# US 11,076,797 B2 · Systems and methods for the identification of medical conditions, and determination of appropriate therapies, by passively detecting acoustic signals from cerebral vasculature

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- Number: US 11,076,797 B2
- Document ID: US11076797B2
- Status: Granted
- Kind: B2
- Application number: 16/380,841
- Filed: 2019-04-10
- Published: 2019-10-10
- Granted: 2021-08-03
- Earliest claimed: 2018-04-10
- Assignees: Cerenetex, Inc.
- Applicants: Cerenetex, Inc.
- Inventors: Benjamin William Bobo; David Robbins Asbury; Devendra Goyal; Mohsin Shah; John Chen; Sahar Bou-Ghazale Toukmaji
- Web page: https://patentgrep.com/patent/US11076797B2

## CPC

- A61B 5/4064: {Evaluating the brain (for intracranial pressure A61B5/031; for cerebral blood gases A61B5/14553; using EEG A61B5/369)}
- A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet}
- A61B 5/026: Measuring blood flow {(A61B3/1233, A61B3/1241 take precedence)}
- A61B 5/1102: {Ballistocardiography}
- A61B 5/165: {Evaluating the state of mind, e.g. depression, anxiety}
- A61B 5/4082: {Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette}
- A61B 5/4088: {Diagnosing of monitoring cognitive diseases, e.g. Alzheimer, prion diseases or dementia}
- A61B 5/4094: {Diagnosing or monitoring seizure diseases, e.g. epilepsy}
- A61B 5/4824: {Touch or pain perception evaluation (A61B5/4821 takes precedence)}
- A61B 5/6803: {Head-worn items, e.g. helmets, masks, headphones or goggles}
- A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems}
- A61B 5/7282: {Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818)}
- A61B 5/7405: {using sound}
- A61B 5/7445: {Display arrangements, e.g. multiple display units}
- A61B 7/001: {Detecting cranial noise, e.g. caused by aneurism}
- A61B 7/04: Electric stethoscopes
- G16H 40/67: for remote operation
- A61B 2562/0204: Acoustic sensors
- A61B 2562/0219: Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
- A61B 2562/06: Arrangements of multiple sensors of different types
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

The present specification describes a system for diagnosing or screening one or more pathologies in a patient. The system includes a headset with at least one microphone or accelerometer to passively receive vibrations generated by the cerebral vasculature of the patient's brain, computing devices coupled with the headset for processing the received vibrations to obtain a unique signal, and a signal analyzer to analyze the signal in order to determine if the data includes patterns uniquely indicative of at least one of tension headaches, migraines, depression, dementia, Alzheimer's disease, epilepsy, Parkinson's disease, autism, cerebral vasospasm and meningitis.

## Claims

### Claim 1

A system for diagnosing one or more pathologies in a patient, the system comprising:
a headset comprising at least one microphone, acoustic sensor, or accelerometer to passively receive vibrations from cerebral vasculature of the patient's brain;
at least one computing device coupled with the headset for processing the received vibrations to obtain a signal;
a signal analyzer coupled with the at least one computing device and configured to analyze the signal to identify a pattern indicative of the one or more predefined pathologies, wherein the one or more predefined pathologies comprise at least one of tension headaches, migraines, vascular dementia, Alzheimer's disease, epilepsy, vascular Parkinson's disease, cerebral vasospasm, or meningitis; and
a second computing device configured to receive the pattern, compare the pattern to a plurality of predefined patterns indicative of the one or more predefined pathologies, and categorize the pattern as being representative of the one or more predefined pathologies, wherein the plurality of predefined patterns comprises acoustic signal data indicative of a plurality of different migraine types.

### Claim 2 (depends on 1)

The system of claim 1 wherein the signal analyzer is configured to differentiate between each of the predefined pathologies and output an audio or visual indicator that specifically identifies one of the predefined pathologies while concurrently excluding a remainder of the predefined pathologies.

### Claim 3 (depends on 1)

The system of claim 1 wherein the signal analyzer is not configured to identify a traumatic brain injury, stroke, aneurysm, or hemorrhage.

### Claim 4 (depends on 1)

The system of claim 1 wherein the headset comprises two microphones, wherein each of the two microphones is provided within each ear covering of the headset.

### Claim 5 (depends on 4)

The system of claim 4, wherein the headset comprises a pre-amplifier, a frequency equalizer and a noise cancellation module.

### Claim 6 (depends on 1)

The system of claim 1 wherein the at least one microphone captures and outputs bi-hemispheric data and has an output for detecting vibrations in a range of 0-750 kHz.

### Claim 7 (depends on 1)

The system of claim 1 wherein the headset comprises a signal quality indicator configured to indicate a quality of the vibrations being received, a light source configured to visually indicate that the headset is in an operational mode, and a light array configured to indicate a level of battery charge.

### Claim 8 (depends on 1)

The system of claim 1 wherein the at least one computing device comprises at least one of an Internet of Things (IoT) device, mobile phone, tablet device, desktop computer or laptop computer.

### Claim 9 (depends on 1)

The system of claim 1 wherein the at least one microphone, acoustic sensor, or accelerometer is configured to be positioned within a predefined distance of at least one of the patient's basilar artery, anterior inferior cerebellar artery, anterior vestibular artery, internal auditory artery, common cochlear artery, internal carotid artery, or ophthalmic artery.

### Claim 10 (depends on 9)

The system of claim 9 wherein the predefined distance is 10 mm.

### Claim 11 (depends on 1)

The system of claim 1 wherein the at least one microphone, acoustic sensor, or accelerometer is configured to be positioned outside of a predefined distance from at least one of the patient's zygoma, external carotid artery, internal maxillary artery, facial artery, or occipital artery.

### Claim 12 (depends on 11)

The system of claim 11 wherein the predefined distance is 5 mm.

### Claim 13 (depends on 1)

The system of claim 1 wherein the at least one microphone, acoustic sensor, accelerometer is configured to be positioned within a first predefined distance of at least one of the patient's basilar artery, anterior inferior cerebellar artery, anterior vestibular artery, internal auditory artery, common cochlear artery, internal carotid artery, or ophthalmic artery and outside of a second predefined distance from at least one of the patient's zygoma, external carotid artery, internal maxillary artery, facial artery, or occipital artery, wherein the first predefined distance is less than the second predefined distance.

### Claim 14 (depends on 13)

The system of claim 13 wherein the first predefined distance is within a range of 0 mm to 5 mm and wherein the second predefined distance is at least 5 mm.

### Claim 15 (depends on 1)

The system of claim 1 further comprising one or more databases coupled with the signal analyzer, wherein the one or more databases comprises pre-determined signal classifications comprising specific frequencies, frequency ranges, energies, energy ranges, periodicities or periodicity ranges unique to each of the predefined pathologies.

### Claim 16 (depends on 15)

The system of claim 15 wherein the signal analyzer comprises one or more algorithms configured to detect one or more of the predefined pathologies present in the signal by comparing the analyzed signal with the pre-determined signal classifications comprising specific frequencies unique to each of the predefined pathologies.

### Claim 17 (depends on 1)

The system of claim 1 wherein the plurality of different migraine types comprise aura, without aura, basilar, hemiplegic, ophthaloplegic, vestibular or chronic.

### Claim 18 (depends on 1)

The system of claim 1 wherein the plurality of predefined patterns is derived from signal measurements taken from individuals other than the patient.

### Claim 19

A method for determining if a patient is suffering from a condition, the method comprising:
positioning at least one microphone, acoustic sensor, or accelerometer within a first predefined distance of at least one of the patient's basilar artery, anterior inferior cerebellar artery, anterior vestibular artery, internal auditory artery, common cochlear artery, internal carotid artery, or ophthalmic artery and outside of a second predefined distance from at least one of the patient's zygoma, external carotid artery, internal maxillary artery, facial artery, or occipital artery, wherein the first predefined distance is less than the second predefined distance;
capturing a signal transduced through a medium, wherein the medium is at least one of air, tissue, bone, vasculature, or nerves, wherein the signal is caused by blood flow in a cerebral vasculature of the patient's brain and is not a function of a second signal originating external to the patient, and wherein the signal is captured using at least one of the accelerometer, the acoustic sensor, or the microphone;
digitizing the captured signal using a first component in data communication with the accelerometer, acoustic sensor, or microphone;
transmitting the digitized captured signal to a signal analyzer using a second component in data communication with the first component;
using the signal analyzer, acquiring the digitized captured signal and processing the acquired digitized captured signal to identify a signature, wherein the signature is a function of a non-zero amplitude, frequency and periodicity of the signal, wherein the signature is uniquely indicative of the condition, and wherein the condition is one of a tension headache, a migraine, vascular dementia, Alzheimer's disease, epilepsy, vascular Parkinson's disease, cerebral vasospasm or meningitis; and
using a computing device, receiving the signature, comparing the signature to one of a plurality of predefined patterns indicative of the condition, and categorizing the signature as being representative of the condition, wherein the plurality of predefined patterns includes acoustic signal data indicative of a plurality of different migraine types.

### Claim 20 (depends on 19)

The method of claim 19 wherein the first predefined distance is within a range of 0 mm to 5 mm and wherein the second predefined distance is at least 5 mm.

### Claim 21 (depends on 19)

The method of claim 19 further comprising accessing one or more databases, wherein the one or more databases comprises pre-determined signal classifications comprising specific frequencies, frequency ranges, energies, energy ranges, periodicities or periodicity ranges unique to the condition.

### Claim 22 (depends on 19)

The method of claim 19 wherein the signal analyzer comprises one or more algorithms configured to detect data indicative of the condition present in the signal by comparing the signal with pre-determined signal classifications comprising specific frequencies unique to the condition.

### Claim 23 (depends on 19)

The method of claim 19 wherein the plurality of different migraine types comprise aura, without aura, basilar, hemiplegic, ophthaloplegic, vestibular or chronic.

### Claim 24 (depends on 19)

The method of claim 19 wherein the plurality of predefined patterns is derived from signal measurements taken from individuals other than the patient.