Application US20200188702

SYSTEMS AND METHODS FOR A DEVICE USING A STATISTICAL MODEL TRAINED ON ANNOTATED SIGNAL DATA
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US20200188702

1. A device, comprising: (7) (2)

a sensor configured to detect a signal from the brain of the person; and

a plurality of transducers, each configured to apply to the brain an acoustic signal, wherein one of the plurality of transducers is selected using a statistical model trained on signal data annotated with one or more values relating to identifying a health condition.

2. The device as claimed in claim 1, wherein the signal data annotated with the one or more values relating to identifying the health condition comprises the signal data annotated with respective values relating to increasing strength of a symptom of a neurological disorder. (6) (0)

3. The device as claimed in claim 2, wherein the statistical model was trained on data from prior signals detected from the brain annotated with the respective values between 0 and 1 relating to increasing strength of the symptom of the neurological disorder. (0)

4. The device as claimed in claim 2, wherein the statistical model includes a loss function having a regularization term that is proportional to a variation of outputs of the statistical model, an L1/L2 norm of a derivative of the outputs, or an L1/L2 norm of a second derivative of the outputs. (0)

5. The device as claimed in claim 2, comprising: (1) (1)

a processor in communication with the sensor and the plurality of transducers, the processor programmed to: provide data from a first signal detected from the brain as input to the trained statistical model to obtain an output indicating a first predicted strength of the symptom of the neurological disorder; and

based on the first predicted strength of the symptom, select one of the plurality of transducers in a first direction to transmit a first instruction to apply a first acoustic signal.

6. The device as claimed in claim 5, wherein the processor is programmed to: (0) (2)

15. The device as claimed in claim 2, wherein the acoustic signal suppresses the symptom of the neurological disorder. (0)

16. The device as claimed in claim 2, wherein the neurological disorder includes one or more of stroke, Parkinson's disease, migraine, tremors, frontotemporal dementia, traumatic brain injury, depression, anxiety, Alzheimer's disease, dementia, multiple sclerosis, schizophrenia, brain damage, neurodegeneration, central nervous system (CNS) disease, encephalopathy, Huntington's disease, autism, attention deficit hyperactivity disorder (ADHD), amyotrophic lateral sclerosis (ALS), and concussion. (0)

17. The device as claimed in claim 2, wherein the symptom includes a seizure. (0)

7. The device as claimed in claim 1, wherein the trained statistical model comprises a deep learning network. (1) (0)

9. The device as claimed in claim 1, wherein the signal data includes data from prior signals detected from the brain that is accessed from an electronic health record of the person. (0)

10. The device as claimed in claim 1, wherein the sensor includes an electroencephalogram (EEG) sensor, and wherein the signal includes an EEG signal. (0)

11. The device as claimed in claim 1, wherein the transducer includes an ultrasound transducer, and wherein the acoustic signal includes an ultrasound signal. (2) (0)

14. The device as claimed in claim 1, wherein the sensor and the transducer are disposed on the head of the person in a non-invasive manner. (0)

18. The device as claimed in claim 1, wherein the signal comprises an electrical signal, a mechanical signal, an optical signal, and/or an infrared signal. (0)

19. A method for operating a device, the device including a sensor configured to detect a signal from the brain of the person and a plurality of transducers, each configured to apply to the brain an acoustic signal, comprising: (0) (1)

20. An apparatus comprising: (0) (1)

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Application US20200188702

SYSTEMS AND METHODS FOR A DEVICE USING A STATISTICAL MODEL TRAINED ON ANNOTATED SIGNAL DATA

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