Methods and diagnostic systems for tinnitus detection and monitoring via physiological, non-physiologicalnd artificial cycle segmentation

Abstract

Objective tinnitus detection uses cycle-locked signal segmentation and coherent averaging. A tinnitus-related signal is acquired from a subject, and cycle markers corresponding to a repeating physiological cycle (e.g., cardiac cycle) are obtained. The acquired signal is segmented based on the cycle markers, aligned to a reference phase, and coherently averaged to enhance the signal-to-noise ratio of tinnitus-related components. In self-gating embodiments, cycle markers are derived from the acquired signal itself by detecting periodicity through autocorrelation or spectral analysis, allowing single-sensor operation. Spectral analysis of the enhanced waveform enables characterization of tinnitus etiology, including indicators of vascular stenosis. Comparison of pre-treatment and post-treatment measurements provides objective treatment efficacy monitoring. Systems implementing these methods range from clinical multi-modal configurations to simplified mobile single-sensor devices.

Description

[0001] METHODS AND DIAGNOSTIC SYSTEMS FOR TINNITUS DETECTION AND MONITORING VIA PHYSIOLOGICAL, NON-PHYSIOLOGICAL AND ARTIFICIAL CYCLE SEGMENTATION

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This document claims the benefit of priority to US Provisional Application Serial Number 63 / 742,547, filed January 7, 2025 entitled NOVEL ENHANCED TINNITUS SIGNAL DETECTION VIA PHYSIOLOGICAL, NON-PHYSIOLOGICAL AND ARTIFICIAL CYCLE SEGMENTATION and US Provisional Application Serial Number 63 / 952,989, filed January 2, 2026 entitled METHODS AND SYSTEMS FOR OBJECTIVE TINNITUS DETECTION AND MONTI ORING USING CYCLE-LOCKED SIGNAL SEGMENTATION AND COHERENT AVERAGING.

[0004] TECHNICAL FIELD

[0005] The present invention relates to medical diagnostics and monitoring systems. Specifically, it concerns methods and systems for detecting and analyzing tinnitus by integrating multiple physiological signals and cycles to enhance signal detection and analysis. It specifies an ecosystem where patients, researchers and medical professionals can virtually meet and evaluate tinnitus, collaborate, and design and plan treatments and monitor outcomes.

[0006] BACKGROUND OF THE IN VENTION

[0007] Tinnitus is a prevalent auditory condition characterized by the perception of sound in the absence of an external acoustic source. Affecting an estimated 10 - 15% of the global population, tinnitus can significantly impair an individual's quality of life. Symptoms include sleep disturbances, difficulty concentrating, emotional distress, and reduced overall well-being, which can lead to considerable psychological and functional challenges.

[0008] Tinnitus is broadly classified into two categories: objective tinnitus and subjective tinnitus. Objective tinnitus is where actual sound vibrations are generated within the body and then are transmitted to the ear, and represents less than 1% of all cases of tinnitus (i.e., prevalence is approximately 0.1-0.15%). These internally generated sounds result from physiological processes and can sometimes be heard by an examiner using a stethoscope or detected with sensitive microphones placed in the ear canal.

[0009] Objective tinnitus often arises from internal biological activities, such as tissue vibrations caused by muscular contractions or spasms near the ear or by fluid turbulence resulting from turbulent blood flow within arteries or veins. Vascular anomalies are among the most commoncauses of objective tinnitus, leading to turbulent blood flow that produces audible sounds. These vascular causes can be categorized into arterial and venous origins.

[0010] Pulsatile tinnitus is a subset of objective tinnitus where the perceived sound is synchronous with physiological rhythms, most commonly the cardiac cycle. Vascular causes of pulsatile tinnitus include venous sinus stenosis, dural arteriovenous fistulas, arteriovenous malformations, and other vascular anomalies that produce turbulent blood flow.

[0011] Arterial lesions are typically associated with pulse-synchronous tinnitus, having a relatively high pitch due to the higher velocities, and where the perceived sound synchronizes with the heartbeat. Common arterial causes include Dural Arteriovenous Fistulas (DAVFs) in which abnormal connections between dural arteries and venous sinuses are present, and Arteriovenous Malformations (AVMs) which are congenital malformations involving tangled blood vessels connecting arteries and veins. Other arterial lesions, such as arterial dissections or aneurysms that alter normal blood flow, can also be causative factors.

[0012] Venous lesions can present as pulsatile or non-pulsatile tinnitus and usually has lower pitch due to lower velocities. Pulsatile tinnitus from venous origins may be pulse-synchronous, respiratory-synchronous, or both. Common venous causes include the following.

[0013] Venous sinus stenosis results from a narrowing of the venous sinuses leading to increased flow velocity and turbulence. Venous sinus aneurysms in which dilations in venous structures cause abnormal flow patterns. And, venous hum is caused by turbulent flow in veins, like the internal jugular vein near the ear.

[0014] Vascular causes of tinnitus are particularly significant because they are often treatable. Interventions may include, surgical procedures to address and correct anatomical abnormalities, endovascular treatments, such as embolization to block abnormal vessels or stunting to reduce stenosis, or medical management: which addresses underlying conditions, like hypertension.

[0015] Successful treatment can lead to significant relief of tinnitus symptoms, markedly improving the patient's quality of life. Yet, despite the potential for treatment, detecting objective tinnitus presents several challenges, among them being the limited ability of traditional methods in objectively detecting and monitoring the condition. Auscultation with a stethoscope and the use of microphones have limited sensitivity, estimated to be less than 10% and may fail to detect subtle internal sounds.

[0016] Another drawback of conventional approaches is due to the variability of symptoms. In this regard, tinnitus symptoms can fluctuate with physiological changes like heart rate, blood pressure, or body position, making detection inconsistent.

[0017] Conventional treatments are often limited by dependence on specialized imaging for diagnosis of the underlying etiology of the tinnitus, relying on expensive, and not always readilyavailable imaging techniques, such as Magnetic Resonance Imaging (MRI), Magnetic Resonance Angiography (MRA), or Digital Subtraction Angiography (DS / A). These modalities identify anatomical abnormalities rather than detecting tinnitus itself, require specialized equipment and expertise, and may expose patients to ionizing radiation or contrast agents.

[0018] Subjective tinnitus is the most common form, and is a neurological condition without external sound or internal vibrations. It arises from aberrant neuronal activity within the auditory- pathways of the brain.

[0019] One such form is Neuronal Hyperactivity, characterized by abnormal firing patterns of neurons in the auditory cortex or along the auditory pathway. Perception of sound is another type, in which patients experience sounds like ringing, buzzing, or hissing, which cannot be heard by others.

[0020] With subjective tinnitus, there is a lack of external stimulus, so that no measurable sound waves or vibrations are present, making diagnosing of subjective tinnitus challenging.

[0021] At present, diagnosis relies heavily on patient self-reporting, which can be influenced by psychological factors and may lack consistency. This is limited by inapplicability to certain populations. For example, infants, young children, and individuals with cognitive impairments may be unable to provide reliable feedback. In addition, current diagnostic tools lack objective measures or biomarkers that can definitively indicate the presence or characteristics of subjective tinnitus.

[0022] Given the morbidity of objective tinnitus and the relatively safe and effective treatments for it, the lack of simple and reliable testing to diagnose and analyze tinnitus is a significant limitation. Also, the inability to objectively measure the effectiveness of treatments for tinnitus limits the routine use of many of these therapies and the development of new therapies. Given that tinnitus usually can not be objectively measured and analyzed, patients are often left without treatment, researchers have difficulty creating and characterizing treatments, and medical professionals often are not enabled to give meaningful diagnoses and treatment options to patients.

[0023] A significant drawback of prior art methods with regard to tinnitus detection and treatment resides in the limited sensitivity of traditional approaches. Existing tools like stethoscopes and microphones are often inadequate for detecting the subtle sounds associated with objective tinnitus.

[0024] Furthermore, reliance on imaging has attendant drawbacks insofar as diagnostic imaging is costly, not always accessible, and may expose patients to risks associated with contrast agents or radiation. These tools do not measure tinnitus directly but can reveal some lesions that can cause tinnitus but rely a high degree of expertise.

[0025] Subjectivity in assessments, i.e., heavy reliance on patient descriptions can lead to inconsistencies and inaccuracies, particularly in subjective tinnitus. There is presently a generallack of objective measurement methods. Difficulty in quantifying the severity and characteristics of tinnitus objectively hampers accurate diagnosis and treatment planning.

[0026] Additionally, inability to track temporal variations because of poor signal-to-noise ratios (SNR) in existing techniques make it challenging to monitor changes in tinnitus over time or in response to treatments.

[0027] Also, tinnitus symptoms can fluctuate with physiological cycles such as heartbeat and respiration, also complicating consistent assessment.

[0028] Ineffective detection methods can lead to delayed diagnosis: in identifying treatable causes of tinnitus, adversely affecting patient outcomes. Without objective measures for monitoring symptoms, assessing the efficacy of interventions becomes difficult, impeding the of treatment strategies. Lack of detailed characterization of tinnitus limits the ability to tailor treatments to individual patient needs, making it difficult to develop targeted interventions.

[0029] Ineffective detection methods cause many patients to suffer alone, relegating patients to subjective reporting of symptoms which is often not well received by medical professionals. Limited treatment options result in patients having difficulty finding medical professionals who specialize in treatment of tinnitus.

[0030] Despite ongoing research, there are significant unmet needs in the field of tinnitus diagnosis and management. There is a critical need for reliable, non-invasive techniques that can objectively detect and analyze tinnitus without solely relying on patient self-reporting or insensitive equipment.

[0031] A need for improved methods to enhance the detection of tinnitus-related signals, particularly those synchronized with physiological cycles, are necessary to overcome the limitations of current techniques, and would be highly desirable.

[0032] It is therefore an object of the invention to arrive at comprehensive assessment tools: that can quantify the severity, frequency, and characteristics of tinnitus, thereby facilitating accurate diagnosis, effective treatment planning and monitoring of treatment response.

[0033] Further, it an object to develop specific EEG tools to measure the brainstem response or the cochlear nerve response to tinnitus to evaluate the severity and characteristics of tinnitus so as to facilitate diagnosis, effective treatment planning and monitoring of treatment response.

[0034] It is a further object of the invention to provide accessible patient platforms and systems that allow patients to measure their own tinnitus and thus validate their symptoms, share their experiences with other patients and connect with researchers and healthcare providers can empower patients and promote collaborative care.It would therefore be desirable to provide a system and method by which an patient and / or a physician or technician could reliably objectively detect and monitor occurrences of tinnitus in a manner overcoming the drawback of the prior art outlined above.

[0035] SUMMARY OF THE INVENTION

[0036] According to these and other objects of the invention, methods and systems provide enhanced mechanisms for detecting and analyzing tinnitus by integrating multiple physiological signals and cycles. By utilizing advanced signal processing techniques, including segmentation and averaging based on physiological, non-physiological and artificial cycles, the invention enhances signal quality to improve tinnitus detection and analysis. The system according to embodiment of the invention also provides a comprehensive platform for patients, researchers, and medical professionals to optionally and advantageously collaborate, share data, and improve treatment methods and outcomes.

[0037] Briefly stated, the present invention provides methods and systems for objectively detecting, characterizing, and monitoring tinnitus by exploiting the repetitive nature of physiological cycles to enhance signal-to-noise ratio through cycle-locked segmentation and coherent averaging.

[0038] Integration and incorporation of one or more advanced signal processing technologies, artificial intelligence, and / or multi-modal data integration enhances detection and provides deeper insights into tinnitus mechanisms.

[0039] Deep brain auditory response and cochlear nerve response recordings relay and record the electrical activity of lOOs-lOOOs of auditory stimuli and then use averaging and other advanced signal processing techniques to reveal the neural activity related to the auditory' stimuli. For pulsatile tinnitus, the sounds are generated cyclically with the heartbeat so that recording the brain stem EEG or the cochlear nerve EEG through 100s- 1000s of cycles and using the same advanced signal processing including averaging each of these cycles can reveal the underlying neural activity, vibrations, sound or other signals initiated by the pulsatile tinnitus. Similarly, recording through numerous cycles of other physiological, non-physiological and even artificial cycles can reveal tinnitus signals and is believed effective in addressing many of the current limitations:

[0040] An embodiment according to the invention utilizes physiological cycle synchronization in which natural physiological cycles, such as the heartbeat or respiration, to segment and average tinnitus signals such as EEG, cochlear nerve activity, vibrations, or sound can enhance the signal- to-noise ratio, revealing subtle tinnitus-related activity. When tinnitus is initiated, augmented or reduced by a physiological cycle such as heartbeat, then segmentation of the signal from tinnitus sensors such as electrical sensors, EEG, audio sensors, vibration sensors, turbulence sensors, andflow pattern sensors can yield multiple repetitions of the signal that can be used in signal processing.

[0041] Another embodiment uses non-physiological cycle synchronization in accordance with which non-physiological cycles are utilized, such as artificial time intervals, for segmentation of the signal from tinnitus sensors such as electrical sensors, EEG, audio sensors, vibration sensors, turbulence sensors, and flow pattern sensors which can yield multiple repetitions of the signal that can be used in signal processing of tinnitus signals including those for non-pulsatile tinnitus. In the case of cochlear nerve or EEG signals, a system such as this will measure subjective tinnitus that imitates neuronal activity.

[0042] Artificial cycle synchronization can advantageously be utilized with induced stimulation such as tissue vibration of tissues of the head, neck or body, or by fluid disturbances such as mixing, induced turbulence, changes in viscosity via injection of various fluids, pressure injections, or changes in body positioning. Then, segmentation of the signal from tinnitus sensors such as electrical sensors, EEG, audio sensors, vibration sensors, turbulence sensors, and flow pattern sensors are effectively used to yield multiple repetitions of the signal that can be used in signal processing.

[0043] An aspect of the invention advantageously involves applying signal averaging techniques similar to methodologies used in Auditory Brainstem Response (ABR) testing, to internal physiological events, where repetitive stimuli and signal averaging improve detection of neural responses,.

[0044] Another aspect of the invention employs multi-modal signal integration, in which combined data from electroencephalography (EEG), electrocardiography (EKG), auditory signals, and bone vibration measurements can provide a more comprehensive understanding of tinnitus.

[0045] An embodiment of the invention utilizes artificial intelligence and advanced analytics. Such feature advantageously implements machine learning algorithms for signal identification, analysis, and pattern recognition to further enhance detection accuracy and provide predictive insights for treatment outcomes.

[0046] An optional feature according to the invention includes calibration by auditory stimuli in which the tinnitus signals such as the EEG, cochlear nerve, and brainstem electrical activity are calibrated via auditory transmitters (e.g., ear phones) where the electrical responses to various amplitudes and frequencies are charted and then compared to the tinnitus signals in the same or different patients.

[0047] In accordance with an advantageous embodiment, recordings of tinnitus signals can be shared between patients, researchers and medical professionals facilitating treatments, research and medical care. It is noted herein that addressing the challenges in tinnitus detection andanalysis, and optimizing the results obtained therefrom, requires an innovative, multi-faceted approach. By integrating neural and physiological monitoring, leveraging physiological cycles for signal enhancement, and employing advanced signal processing techniques, it makes possible the development and refinement of objective, non-invasive methods for tinnitus assessment. Such advancements will potentially revolutionize the diagnosis and management of tinnitus, leading to significant improvements in patient care, enabling targeted treatments, and advancing the understanding of this complex condition.

[0048] Integration of these methods into a community-shared system where patients, researchers and medical professionals can interact will provide a critical tool in leveraging the tinnitus detection, measurement and characterization to improve patient outcomes, research and development and treatments would be highly desirable.

[0049] The present invention introduces a comprehensive system for the objective detection and analysis of tinnitus. By integrating multi-modal signal acquisition including EEG, EKG, auditory, and vibration signals and utilizing physiological, non-physiological and artificial cycles for signal segmentation and averaging, the system significantly enhances signal quality. Advanced signal processing techniques, including adaptive filtering and Al-driven analysis, enable accurate detection and characterization of tinnitus. Additionally, the invention provides a platform that connects patients, researchers, and medical professionals, fostering collaboration and improving treatment outcomes.

[0050] A full system according to a particularly advantageous embodiment of the invention includes a client-side application comprising one or more of the following. A signal production and collection control capable of managing signal acquisition and for providing analysis to patients, researchers, and manufacturers. Optional educational tools including videos about tinnitus and its management. Another advantageous feature would allow bulletin board access to patients, researchers, and medical professionals to post and connect in various forums. Other feature include a Graphical User Interface (GUI) For initiating tinnitus measurements, and a communication system which enables users to search for and connect with others. With regard to system platforms, a selection from multiple interfaces can be provided in the forms of a simplifi ed interface for patients and a more complex system for researchers and medical professionals with additional analysis tools.

[0051] The full system referred to above will further advantageously includes a server-side application which includes one of more of the following features. A user database for patients, researchers, medical professionals, and / or industry partners such as device manufacturers. Internet connectivity for connecting the user database and application to client applications on users' phones, tablets, computers, or other computing devices. A content server providing educationalmaterials, advertisements, and bulletin board access to client applications. And, advantageously include advanced analysis tools comprising higher-level analysis and Al tools.

[0052] Another feature of the invention will allow multi-modal signal integration allowing simultaneous recording of one or more of EEG, EKG, auditory signals, and / or bone vibration signals, as well as physiological cycle integration of one or more of cardiac, respiratory, and other cycles. Non-physiological cycle integration is also provided as an option, such as time-based or Al-detected patterns. Artificial cycle integration, i.e., cycles created by inducing vibrations, pressure, turbulence, velocity and lesion configuration would also be possible to create artificial pulsations of tinnitus signal that can be segmented and analyzed.

[0053] Enhanced signai-to-noise ratio (SNR) is achieved through synchronized (coherent) averaging, filtering and other advanced signal processing tools.

[0054] In accordance with advantageous embodiments, various modes of measurement and analysis are selectively employed to yield desired results. These will include, as appropriate to the type of tinnitus involved, physiological cycle utilization, including heartbeat-based segmentation for pulse-synchronous tinnitus, respiratory-based segmentation for breathing-related variations, additional physiological rhythms for specific tinnitus types and combination of cycles for complex tinnitus presentations.

[0055] Non-physiological and artificial cycle utilization will be advantageously selected comprising random Time Interval Segmentation For non-pulsatile tinnitus. Artificial cyclical changes in pressure, flow velocity, turbulence, or lesion configuration will optionally be induced for pulsatile or non-pulsatile tinnitus.

[0056] Another advantageous embodiment of the invention will incorporate advanced signal processing, including multi-cycle averaging to improve SNR of various tinnitus signals, including EEG, cochlear nerve signals, cochleography, sound, and vibrations. Other signal processing approaches may also include adaptive filtering, artificial intelligence methods for signal identification, analysis, prognosis, treatment evaluation, and prediction. Also, time and frequency domain analysis, independent component analysis for signal isolation and tinnitus signal calibration via audio or other signal transmitters may also be used.

[0057] A software and control of system advantageously utilizes a server application to allow access to a user database, optionally provided in various platforms of various levels suited to patients, medical professionals, or researchers. A bulletin board would be optionally available comprising a media server: for videos, advertisements, and other data. An optional feature will facilitate patients, professionals and researchers to connect with one another via a matching algorithm.A patient interface includes options for access to such things as instructional videos, bulletin board access, and tinnitus detection capabilities. Researcher and medical professional application lb offers, for example, advanced tinnitus analysis capabilities, bulletin board access, and content creation tools.

[0058] Control software initiates and records ABR, cochlear signals, EEGs, electrical signals, EKG, 3 vibrations, and audio sensing and production.

[0059] A signal acquisition system advantageously achieves primary signal recording using a combination of integrated sensors and transmitters The system utilizes combination sensor / transmitter devices that may include EKG, EEG electrodes or high-fidelity microphones coupled with audio or vibration transmitters. These devices are designed for simultaneous recording and transmission of physiological and auditory signals relevant to tinnitus detection.

[0060] One such sensor is adapted for placement in the ear, and comprises a combination device which when placed within the ear canal, captures neural activity (EEG signals), auditory signals, and internal sounds associated with tinnitus. This placement allows for high-fidelity signal acquisition close to the source of tinnitus perception.

[0061] The ear sensor also advantageously includes an outer earbud component to maintain sterility and enable reuse of the combination device. This component acts as a protective barrier between the sensor / transmitter device and the ear canal, ensuring hygienic use across multiple sessions or users.

[0062] Specific Connection Mechanism: The outer earbud component requires a unique connection to the combination device. This connection is designed to be both functional and secure, ensuring that the components fit together precisely while maintaining function. The connection mechanism may include specialized fittings, locking mechanisms, or magnetic connectors that align and secure components.

[0063] In cases where the outer earbud component includes an EEG electrode contact, it must provide reliable electrical connectivity to the rest of the combination device. This is achieved by incorporating conductive materials and contact points within the fitting mechanism, allowing electrical signals to pass seamlessly from the electrode to the signal processing unit.

[0064] Some design considerations for optimal use include customized fit:. In this regard, the outer earbud components will be optionally made available in various sizes and shapes to accommodate different ear anatomies, providing a comfortable and secure fit for users.

[0065] Another design consideration is that the connection between the outer earbud and the combination device is engineered to prevent accidental dislodgement during use. This ensures consistent signal acquisition and user comfort.Material selection is also a consideration, and biocompatible and hypoallergenic materials are advisably used for all components that come into contact with the user's skin or ear canal to prevent irritation and allergic reactions.

[0066] The above mentioned combination devices are advantageously capable of capturing multiple types of signals simultaneously, such as, for example, EEG Signals recording neural activity from the cochlear nerve or auditory pathways. Also capturing auditory signals comprised of internal sounds or vibrations related to tinnitus via high-fidelity microphones.

[0067] Integrated transmitters within the devices send the acquired signals to the client application for processing and analysis. Transmission methods may include wired connections or wireless technologies like Bluetooth Low Energy (BLE).

[0068] For segmentation, physiological marker recording may be achieved by use of EKG Sensors. An advantageous embodiment employs simplified EKG components comprised of single-lead or multi-lead EKG sensors designed for ease of use. These may be integrated with the combination devices or function as standalone units. User-friendly attachment is facilitated by use of electrodes with adhesive pads or wearable bands for quick and accurate placement on the chest or limbs. Wired or wireless connectivity options ensure secure attachment for reliable data transmission to the client application.

[0069] Respiratory monitoring systems comprising sensors for respiratory cycle detection can optionally include wearable devices, such as chest straps or adhesive sensors that measure breathing patterns, and can be integrated with other wearable components for seamless data acquisition.

[0070] In addition to heart rhythm and respiration rate, other physiological cycle sensors and physiological monitors can be used. These include, pulse oximetry for measuring blood oxygen levels and pulse rate, and motion sensors to detect body movements that may correlate with tinnitus symptoms.

[0071] Integration and data synchronization of signals is an important aspect of the invention. To ensure accurate time alignment, all sensors and transmitters are synchronized to ensure that data from different modalities can be accurately correlated during analysis.

[0072] Centralized data collection is used, meaning that signals from the combination devices and physiological markers are collected and processed by the client application in real-time. Data quality assured by signal validation by included system algorithms to verify signal integrity and quality before analysis. Also, artifact detection is also advantageously included in the system, providing automatic identification and exclusion of corrupted or noisy data segments.

[0073] Reuse and maintenance is addressed as follows.Disposable components are used where appropriate. For example, the outer earbud components may be designed as disposable items to maintain hygiene between uses. Reusable components are constructed to withstand standard sterilization methods without degrading functionality.

[0074] To allow modularity and upgradability, interchangeable parts are used when feasible. Such components can be easily replaced or upgraded, allowing for customization based on user needs or technological advancements. Furthermore, a system according to embodiment of the invention system is advantageously designed to be compatible with various devices and sensors, promoting flexibility and scalability.

[0075] Calibration and validation of system measurements can be established by methods which include for example, auditory 24-bit establishment. This approach uses controlled stimulus presentation, and / or ABR and cochlear nerve response measurement. System Sensitivity Calibration is also feasible by measuring variations of the tinnitus signals in response to auditory variations to characterize amplitude, frequency, and other signal characteristics.

[0076] Another approach is use of comparative analysis which includes comparison with known stimulus response, tinnitus signal characterization, and / or frequency content analysis.

[0077] Core system components of a suitable contemplated system to achieve the objects of the invention will include consideration of an effective EEG Recording Configuration.

[0078] A standard ABR electrode placement may be used in this regard, which includes an active electrode on the vertex (Cz), reference electrodes positioned on the mastoids (Al, A2) or earlobes and a ground electrode on the forehead (Fpz)

[0079] For cochlear response configuration, electrode placement will be in contact with the tympanic membrane or in the ear canal, a reference electrode placed on the mastoid and a ground electrode on the forehead.

[0080] An audio stimulus system will generally comprise insertable earphones for controlled sound delivery advantageously having calibrated audio output capabilities. It may include standard audiometric frequencies, click stimulus generation and / or tone burst capabilities.

[0081] A feature for achieving acceptable cardiac cycle recording will include a basic 3-lead EKG configuration, include R-Wave detection to ensure precise timing. Further, the system advantageously includes continuous cardiac cycle monitoring and real-time QRS complex identification.

[0082] A system according to an embodiment of the invention includes Control System and Electronics comprising a suitable Computing Device, such as a computer, tablet, or smartphone. Also including amplifiers for EKG, EEG, audio, and vibration sensors. The system furthercomprises, as needed, analog-to-digital converters and software and control for signal collection and analysis.

[0083] To achieve EKG-Based Signal Segmentation, the system will advantageously include QRS Complex Detection involving Continuous Monitoring of the EKG signal, Real-Time QRS Complex Identification, an R-Wave peak detection algorithm, timing marker generation for each heartbeat and validation of R-R Intervals for consistency.

[0084] A Signal Segmentation Process in accordance with an embodiment of the invention advantageously includes time-locking to R-Wave peak. The process further will advantageously include Defined segment window selection of pre-R-Wave interval or post-R-Wave interval. Further optimizing features include segment length optimization and consistent segment alignment verification.

[0085] With regard to respiratory-based or other physiological cycle-based signal segmentation, detection and segmentation processes will advantageously utilize a respiratory monitor for respiratory cycle recording, and / or other biological monitors for additional physiological cycles. Cycle Detection Using peak detections or standard algorithms, segmentation of tinnitus signal based on detected physiological cycles, segmentation by non-physiological cycles based on time, Al detection, or other pattern recognition methods will also be considered.

[0086] The mathematical basis for the segmented Signal Averaging Technique contemplated for use in furtherance of the goals of the invention to improve Signal-to-Noise Ratio (SNR). Segmentation averaging is believed to increase the SNR by a factor of the SqrRt of N, where N is the number of averaged segments. For example, 100 segments improve SNR by a factor of 10, and 400 segments improve SNR by a factor of 20. Random noise reduction is achieved through averaging while preserving time-locked signals.

[0087] For optimal accuracy, the averaging process advantageously includes an accumulation of aligned segments, running average calculations, progressive SNR Improvement Tracking and statistical Validation of signal Improvement. Quality control measures will advantageously include one or more of the artifact rejection criteria, segment quality assessment, statistical outlier detection and / or signal stability monitoring

[0088] For display of time domain representations, a primary signal display will conveniently employ standard ABR / Cochlear Response Format, wherein voltage (V) vs. time (ms) is shown. The display will advantageously include multiple trace overlay capabilities, standard time windows (0 10 ms, 020 ms), amplitude scale standardization and waveform peak labeling.

[0089] To allow calibration comparisons, an amplitude reference display will show an overlay of responses to known stimuli. The display advantageously indicates multiple intensity levels (dB SPL / HL), direct amplitude comparison, peak-to-peak measurements and latency measurements.Visual comparison tools are advantageously provided in various forms including split-screen viewing, overlay capabilities pertaining to tinnitus-related response, calibration responses and / or normative data. Other features for comparison will include adjustable scaling, interactive cursors, peak alignment tools and / or time and frequency domain windows and comparisons.

[0090] An embodiment of the invention includes a feature providing frequency domain analysis by spectral representations or frequency comparison methods. For spectral representations, Fast Fourier Transform (FFT) Displays may be used, as well as power spectrum analysis, frequency distribution plots, spectral energy comparisons and / or phase analysis. Where domain analysis is by use of frequency comparison methods, overlay of spectral components including tinnitus-related spectra, known frequency responses and / or multiple stimulus conditions can be employed. Also, the system can operate to provide frequency peak identification, bandwidth analysis, harmonic content analysis,

[0091] A mobile system provided as a commercial embodiment advantageously includes an integrated ear sensor and a combined electrode / sound delivery system comprising an in-ear canal electrode for cochlear response, an integrated sound port for stimulus delivery. The combined system is advantageously comprised of biocompatible materials and have disposable or reusable options, and will provide a comfortable fit design. Optional features include microphone integration, ambient noise monitoring and ear canal impedance checking.

[0092] The commercial mobile version will also include a simplified EKG Component, achieved by providing a single-lead EKG Configuration comprising a small form factor, offered as wireless or wired connectivity versions. The commercial version with also advantageously provide other features like a long battery life, an easy attachment method, a additionally have a user-friendly design including clear placement indicators, Simple connection verification and Battery status monitoring (if wireless).

[0093] In accordance with a particularly advantageous embodiment, a mobile interface unit will comprise a Smartphone-Based System. Such system will have iOS / Android compatibility, Bluetooth connectivity, Real-time data processing and Local data storage. A hardware interface would include Small adapter (or a dongle adapter) if needed, signal conditioning, analog-to-digital (A / D) conversion and power management.

[0094] According to an embodiment of the invention hardware configurations include a common core electronics module comprising signal acquisition components, data conversion systems and an integrated audio system as identified below.

[0095] The EEG Amplification System comprises a Low-noise instrumentation amplifier, High input impedance, adjustable gain settings, common-mode rejection, bandwidth of 0.1 Hz to 3,000 Hz and noise floor < 1 µV RMS.The EKG Amplification System will include, for example, a single-lead configuration, provide medical-grade amplification, and provide built-in filtering and 50 / 60 Hz notch filter options.

[0096] Data conversion systems of the hardware configurations mentioned above include Analog-to-Digital Conversion (ADC) and Digital-to-Analog Conversion (DAC). The ADC ideally comprises

[0097] an EEG channel with 24-bit resolution, an EKG channel with 16-bit resolution, a sampling rate up to 48 kHz and multiple channel synchronization. The DAC ideally comprises 24-bit resolution, support for multiple sampling rates, low distortion output and calibrated output levels.

[0098] The Integrated Audio System included in the hardware configurations referred to above handles sound generation and acoustic delivery, Hardware for sound generation includes calibrated speaker driver, a Sound tube interface which operates in a frequency range of 20 Hz-20 kHz, and level control between 0 and 100 dB SPL. Design parameters for acoustic delivery will include sound tube specifications, length-optimized design, minimal acoustic distortion and frequency response compensation.

[0099] In accordance with an ABR configuration embodiment, scalp EEG components comprise an electrode configuration including an active electrode (Cz - vertex, reference electrodes (Al, A2 - mastoids) and a ground electrode (Fpz - forehead). The medical grade electrodes are advantageously utilized with low impedance design., allowing easy application and stable contact maintenance. A sound delivery system

[0100] provided includes a speaker assembly comprising a miniature speaker the specifications of which optimally include a frequency response: 20 Hz-20 kHz, low distortion characteristics and calibrated output levels.

[0101] Further included in the sound delivery system is a sound tube formed of medical-grade tubing and presenting an optimized length and diameter, acoustic impedance matching and frequency response compensation.

[0102] An embodiment of software for a system according to the invention will allow selection of applicable skill-appropriate operation modes.

[0103] One of these operational modes is a consumer / patient mode which provides basic features including simplified controls, such as a user interface providing a step-by-step setup wizard, clear visual instructions, video tutorials, progress indicators and status notifications. The consumer / patient mode will also feature guided operation, comprising equipment placement guidance, connection verification, signal quality checks, recording duration tracking and simplified troubleshooting. With regard to data collection, the mode will also advantageously feature automated protocols including pre-configured settings, quality monitoring, duration management,artifact detection and automatic retries if needed. A results display will provide such elements as basic visualization (for example, a simple signal presence indicator and relative strength indication), basic trending (such as, e.g., historical comparisons) and notifications (including detection confirmations, quality alerts, recording completion, and follow-up reminders).

[0104] Another of the modes is a professional mode, intended for physicians and other trained medical practitioners, and will feature an advanced Interface with comprehensive controls including, for example, parameter adjustments, protocol customization, advanced settings, raw data access and quality metrics.

[0105] Patient management capability will allow data reception pertaining, for example, to patient recording review, signal quality assessment, historical tracking and comparative analysis, and also allow patient communication for, e.g., direct messaging, result sharing, appointment scheduling, treatment tracking, etc..

[0106] A Community Platform feature of the invention will include a server-side user management system for accessing patient accounts, provider accounts, administrator accounts, moderator accounts, etc., and managing aspects of profile management including, for example, basic demographic, medical history options,

[0107] privacy settings, communication preferences and connection management.

[0108] An advantageous option is provided by another embodiment of the invention which provides a bulletin board system, including content management capabilities, allowing for tinnitus recording sharing, experience narratives, treatment discussions, question-and-answer sections, success stories, etc..

[0109] Interactive features would include, for example, recording annotations, comment threads, rating systems, tagging capabilities, search functionality, and so forth. A data repository' might include a recording base for storage of anonymized tinnitus recordings, signal characteristics, analysis results, treatment correlations, outcome tracking, etc.. The repository' may also include an experience database for storage of, for example, treatment histories, symptom patterns, trigger factors, management strategies and success metrics.

[0110] As always, security and compliance are important issues, and embodiment of the invention will incorporate data protection and be HIPAA Compliant by employing encryption protocols, access controls, audit trails and data backup systems. Privacy controls will be in place for user consent management, data sharing permissions, anonymous posting options and content moderation tools.

[0111] The above, and other objects, features and advantages of the present invention will become apparent from the following description read in conjunction with the accompanying drawings.BRIEF DESCRIPTION OF THE DRAWINGS

[0112] FIG. 1 is a schematic depiction of a system according to an embodiment of the invention; FIG. 2 is a block flow chart detailing workflow processes signal processing workflow methodology for tinnitus signal detection and analysis;

[0113] FIG. 3 is a schematic diagram showing hardware configuration for signal acquisition; FIGs. 4A - 4C depict electrode placements for EEG and EKG recording;

[0114] FIG. 5 is an illustration showing the processing to enhance tinnitus signal detection through segmentation and averaging using heart rhythm;

[0115] FIG. 6 shows an example of a client-side application interface for patients and professionals;

[0116] FIG. 7 is a server-side architecture diagram of a server infrastructure and community platform;

[0117] DETAILED DESCRIPTION OF THE INVENTION

[0118] Referring now to FIG. 1, a schematic block diagram detailing a system overview according to an embodiment of the invention is depicted and designated generally by reference numeral 10. System 10 will be available to users as a comprehensive tinnitus detection and analysis system. As shown therein,

[0119] system 10 includes a block 1 representing a client-side application, a signal acquisition block 2, and a server-side application represented by block 3.

[0120] Client-side application 1 would be functionally available, for example, on a smartphone, tablet, or computer. A screen thereof would optionally show, by example, two interfaces including a patient interfacela representing a simplified user interface (UI) with basic controls, and a professional interface lb, comprising an advanced UI with detailed controls and analysis tools suited to the more sophisticated user’s expertise. Examples of labeled features might include (while not all depicted) such features as " Signal Production and Collection Control", " Educational Tools", " Bulletin Board Access" and / or “Communication System".

[0121] In the depicted example of FIG. 1, signal acquisition block 2 shows various included signal acquisition modules comprising an EEG Sensor Module 2a which will, for example, comprise electrodes placed on the scalp (vertex, mastoids, forehead) or in the ear canal of the patient, are conveniently connected to the client device via wires or wireless connection. An EKG Sensor Module shown in block 2b also shown will include electrodes attached to the chest area (single-lead or 3-lead configuration, as detailed later herein). Block 2c represents an auditory signal module comprising earphone(s) inserted into the ear canal for sound delivery, and includes an integrated microphone for capturing auditory signals.While not depicted in FIG. 1, a bone vibration sensor module including sensors placed on the mastoid bone or forehead, or contacting teeth of the patient may optionally be utilized to receive conducted vibrations.

[0122] Server-side application 3 may optionally include display of, for example, a cloud or server icon for appropriate selection by a user, and is interconnected to a client-side application 1 via the internet.

[0123] Server-side application 3 includes at least one user database 3a with, for example, icons (not shown) representing different user types, i.e, patients, researchers or medical professionals. A content server 3b provides, for example, educational materials and advertisements. Server-side application 3 also optionally includes a bulletin board system 3c for community interaction. While not shown, server-side application also optionally provides advanced analysis tools and Al modules for data processing and insights.

[0124] As seen in FIG. 1 and depicted by the flow arrows shown, data signal acquisition modules 2a, 2b, 2c in signal acquisition block 2 are sent to client-side application 1 which are communicated from client-side application 1 to server-side application 3 (bidirectional arrows indicating communication transmissions between signal acquisition block 2 and client-side application 1, and between client-side application 1 and server-side application 3).

[0125] It is noted that key functionalities of server-side application 3 advantageously utilizes enhanced signal processing and multi-modal integration for accuracy of data acquisition and analysis.

[0126] Turning now to FIG. 2, a block flow chart is depicted, detailing signal processing workflow methodology for tinnitus signal detection and analysis. A start point block 21 indicates the initial starting point in the processing workflow. Sequential procedures are connected by arrows indicating the flow of the process.

[0127] A signal acquisition block 22 represents the input of collected physiological signals (EEG, EKG, auditory, bone vibration). Cycle detection is then processed in block 23, and comprises physiological cycles, e.g., cardiac cycles detected from EKG or respiratory cycles detected from respiratory monitoring,

[0128] Non-physiological cycles may also be used in signal acquisition block 22, and include, for example, time-based intervals or patterns developed by Al algorithms.

[0129] In a signal segmentation block 24, raw signals collected in signal acquisition block 22 are divided into segments based on detected cycles in block 23. The segments are aligned according to cycle markers (e.g., R-wave peaks) for proper signal averaging of the aligned segments subsequently performed in block 25. As is well accepted, SNR improvement is proportional to the square root of the number of segments used. / Additional signal enhancement may be achievedusing one of more of application of noise reduction algorithms, adaptive filtering and artifact removal techniques.

[0130] Following signal segmentation in block 25, signal analysis is performed in a subsequent block 26, wherein functions, such as time domain analysis, are performed to generate analogs, such as waveform graphs and frequency domain analysis, to generate spectral plots. Analysis can also include cross-modality correlation, linking data from different signal types, and Al-based pattern recognition.

[0131] Visualization results are then output in a results output block 27, conveniently in the form of graphs and / or charts displaying analysis results. Additionally, summary reports can optionally be generated for users.

[0132] Finally, the process terminates in an end point block 28.

[0133] Referring now to FIG. 3, a signal acquisition hardware configuration diagram is schematically depicted, and comprises a central device 31, provided conveniently, for example, in the form of a smartphone or tablet acting as a mobile interface unit. A display screen 31a shows the client application interface.

[0134] Connected to central device 31, conveniently by wired or wireless communication, are various sensors, including an integrated in-ear device 32, components of which include an in-ear electrode 32a positionable to contact the ear canal or tympanic membrane, a sound delivery port 32b for auditory stimuli and a microphone 32c for capturing internal sounds, and which are identified on the display screen 31a of central device 31 as titles such as, for example, " Cochlear Response Recording", " Sound Stimulus Delivery" and " Auditory Signal Capture."

[0135] A Simplified EKG device 33 is also connected to central device 31, which includes electrodes 33a attached to the chest of the tinnitus patient conveniently provided in a small module which includes a device for signal transmission. Another sensor connected to central device 31 can also be provided in the form of a bone vibration sensor 34 suited for placement on the mastoid bone behind the ear.

[0136] Connection options for each of the sensors connected to central device 31 are by wireless mode (indicated with signal waves in FIG. 3), or by wired connection depicted by broken lines.

[0137] Turning to FIGs. 4A-4C, various electrode placement configurations are depicted.

[0138] FIG, 4A is a schematic representation of a front view of a human head 40 depicting placement of electrodes for EEG Recording according to standard ABR electrode placement protocol (eyes, nose and mouth omitted for clarity and simplicity). As such, an active electrode (Cz) 41a shown as the dot at the top center of the scalp. A ground electrode (Fpz) 41b is also provided, shown as the dot on the forehead below active electrode 41a. Reference electrodes 41c, 41d are depicted as dots on both mastoid processes behind the ears.FIG. 4B schematically depicts cochlear response electrode placement relative to a human head 42 shown in side view. An in-ear electrode 43 is inserted into the ear canal, and a reference electrode 44 is placed on the mastoid bone. A ground electrode 45 is placed on the forehead. (Illustration shows the electrode reaching towards the cochlea).

[0139] FIG. 4C is a partial frontal view of a human torso diagraming EKG electrode placement for simplified use. A single-lead EKG configuration is shown by example, in which the positive electrode 47 is positioned below the left clavicle, the negative electrode below the right clavicle, and the ground electrode at the lower left abdomen. Wires conveniently connect electrodes 47, 48, 49 to an EKG module (not shown).

[0140] Referring to FIG. 5, signal segmentation and averaging to improve SNR (Signal-to-Noise Ratio) by a factor proportional to the square root of the N number of segments is graphically depicted in a sequential series of graphs in panels A-D.

[0141] Panel A shows Raw EEG Signal, the wavy line representing EEG data over time. In practice, for visual analysis, the time axis (x-axis) will conveniently labeled in milliseconds, and the voltage axis (y-axis) labeled in microvolts (µV).

[0142] Panel B depicts the collected EKG signal with R-Wave peaks, appearing as the clear spikes representing R-Waves at regular intervals. Vertical broken lines (or markers) in panel B are indicated a each R-Wave peak. The graph of panel B is in time alignment with Panel A to insure proper segmentation.

[0143] Panel C multiple EEG segments aligned beneath each other (3 being shown). Each segment corresponds to an R-wave marker. Segments shown between two vertical broken lines space apart by the segment time.

[0144] Panel D represents the averaged EEG signal. The single waveform shows noticeably reduced noise using the approach according to the invention for enhance results indicating tinnitus-related activity.

[0145] Turning now to FIG. 6, various user interface screens are shown for patients (part A) and professionals (part B).

[0146] Patient interface A includes a home screen 60, with selection buttons, examples of which follow. A button 60a reads " Start Tinnitus Measurement," a button 60b reads " Educational Videos," and a button 60c reads " Community Forum," Simple icons representing each function can be shown if desired.

[0147] A measurement screen 61 displays instructions like " Please attach the sensors as shown" with visual indicators which show connection status (e.g., green checkmarks). Measurement screen 61 also includes a start button labeled " Begin Recording."If tinnitus is detected, a results screen 62, on which a gauge or meter showing relative signal strength will announce “Tinnitus detected.” Various options will be presented including: " Save Results," " Share with Doctor, " " View Recommendations," etc..

[0148] FIG. 6, Part B depicts a more sophisticated professional interface. Professional interface B includes a dashboard screen: showing, for example, a list of patient names or IDs with recent, notifications for new data, etc.. An analysis screen is 70 is provided displaying thereon detailed graphs 72 including time-domain waveforms and frequency-domain spectra. Screen 70 also includes controls for adjusting analysis parameters and selecting different data sets, and buttons 72 for " Save Analysis," " Export Data" and " Generate Report."

[0149] Part B also includes a patient communication screen 73 providing a messaging interface with chat history, options to schedule appointments, sections for notes and treatment plans, etc.

[0150] Referring now to FIG. 7, a server-side architecture diagram is shown, and embraces the server infrastructure and community platform accessible by, for example, a mobile device or other internet-capable terminal. Components of the server-side application comprise a user management system 101 comprised of databases represented in FIG. 7 as stacked cylinders, having separate sections for patient accounts, provider accounts, administrator accounts, moderator accounts, etc.

[0151] A data repository 102 includes storage units labeled " Anonymized Recordings," " Analysis Results," and “Treatment Histories"

[0152] A bulletin Board System: 103 is optionally provided with icons representing forums, threads, and posts. Including features like " Experience Sharing,” " Q& A Sections" and " Treatment Discussions."

[0153] A security and compliance module 104 is provided, identified for example, by a shield icon 104a labeled " HIPAA Compliance." Features advantageously include " Encryption Protocols," " Access Controls" and " Audit Trails" Arrows from smartphones / computers 1 to the server-side application 100 (bidirectional communication indicated). A data analytics module 105, represented by a processing unit symbol 105a, is also provided, and is connected to the data repository, and will be labeled " Al and Machine Learning Algorithms."

[0154] The tinnitus-related signal is segmented into a plurality of segments based on the detected cycle markers. Each segment corresponds to a defined temporal window relative to a cycle marker.

[0155] In the embodiment described above, which employs cardiac-gated analysis, each segment spans one complete cardiac cycle, beginning at a fixed temporal offset relative to the R-wave (or other cycle marker). The segment length may be determined based on the detected cardiac period or may be set to a fixed duration encompassing the expected cardiac cycle length.Segments may alternatively span a fraction of a cardiac cycle corresponding to a phase of interest. For example, segments may be defined to capture the systolic phase (approximately 50-350 ms post-R-wave) when turbulent flow signals are expected to be maximal.

[0156] Prior to averaging, segments are aligned to a reference phase within the cycle. In a basic embodiment, alignment comprises temporal registration based on the detected cycle markers, such that corresponding phases of each cardiac cycle are superimposed.

[0157] Advantageously, alignment further comprises cross-correlation-based refinement. Each segment is cross-correlated with a template waveform (which may be initialized as the mean of all segments), and circular shifting is applied to maximize correlation. This compensates for jitter in cycle marker detection and physiological variability in cycle timing.

[0158] The aligned segments are coherently averaged to generate an enhanced tinnitus waveform. Coherent averaging exploits the fact that signal components that are phase-locked to the cycle add constructively, while noise components that are uncorrelated with the cycle add incoherently.

[0159] In particularly advantageous embodiments, individual segments are evaluated for quality prior to inclusion in the average. Segments exhibiting artifacts are excluded from averaging to prevent contamination of the enhanced waveform.

[0160] Artifact rejection criteria may include an amplitude-based rejection wherein segments whose root-mean-square (RMS) amplitude deviates from the median RMS by more than a threshold (e.g., 3.5 times the median absolute deviation) are rejected as potential motion artifacts or transient interference. Alternatively, artifact rejection may include a morphology -based rejection in which segments whose correlation with the running template fails below a threshold are rejected as potentially corrupted. Also,

[0161] physiological rejection can be used in which segments corresponding to cardiac cycles with abnormal R-R intervals (e.g., premature ventricular contractions) may be excluded.

[0162] In is noted, that in accordance with a particularly advantageous embodiment, cycle-marker signals for segmentation allowing for coherent averaging are not derived using cardiac-gated analysis based on measured EKG signals, but rather from the tinnitus-related signal itself, enabling single-sensor tinnitus detection without requiring separate cardiac monitoring equipment, referred to herein as “self-gating.”. Periodicity detection may be accomplished through envelope-based autocorrelation, spectral analysis, or other signal processing techniques.

[0163] In embodiments employing self-gating (described below), the cycle-marker signal is derived from the tinnitus-related signal itself, and separate cycle-marker acquisition hardware may be omitted.

[0164] In accordance with these particularly advantageous embodiments, the cardiac cycle periodicity can be derived from the tinnitus-related signal itself, eliminating the need for separateelectrocardiogram or other cardiac monitoring equipment. Multiple complementary methods may be employed to robustly detect cardiac periodicity from the tinnitus-related signal, detailed below.

[0165] Envelope-based autocorrelation can be used in which the analytic signal is computed via Hilbert transform, and the envelope (magnitude of the analytic signal) is extracted. The envelope is lowpass filtered (e.g., cutoff frequency of 5 Hz) to emphasize cardiac-rate variations. The autocorrelation of the filtered envelope is computed, and peaks in the autocorrelation function within a physiologically plausible range (e.g., corresponding to 40-180 beats per minute) are identified. The lag corresponding to the highest autocorrelation peak within this range indicates the cardiac period.

[0166] In a preferred implementation, autocorrelation is computed efficiently using FFT methods. Direct signal autocorrelation may be used by which the autocorrelation of the tinnitus-related signal itself (optionally bandpass filtered to the cardiac frequency range) is computed, and peaks are identified as candidate cardiac periods.

[0167] Spectral analysis may be employed in which the power spectral density of the signal (or its envelope) is computed using Welch's method or other spectral estimation techniques. Peaks in the spectrum within the cardiac frequency range indicate candidate cardiac frequencies.

[0168] In accordance with a preferred embodiment, ensemble periodicity estimation: in employed, wherein multiple periodicity detection methods are applied in parallel, and a consensus estimate is derived. The median of the period estimates from different methods provides robustness to failure of any single method. A confidence metric is computed based on agreement between methods; high agreement indicates reliable periodicity detection.

[0169] Once the fundamental cardiac period is estimated, individual cycle markers are identified in the tinnitus-related signal. This may be accomplished by peak detection in the envelope: which identifies local maxima in the lowpass-filtered envelope, spaced approximately one cardiac period apart, to serve as cycle markers.

[0170] A template cardiac cycle waveform is cross-correlated with the signal to identify cycle boundaries, and the cardiac period estimate is refined over time using a tracking filter (e.g., Kalman filter) to accommodate gradual changes in heart rate.

[0171] It is noted that a valuable feature of the invention provides method of characterizing tinnitus etiology based on spectral features of the enhanced tinnitus waveform, including features indicative of turbulent versus laminar blood flow patterns associated with vascular stenosis and for monitoring tinnitus treatment efficacy by comparing tinnitus detection outputs obtained before and after therapeutic intervention.

[0172] Vascular stenosis (narrowing) produces turbulent blood flow with characteristic acoustic signatures that differ from normal laminar flow. Normal laminar flow includes low frequencycontent (predominantly below 200 Hz), smooth temporal envelope, low spectral entropy. In contrast, stenotic turbulent flow: Broadband frequency content extending to 2000 Hz or higher, chaotic temporal structure, high spectral entropy, possible tonal components corresponding to vortex shedding frequencies.

[0173] In stenotic pulsatile tinnitus, turbulent flow is typically maximal during systole when blood velocity is highest. The invention provides methods for extracting and analyzing the systolic phase. Specifically, the enhanced cardiac cycle waveform is divided into phases based on timing relative to the R-wave (or detected cycle marker). The systolic phase, approximately 50-350 ms postmarker, is extracted for separate analysis. Spectral features computed specifically from the systolic phase may provide enhanced diagnostic sensitivity for stenosis.

[0174] As mentioned above, a significant application of the present invention is objective monitoring of tinnitus treatment efficacy. Effectiveness of treatment can look to such things as reduction in peak amplitude or RMS amplitude of the enhanced tinnitus waveform, detection status change based on SNR or amplitude thresholds, spectral change indicating a reduction in high- frequency energy, shift in spectral centroid toward lower frequencies, reduction in stenosis likelihood score. Longitudinal trending in which measurements over time may be plotted to visualize treatment response trajectory.

[0175] In summation, the invention provides an objective tinnitus detection and monitoring framework that is robust to noise, adaptable to different tinnitus phenotypes, implementable with minimal hardware, and capable of quantifying treatment response.

[0176] Having described preferred embodiments of the invention with reference to the accompanying drawings, it is to be understood that the invention is not limited to those precise embodiments, and that various changes and modifications may be effected therein by one skilled in the art without departing from the scope or spirit of the invention as defined in the appended claims.

Claims

Claims1, A method of detecting tinnitus in a subject, comprising:acquiring at least one tinnitus-related signal from the subject using at least one sensor; obtaining a plurality of cycle markers corresponding to a repeating physiological cycle; segmenting the tinnitus-related signal into a plurality of segments based on the plurality of cycle markers;aligning the plurality of segments to a reference phase of the repeating physiological cycle; generating an enhanced tinnitus waveform by coherently averaging the aligned plurality of segments, wherein coherent averaging increases a signal-to-noise ratio of tinnitus-related signal components that are time-locked to the repeating physiological cycle; andcreating a tinnitus detection output based on the enhanced tinnitus waveform.2 A method according to claim 1, further comprising:analyzing the tinnitus-related signal to identify a detected periodicity corresponding to the repeating physiological cycle; andderiving the plurality of cycle markers based on the detected periodicity.

3. A method according to claim 1, wherein said obtaining comprises acquiring an electrocardiogram signal from the subject and detecting R-wave peaks in the electrocardiogram signal.

4. A method according to claim 2, further comprising:computing an envelope of the tinnitus-related signal in said deriving;determining an autocorrelation of the envelope; andidentifying peaks in the autocorrelation corresponding to a cardiac cycle period.

5. A method according to claim 4, wherein said computing comprises applying a Hilbert transform to the tinnitus-related signal and computing a magnitude of the resulting analytic signal.

6. A method according to claim 4, further comprising lowpass filtering the envelope prior to determining.

7. A method according to claim 1, wherein said obtaining comprises acquiring a respiratory signal and detecting respiratory cycle transitions.

8. A method according to claim 1, further comprising identifying characteristic acoustic signatures that differ from normal laminar flow from the tinnitus detection output to diagnose a source of the tinnitus.

9. A method according to claim 1, wherein the tinnitus-related signal comprises at least one of. an acoustic signal acquired from an ear canal of the subject;a vibration signal acquired from a cranial structure of the subject; oran electrical signal representing neural activity.

10. A method according to claim 1, further comprising, prior to averaging, rejecting one or more segments based on an artifact criterion.

11. A method according to claim 1, wherein:said aligning comprises cross-correlating each segment with a template waveform, and applying a temporal shift to maximize correlation.

12. A tinnitus detection system comprising:at least one sensor configured to acquire at least one tinnitus-related signal from a subject; at least one processor; anda non-transitory computer-readable memory storing instructions that, when executed by the processor, cause the processor to perform a process including:obtaining a plurality of cycle markers corresponding to a repeating physiological cycle; segmenting the tinnitus-related signal into a plurality of segments based on the plurality of cycle markers;aligning the plurality of segments to a reference phase of the repeating physiological cycle; generating an enhanced tinnitus waveform by coherently averaging the aligned plurality of segments; andcreating a tinnitus detection output based on the enhanced tinnitus waveform.

13. A tinnitus detection system according to claim 12, wherein said process further comprises:before said aligning, analyzing the tinnitus-related signal to detect a periodicity corresponding to a physiological cycle; anddetermining said plurality of cycle markers based on the detected periodicity.

14. A tinnitus detection system according to claim 12, wherein the at least one sensor comprises a vibration-sensing microphone configured for placement in or near an ear canal of the subject.

15. A tinnitus detection system according to claim 12, further comprising an electrocardiogram sensor, wherein the instructions further cause the processor to detect R-wave peaks in an electrocardiogram signal acquired by the electrocardiogram sensor to obtain the plurality of cycle markers.

16. A tinnitus detection system according to claim 12, wherein the instructions further cause the processor to derive the plurality of cycle markers from the tinnitus-related signal.

17. A tinnitus detection system according to claim 12, wherein the sensor comprises a single vibration-sensing microphone, and wherein the system does not require a separate cardiac monitoring sensor.

18. A tinnitus detection system according to claim 12, further comprising a mobile computing device, wherein the processor is included in the mobile computing device.

19. A tinnitus detection system according to claim 18, further comprising a wireless communication interface between the at least one sensor and the mobile computing device.

20. A method of evaluating treatment efficacy for tinnitus, comprising:prior to treatment, acquiring a baseline tinnitus-related signal from a subject; generating a baseline tinnitus detection output by:(i) obtaining a plurality of cycle markers corresponding to a repeating physiological cycle,(ii) segmenting the baseline tinnitus-related signal into a plurality of baseline segments based on the plurality of cycle markers,(iii) coherently averaging the plurality of baseline segments to generate a baseline enhanced waveform, and (iv) computing a baseline tinnitus metric from the baseline enhanced waveform;after treatment, acquiring a follow-up tinnitus-related signal from the subject and generating a follow-up tinnitus detection output by:(i) obtaining a plurality of cycle markers corresponding to the repeating physiological cycle,(ii) segmenting the follow-up tinnitus-related signal into a plurality of follow-up segments based on the plurality of cycle markers,(iii) coherently averaging the plurality of follow-up segments to generate a follow¬ up enhanced waveform, and (iv) computing a follow-up tinnitus metric from the follow-up enhanced waveform; andcomparing the baseline tinnitus metric and the follow-up tinnitus metric to generate a treatment response indicator.

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