "consisting of excludes any element, step, or ingredient not specified in the claim, closing the claim to the inclusion of materials other than those recited except for impurities ordinarily associated therewith. When the phrase "consists of appears in a clause of the body of a claim, rather than immediately following the preamble, it limits only the element set forth in that clause; other elements are not excluded from the claim as a whole.

[0158] The transitional phrase "consisting essentially of limits the scope of a claim to the specified materials or steps and those that do not materially affect the basic and novel characteristic(s) of the claimed invention. A “consisting essentially of’ claim occupies a middle ground between closed claims that are written in a “consisting of’ format and fully open claims that are drafted in a “comprising” format. Optional additives as defined herein, at a level that is appropriate for such additives, and minor impurities are not excluded from a composition by the term “consisting essentially of’.

[0159] As used herein, an "embodiment" means that a particular feature, structure or characteristic is included in at least one or more manifestations, examples, or implementations ofthis invention. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner, as would be apparent to a person skilled in the art.

[0160] Combinations of features of different embodiments are all meant to be within the scope of the invention, without the need for explicitly describing every possible permutation by example. Thus, any of the claimed embodiments can be used in any combination.

[0161] Further, unless expressly stated to the contrary, “and / or” refers to an inclusive and not to an exclusive. Thus, “and / or” should be understood to mean “either or both” of the elements so conjoined, e.g., elements that are conjunctively present in some cases and disjunctively present in other cases. For example, a condition A and / or B, is satisfied by any one of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present).

[0162] The use of "a" or "an" to describe the various elements and components herein is merely for convenience and to give a general sense of the disclosure. This description should be read to include one or at least one and the singular also includes the plural unless it is obvious that it is meant otherwise. Similarly, the adjective “another,” when used to introduce an element, is intended to mean one or more elements. The terms “including” and “having” are intended to be inclusive such that there may be additional elements other than the listed elements.

[0163] The above written description of the invention provides a manner and process of making and using it such that any person skilled in this art is enabled to make and use the same, this enablement being provided in particular for the subject matter of the appended claims, which make up a part of the original description.

[0164] As used herein, the phrases “selected from the group consisting of,” “chosen from,” and the like include mixtures of the specified materials.

[0165] Having generally described this invention, a further understanding can be obtained by reference to certain specific examples, which are provided herein for purposes of illustration only, and are not intended to be limiting unless otherwise specified.

[0166] The aspects of the invention are non-exclusively described in the below numbered clauses:1. An electronic device comprising: a housing;at least one sensor in communication with the housing, wherein the at least one sensor is capable of obtaining a signal indicating the position of, and / or movement of, the temporal mandibular joint (TMJ), or a portion thereof.2. The electronic device of clause 1, wherein the sensor is directly connected to the housing.3. The electronic device of clause 1, wherein the sensor is indirectly connected to the housing.4. The electronic device of any one of clauses 1-3, wherein the electronic device comprise a plurality of sensors.5. The electronic device of clause 4, wherein the plurality of sensors are positioned at different locations on the surface of the housing.6. The electronic device of clause 4 or 5, wherein the sensors work together to obtain the signal.7. The electronic device of any one of clauses 1 to 6, wherein the at least one sensor is positioned on the external surface of the housing.8. The electronic device of any one of the clauses 1-7, wherein a data communication interface is within the housing and is configured to transmit and receive data to a communication processor.9. The electronic device of clause 8, wherein a portion of the communication processor is within the housing and connected to the data communication interface.10. The electronic device of clause 9, wherein the communication processor is external of the housing.11. The electronic device of clause 9, wherein the communication processor is wirelessly connected the electronic device.12. The electronic device of any one of clauses 8-11, wherein the communication processor is capable of retrieving a signal protocol and relaying the signal protocol.13. The electronic device of any one of clauses 8-11, wherein the communication processor is capable of sending a signal to a smart device or computer.14. The electronic device of any one of clauses 1-13, wherein the signal is used to identify a subset of TMJ movements including vertical, horizontal, retrusion, protrusion or any combination thereof.15. The electronic device of any one of clauses 1-14, wherein the electronic device is a wireless earbud device, wireless headphone device or a wired headphone device.16. The electronic device of any one of clauses 1-15, wherein the electronic device is a hearing aid.17. The electronic device of any one of clauses 1-16, wherein the electronic device receives information regarding movement from the TMJ from by sensing deformation of the ear canal during mandibular movement using a sensor18. The electronic device of any one of clauses 1-17, wherein the housing is partially positioned in the ear canal.19. The electronic device of any one of clauses 1-17, wherein the housing is positioned outside the ear canal.20. The electronic device of any one of clauses 1-19, wherein the sensor is partially positioned in the ear canal.21 . The electronic device of any one of clauses 1 -20, wherein the sensor is capable of detecting TMJ movements with a force between the mandibular condyle and the sensor.22. The electronic device of any one of clauses 1-21, wherein the transduction of TMJ movement or force is achieved through a sensorthat transduces information regarding a change in deformation of the surface of the ear canal due to a change in TMJ position by changes in the electrical properties of a conductive, semi-conductive or non-conductive material.23. The electronic device of any one of clauses 1-22, wherein the sensor is capable of detecting signals selected from a group comprising resistance, impedance, current, capacitance, electrostatic field, electromagnetic field, sound, light and any combination thereof.24. The electronic device of any one of clauses 1-23, wherein the sensor transduces information regarding a change in deformation of the surface of the ear canal due to a change in TMJ position by changes in light intensity, color, wavelength from a light source or any combination thereof.25. The electronic device of any one of clauses 1-24, wherein the sensor obtains measurements of deformation of the outer ear canal corresponding with TMJ activity, wherein the measurements are obtained from at least one of a microphone(s), a force transducer(s), a strain gauge(s), a capacitive sensor(s), a Hall-Effect sensor(s), a light sensor(s), an accelerometer(s), a force sensitive resistor(s), a piezoelectric sensor(s), field effect sensor(s), an ultrasound sensor(s)a gyroscope(s), a magnetometer(s), EMG electrodes, optical sensors. LIDAR, infrared, NIR, visual spectrum, video camera, -goniometer or any combination thereof.26. The electronic device of any one of clauses 1-25, wherein the sensor(s) are rigidly positioned on the surface of housing.27. The electronic device of any one of clauses 1-25, wherein the sensor(s) are not rigidly positioned on the housing.28. The electronic device of any one of clauses 1-27, wherein the sensor(s) are positioned to measure movement of the mandibular condyle within 1000 microns.29. The electronic device of any one of clauses 1-27, wherein the sensor(s) are positioned to measure movement of the mandibular condyle within 500 microns.30. The electronic device of any one of clauses 1-27, wherein the sensor(s) are positioned to measure movement of the mandibular condyle within 250 microns.31. The electronic device of any one of clauses 1-27, wherein the sensor(s) are positioned to measure movement of the mandibular condyle within 100 microns.32. The electronic device of any one of clauses 1-27, wherein the sensor(s) are positioned to measure movement of the mandibular condyle within 10 microns.33. The electronic device of any one of clauses 1-27, wherein the sensor(s) are positioned to measure movement of the mandibular condyle within 1 microns.34. The electronic device of any one of clauses 4-33, wherein the each of the plurality of sensors relay different signals.35. The electronic device of any one of clauses 1-34, wherein the sensor comprising filaments, wherein the filaments are either a rigid filament or a flexible filament.36. The electronic device of clause 35, wherein the location of the deformation is determined along the length fdament(s).37. The electronic device of any one of clauses 35-36, wherein the filament is a synthetic fiber.38. The electronic device of any one of clauses 35-37, wherein the resting state of the filament occurs when the mandible is in a fully depressed or protruded position.39. The electronic device of any one of clauses 35-38, wherein the filament is considered in a force neutral position when the mandible is at rest, a positive force position when the mandible is elevated, retruded or a lateral deviation to the ipsilateral ear sensor.40. The electronic device of any one of clauses 35-39, wherein the filament is considered in a force negative position when the jaw is position when the mandible is depressed, protruded or a lateral deviation to the contralateral of the ear sensor.41. The electronic device of any one of clauses 1-40, wherein the electronic device comprises a plurality of filaments.42. The electronic device of any one of clauses 35-41, further comprising an actuator, wherein the actuator is activated to protrude filaments towards the TMJ.43. The electronic device of clause 43, wherein the actuator is selected from a group comprising a lever, slide, knob, button, disc or any combination thereof.44. The electronic device of any one of clauses 42-43, wherein the actuator comprise a microphone for activating the filament(s)with an auditory command.45. The electronic device of any one of clauses 1-44, wherein the sensor is selected to detect TMJ movements with a frequency between 0.001 and 1000 Hz.46. The electronic device of any one of clauses 1-44, wherein the sensor is selected to detect TMJ movements with a frequency between 0.001 and 10 Hz.47. The electronic device of any one of clauses 1-44, wherein the sensor is selected to detect TMJ movements with a frequency greater than 10 Hz.48. The electronic device of any one of clauses 1-44, wherein the sensor is selected to detect TMJ movements between 0.001 Hz and 1 Hz.49. The electronic device of any one of clauses 1-44, wherein the sensor is selected to detect TMJ movements between 1 Hz and 10 Hz.50. A TMJ system comprising: a. a first electronic device of any one of clauses 1-49 and b. a second electronic device of any one of clauses 1-49.51. The TMJ system of clause 50, wherein the sensor(s) are positioned to measure movement of the left and right TMJ simultaneously.52. The TMJ system of clauses 50 or 51, wherein the data communication interface in each of the two housings are connected to a single communication processor.53. The TMJ system of any one of clauses 50-52, wherein the communication processor is wirelessly connected to the plurality of data communication interface signals.54. The TMJ system of any one of clauses 50-53, wherein, the right and left sensors work cooperatively to determine vertical, horizontal, retrusive and / or protrusive mandibular movements and / or relative mandibular positions from a zero coordinate.55. The TMJ system of any one of clauses 50-54, further comprising a calibration component.56. The TMJ system of clause 55, where the calibration component comprises a video imaging system.57. The TMJ system of any one of clauses 55 or 56, wherein the calibration component comprises a LiDar system.58. The system of any one of clauses 55-57, wherein the calibration component provides auditory instructions.59. The system of any one of clauses 55-58, wherein the calibration component comprises calibration options selected from a group comprising: time, functionality, user, mandibular position, mandibular movement or any combination thereof.60. A method of detecting foodstuff consumption in a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.61. The method of clause 60, wherein the data communication interface can determine what category of foodstuff is being consumed.62. The method of clause 61, wherein the foodstuffs is selected from a group comprising moderately thick, extremely thick, minced and moist, soft and bite sized and solid or any combination thereof.63. The method of any one of clauses 60-62, wherein the foodstuffs is selected from a group comprising fruit, vegetable, meat, fat, bread, rice, pasta, tree nuts, drupes, legumes and any combinations thereof.64. The method of any one of clauses 60-63, further comprising the step of determining time spent masticating the foodstuffs.65. The method of any one of clauses 60-64, wherein the sensor is capable of obtaining mastication behavior selected from a group comprising: measuring changes in swallowing function, appetite, eating habits, food preference, food cramming and combinations thereof.66. The method of any one of clauses 60-65, wherein the sensor is capable of obtaining mastication movement, thereby predicting foodstuff being consumed including: measuring changes in duration of mastication episodes, number of mastication episodes, inter-mastication episode delay, oral drug consumption, bite amplitude, bite duration, bite kinetics, chewing duration, chewing amplitude, changes in chewing amplitude before a swallowing event, kinetics of a single chewing event, swallowing amplitude and swallowing kinetics and combinations thereof.67. The method of any one of clauses 60-66, wherein the device is used to determine changes in eating behaviors in persons with dementia or pre-dementia68. The method of any one of clauses 60-67, wherein the sensor is capable of obtaining TMJ behavior associated to swallowing a liquid by measuring a swallow event in the absence of bite and / or chewing events.69. The method of any one of clauses 60-67, wherein the sensor is capable of obtaining texture of a liquid being consumed including thin, slightly thick, mildly thick, liquidized and pureed or any combination thereof.70. The method of any one of clauses 60-69, wherein the sensor is capable of obtaining type of liquid being consumed including a sweet or nonsweet beverages which may involve measuring post ingestion shallow swallows.71. The method of any one of clauses 60-70, wherein the sensor is capable of obtaining mastication and / or swallowing behavior that indicates the presence of dysphagia, and optionally the progression of dysphagia over time.72. The method of any one of clauses 60-70, wherein the sensor is capable of obtaining mastication and / or swallowing behavior that indicates the presence of dysphagia and optionally the progression of dysphagia over time in persons with dementia or pre-dementia.73. The method of clause 71 or 72, wherein dysphagia is determined at least one signal calculated by; length of time between chewing events, a swallow event, a swallow event duration with chewing, a swallow event without chewing, a biting event, kinetics of the swallowing event and any combination thereof.74. The method of any one of clauses 71-73, wherein the system is used for eating detection, wherein the system optionally uses a closed loop stimulation device.75. A method of detecting inhalation in a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.76. The method of clause 75, wherein the data communication interface can determine frequency of an inhalation event.77. The method of clause 75 or 76, wherein the inhalation event is selected from a group comprising smoking, vaping, metered dose, dry powder, soft mist, nebulizer and combinations thereof.78. The method of any one of clauses 75-77, further comprising the step of determining time spent performing inhalation event.79. The method of any one of clauses 75-78, further comprising the step of determining frequency performing inhalation event.80. The method of any one of clauses 75-79, further comprising the step of determining inhalation event patterns.81. The method of any one of clauses 75-80, wherein inhalation is distinguishable from other mandibular activities by TMJ movement interval, duration of the TMJ displacement, duration of time between TMJ displacements and / or kinetics of the TMJ displacement and any combination thereof.82. A method of controlling an external device comprising the steps: a. positioning an electronic device any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor, wherein the communication processor sends a signal to an external device to initiate a command.83. The method of clause 82 in which the controlled device is selected from a group comprising a head lamp, night vision goggles, computer apparatus (i.e. mouse or keyboard), phones, car phone systems, televisions, remotes, wheelchairs, control and operational settings of avehicle (military or non-military), a gun (aiming and firing for military or non-military applications), artillery control, missile control, control of land, air and sea drones, control of exoskeletons and any combination thereof.84. The method of clause 82 or 83, wherein the electronic device of any one of clauses 1-59 is positioned in a subjects right ear and a second electronic device of any one of clauses 1-59 is positioned in a subjects left ear.85. The method of clause 84, wherein the sensor(s) are positioned to measure movement of the left and right TMJ simultaneously to obtain movement commands.86. The method of clause 84, wherein the sensor(s) are positioned to measure movement of the left and right TMJ separately to obtain movement commands.87. The method of any one of clauses 82-86, wherein the device commands are binary, using rapid vertical or horizontal or protrusion / retrusion movements.88. The method of clause 87, wherein the binary commands are achieved with 1-10 successive mandibular movements.89. The method of any one of clauses 82-86, wherein the device commands are nonbinary by a combination of mandibular movements including vertical and / or horizontal and / or protrusion / retrusion movements or any combination thereof.90. A method of detecting, diagnosing, treating or preventing cardiovascular events in a subject comprising the steps: a. positioning an electronic device any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.91. The method of clause 90, wherein the cardiovascular event comprises cardiovascular disease.92. A method of detecting sleep quality in a subject comprising the steps: a. positioning an electronic device any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.93. The method of clause 92, wherein the device measures the amount of sleep, time spent in different sleep stages, snoring, obstructive sleep apnea, sleep bruxism, nasal breathing, mouth breathing, nocturnal seizures, seizures, or any combination thereof.94. The method of clauses 92 or 93, wherein the device further comprises a pulse generator, capable to stimulate the hypoglossal nerve to induce protrusion of the tongue, to prevent or stop a sleep bruxism event.95. The method of clause 92, wherein the device measures waking gasping events during, or following a sleep apnea event.96. The method of clause 92, wherein the device measures waking gasping events during sleep apnea by fast increases and / or decreases in force on the TMJ sensor.97. The method of any one of clauses 92-95, wherein the device measures waking gasping events during sleep apnea by increases and / or decreases in force on the TMJ sensor at a rate from 0.1 to 1000 Hz.98. The method of any one of clauses 92-95, wherein the device measures waking gasping events during sleep apnea by increases and / or decreases in force on the TMJ sensor at a rate from 0.1 to 5 Hz.99. The method of any one of clauses 92-98, wherein the device determines whether a subject is mouth breathing and nasal breathing during a during sleep.100. The method of any one of clauses 92-98, wherein the device determines whether a subject is mouth breathing and nasal breathing during awake states.101. The method of any one of clauses 92-98, wherein the device during the subject being awake measures blood oxygen levels, heart rate, heart rhythm, blood pressure, body temperature and any combination thereof.102. The method of any one of clauses 92-98, wherein the device during the subject being asleep measures blood oxygen levels, heart rate, heart rhythm, blood pressure, body temperature and any combination thereof.103. The method of any one of clauses 92-102, wherein the device measures changes in heart rate variability.104. The method of any one of clauses 92-103, wherein the device detects tiredness / exhaustion.105. The method of any one of clauses 92-103, wherein the device detects tiredness / exhaustion, and optionally induces a notification from a smart device.106. The method of any one of clauses 92-103, wherein the device detects tiredness / exhaustion, and optionally induces a notification to a third party.107. The method of any one of clauses 92-103, wherein the device measures sleep disorders by working cooperatively with facial EMG activity.108. A method of detecting, diagnosing, treating or preventing depression in a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.109. A method of detecting, diagnosing, treating or preventing anxiety in a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.110. A method of detecting, diagnosing, treating or preventing psychiatric disorders in a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.111. The method of clause 110, wherein the psychiatric disorders is selected from a group comprising bipolar disorder, schizophrenia, psychosis, eating disorders and any combination thereof.112. The method of clause 111, wherein the eating disorder is selected from a group comprising anorexia, bulimia and any combination thereof.113. A method of detecting, diagnosing, treating or preventing binge eating in a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.114. The method of clause 113, further comprising the step of combining the use of the device with surgical weight loss, pharmaceutical weight loss therapies, bariatric surgery and any combination thereof.115. A method of detecting, diagnosing, treating or preventing binge alcohol consumption in a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.116. A method of usage and / or compliance of a drug treatment for a disorder in a subj ect comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.117. A method of detecting, diagnosing, treating or preventing a disease in a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.118. The method of clause 117, wherein the disease is selected from a group comprising blood glucose dysregulation, obesity, metabolic syndrome, TMD, stress, and any combination thereof.119. The method of clause 118, further comprising the step of detecting TMJ derangements.120. The method of any one of clauses 118 or 119, where the device detects effectiveness of TMD treatments and / or reconstructive surgeries.121. The method of any one of clauses 117-120, wherein the device works cooperatively with EMG sensors.122. The method of any one of clauses 118-121, wherein the device detects TMDs, TMD source or sources of orofacial pain.123. A method of detecting, diagnosing, treating or preventing neurodegenerative disorders in a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.124. The method of clause 123, wherein the neurodegenerative disorders are selected from a group comprising dementia, Alzheimer’s, bipolar disorder, tardive dyskinesia, post- traumatic stress disorder (PTSD), personality disorders (antisocial personality disorder, avoidant personality disorder, borderline personality disorder, dependent personality disorder, histrionic personality, disorder, narcissistic personality disorder, obsessive-compulsive personality disorder, paranoid personality disorder, psychotic disorders, hallucinations, delusions and any combination thereof.125. The method of any one of clauses 60-124, wherein the sensors are calibrated to mandibular movement with a camera.126. The method of any one of clauses 60-125, wherein the sensors are calibrated to mandibular movement with lidar imaging.127. The method of any one of clauses 60-126, wherein the device transmits subject TMJ information for telemedicine to diagnose disease, assess therapeutic recovery, diagnosis signals for preventative medicine.128. A method of predicting purchasing behavior of a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear;b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.129. The method of clause 128, wherein the device obtains the subjects location in relation to external locations.130. The method of clause 129, wherein the device provides information to the subject to provide at least one option to obtain a good or service.131. A method of performing cognitive behavioral therapy on a subject comprising the steps: a. positioning an electronic device of any one of clauses 1-59 in a subjects ear; b. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and c. relaying the signal to a communication processor.132. The method of clause 131 , wherein the device is calibrates based on facial expression of the user.133. The method of clause 131 or 132, wherein the device can be activated to initiate a CBT therapy regime.134. The method of any one of clauses 60-133, wherein the device further comprises Al capabilities.135. The method of any one of clauses 60-133, wherein the device further comprises Al in order to predict a diseases state.136. The method of any one of clauses 60-133, wherein the device further comprises Al in order to improve the device effectiveness.137. The method of any one of clauses 60-133, wherein the device further comprises Al in order to predict desired mandibular commands for device control.138. The method of any one of clauses 134-137, wherein the Al output relays the output to an external device.139. The method of any one of clauses 60-133, wherein the device further comprises Al in order to predict behavior of the user.140. The method of any one of clauses 60-133, wherein the device further comprises Al in order to predict activity of the user.141. The method of any one of clauses 139 or 140, wherein the device detects changes in delayed discounting behavior.142. The method of any one of clauses 141, wherein the device relays output with changes in delayed discounting behavior to an external device.143. The method of any one of clauses 134-142, wherein the Al output provides a decision strategy.144. The method of any one of clauses 134-143, wherein the Al comprises machine learning.

Claims

AMENDED CLAIMS received by the International Bureau on 24 January 2025 (24.01.2025)What is claimed is:

1. An electronic device comprising: a housing; at least one sensor in communication with the housing, wherein the at least one sensor is capable of obtaining a signal indicating the position of, and / or movement of, the temporal mandibular joint (TMJ), or a portion thereof.

2. The electronic device of claim 1, wherein the electronic device comprise a plurality of sensors.

3. The electronic device of claim 1 or 2, wherein the sensors work together to obtain the signal.

4. The electronic device of claim 1 or 2, wherein a data communication interface is within the housing and is configured to transmit and receive data to a communication processor.

5. The electronic device of claim 1 or 2, wherein the signal is used to identify a subset of TMJ movements including vertical, horizontal, retrusion, protrusion or any combination thereof.

6. The electronic device of claim 1 or 2, wherein the electronic device receives information regarding movement from the TMJ from by sensing deformation of the ear canal during mandibular movement using a sensor.

7. The electronic device of claim 1 or 2, wherein the sensor is capable of detecting signals selected from a group comprising resistance, impedance, current, capacitance, electrostatic field, electromagnetic field, sound, light and any combination thereof.

8. The electronic device of claim 1 or 2, wherein the sensor obtains measurements of deformation of the outer ear canal corresponding with TMJ activity, wherein the measurements are obtained from at least one of a microphone(s), a force transducer(s), a strain gauge(s), a capacitive sensor(s), a Hall-Effect sensor(s), a light sensor(s), an accelerometer(s), a force sensitive resistor(s), a piezoelectric sensor(s), field effect sensor(s), an ultrasoundsensor(s) a gyroscope(s), a magnetometer(s), EMG electrodes, optical sensors. LIDAR, infrared, NIR, visual spectrum, video camera, goniometer or any combination thereof.

9. The electronic device of claim 2, wherein the each of the plurality of sensors relay different signals.

10. A TMJ system comprising: c. a first electronic device of claim 1 and d. a second electronic device of claim 1.

11. The TMJ system of claim 10, further comprising a calibration component.

12. The system of claims 11, wherein the calibration component comprises calibration options selected from a group comprising: time, functionality, user, mandibular position, mandibular movement or any combination thereof.

13. A method of detecting foodstuff consumption in a subject comprising the steps: d. positioning an electronic device of claim 1 or 2 in a subjects ear; e. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and f. relaying the signal to a communication processor.

14. The method of claim 13, wherein the data communication interface can determine what category of foodstuff is being consumed.

15. The method of claim 14, wherein the foodstuffs is selected from a group comprising moderately thick, extremely thick, minced and moist, soft and bite sized and solid or any combination thereof.

16. The method of claim 13, wherein the sensor is capable of obtaining mastication behavior selected from a group comprising: measuring changes in swallowing function, appetite, eating habits, food preference, food cramming and combinations thereof.

17. A method of detecting sleep quality in a subject comprising the steps: d. positioning an electronic device claim 1 in a subjects ear; e. obtaining a signal from movement in the temporal mandibular joint via a data communication interface; and f. relaying the signal to a communication processor.

18. The method of claim 17, wherein the device measures the amount of sleep, time spent in different sleep stages, snoring, obstructive sleep apnea, sleep bruxism, nasal breathing, mouth breathing, nocturnal seizures, seizures, or any combination thereof.

19. The method of claim 17 or 18, wherein the device further comprises a pulse generator, capable to stimulate the hypoglossal nerve to induce protrusion of the tongue, to prevent or stop a sleep bruxism event.

20. The method of claim 19, wherein the device measures waking gasping events during, or following a sleep apnea event.

21. The method of claim 17, wherein the device during the subject being awake measures blood oxygen levels, heart rate, heart rhythm, blood pressure, body temperature and any combination thereof.

22. The method of claim 17, wherein the device during the subject being asleep measures blood oxygen levels, heart rate, heart rhythm, blood pressure, body temperature and any combination thereof.

23. The method of claim 17, wherein the device detects tiredness / exhaustion, and optionally induces a notification from a smart device.

24. The method of claim 17, wherein the device further comprises Al capabilities.

25. The method of claim 17, wherein the device further comprises Al in order to: predict behavior, provide a decision strategy, determine activity of the user and any combination thereof.

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