Optimization of cranial nerve stimulation to treat seizure disorders during sleep

1. A method comprising:

receiving, at a computing device, body parameter data of a patient;

determining that the patient is in a particular sleep cycle stage based on the body parameter data;

detecting, while the patient is in the particular sleep cycle stage, a seizure event based on synchrony of brain waves of the patient;

comparing, at the computing device, the brain waves to a target profile associated with the particular sleep cycle stage; and

in response to determining the brain waves are not in conformance with the target profile, adjusting, at the computing device, a cranial nerve stimulation parameter to drive the brain waves to the target profile.

2. The method of claim 1 , wherein the body parameter data comprises electroencephalography (EEG) data, electrooculography (EOG) data, electromyography (EMG) data, electrocardiography (ECG) data, accelerometer data, or a combination thereof.

3. The method of claim 1 , wherein the particular sleep cycle stage is determined further based on a sleep stage transition, an amount of time the patient spends in one or more stages during the particular sleep cycle, an amount of time the patient spends in one or more stages during a sleep period that includes multiple sleep cycles, or a combination thereof.

4. The method of claim 1 , wherein the body parameter data is received from a sensor that is attached to the patient.

5. The method of claim 1 , further comprising readjusting the cranial nerve stimulation parameter in association with a first transition from a light sleep stage to an awake state; a second transition from stage 1 sleep to stage 2 sleep; the patient being in the light sleep stage; the patient being in the light sleep stage for a particular amount of time; or a combination thereof.

6. The method of claim 5 , further comprising stimulating a cranial nerve based on the readjusted cranial nerve stimulation parameter to drive the patient toward a deep sleep stage.

7. The method of claim 1 , further comprising applying stimulation signals to a vagus nerve or a trigeminal nerve of the patient via a therapy delivery unit based on the adjusted cranial nerve stimulation parameter.

8. The method of claim 1 , wherein the cranial nerve stimulation parameter indicates a pulse width, an output current, a cranial nerve stimulation frequency, a cranial nerve stimulation duty cycle, a particular nerve or nerves stimulated, a cranial nerve stimulation frequency sweep, a cranial nerve stimulation on-time, a cranial nerve stimulation off-time, or a combination thereof.

9. The method of claim 1 , wherein the seizure event corresponds to an epileptic seizure.

10. A computing device comprising: a processor; and a memory having instructions stored thereon that, when executed by the processor, cause the processor to: receive body parameter data of a patient; determine that the patient is in a particular sleep cycle stage based on the body parameter data; detect, while the patient is in the particular sleep cycle stage, a seizure event based on synchrony of brain waves of the patient; compare the brain waves to a target profile associated with the particular sleep cycle stage; in response to determining the brain waves are not in conformance with the target profile, adjust a cranial nerve stimulation parameter to drive the brain waves to the target profile.

11. The computing device of claim 10 , wherein the body parameter data comprises electroencephalography (EEG) data, electrooculography (EOG) data, electromyography (EMG) data, electrocardiography (ECG) data, accelerometer data, or a combination thereof.

12. The computing device of claim 10 , wherein the particular sleep cycle stage is determined further based on a sleep stage transition, an amount of time the patient spends in one or more stages during the particular sleep cycle, an amount of time the patient spends in one or more stages during a sleep period that includes multiple sleep cycles, or a combination thereof.

13. The computing device of claim 10 , wherein the body parameter data is received from a sensor that is attached to the patient.

14. The computing device of claim 10 , wherein the instructions, when executed by the processor, further cause the processor to:

readjust the cranial nerve stimulation parameter in association with a first transition from a light sleep stage to an awake state; a second transition from stage 1 sleep to stage 2 sleep; the patient being in the light sleep stage; the patient being in the light sleep stage for a particular amount of time; or a combination thereof.

15. The computing device of claim 14 , wherein the instructions, when executed by the processor, further cause the processor to:

stimulate a cranial nerve based on the readjusted cranial nerve stimulation parameter to drive the patient toward a deep sleep stage.

16. The computing device of claim 10 , wherein the instructions, when executed by the processor, further cause the processor to:

apply stimulation signals to a vagus nerve or a trigeminal nerve of the patient via a therapy delivery unit based on the adjusted cranial nerve stimulation parameter.

17. The computing device of claim 10 , wherein the cranial nerve stimulation parameter indicates a pulse width, an output current, a cranial nerve stimulation frequency, a cranial nerve stimulation duty cycle, a particular nerve or nerves stimulated, a cranial nerve stimulation frequency sweep, a cranial nerve stimulation on-time, a cranial nerve stimulation off-time, or a combination thereof.

18. The computing device of claim 10 , wherein the seizure event corresponds to an epileptic seizure.

19. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to:

receive body parameter data of a patient;

determine that the patient is in a particular sleep cycle stage based on the body parameter data;

detect, while the patient is in the particular sleep cycle stage, a seizure event based on synchrony of brain waves of the patient;

compare the brain waves to a target profile associated with the particular sleep cycle stage;

in response to determining the brain waves are not in conformance with the target profile, adjust a cranial nerve stimulation parameter to drive the brain waves to the target profile.

20. The non-transitory computer-readable medium of claim 19 , wherein the body parameter data comprises electroencephalography (EEG) data, electrooculography (EOG) data, electromyography (EMG) data, electrocardiography (ECG) data, accelerometer data, or a combination thereof.