Biological marker and methods

1. A method of evaluating the effectiveness of an intervention measure, comprising:

estimating the risk of occurrence of a physiological event in a mammal, wherein said estimating comprises:

obtaining brain activity data that describes brain activity of the mammal over a first period of time;

obtaining peripheral activity data that describes peripheral activity of the mammal over a second period of time;

receiving, by at least one device, brain data from a brain activity measurement device that describes brain activity of a mammal over the first period of time;

receiving, by the at least one device, periphery data from a peripheral activity measurement device that describes peripheral activity of a mammal over the second period of time;

generating, by the at least one device, one or more brain feature representations based on the brain data;

generating, by the at least one device, one or more periphery feature representations based on the periphery data;

generating, by the at least one device, one or more brain statistical distributions of the one or more brain feature representations;

generating, by the at least one device, one or more periphery statistical distributions of the one or more periphery feature representations;

identifying, by the at least one device, one or more brain feature representations that fall outside of a predetermined range in the brain statistical distribution to generate a set of one or more target brain feature representations;

identifying, by the at least one device, one or more periphery feature representations that fall outside of a predetermined range in the periphery statistical distribution to generate a set of one or more target periphery feature representations;

determining, by the at least one device, a brain-periphery temporal association between the one or more target brain feature representations and the one or more target periphery feature representations;

determining, by the at least one device, an estimate of risk of a future physiological event based on the brain-periphery temporal association; and

providing, by the at least one device, an indication of the estimate of risk of the future physiological event;

applying at least one intervention measure that is commensurate with the prevention of the physiological event; and

determining the effectiveness of the intervention measure.

2. The method of claim 1 , wherein estimating the risk and applying the intervention measure are performed automatically.

3. The method of claim 1 , wherein said mammal is a human.

4. The method of claim 1 , wherein said mammal is at risk of developing or has a neurologic disease, and wherein said neurological disease is epilepsy.

5. The method of claim 1 , wherein the physiological event is selected from the onset of acquired epilepsy, an epileptic seizure, sudden unexpected death in epilepsy (SUDEP), hydrocephalus, sepsis, and onset of cerebral palsy.

6. The method of claim 1 , wherein the intervention measure is an anti-epileptogenic therapy.

7. The method of claim 1 , wherein the intervention measure is administration of an anti-epileptic drug (AED).

8. The method of claim 7 , wherein said AED is selected from the group consisting of acetazolamide, carbamazepine, clobazam, clonazepam, eslicarbazepine acetate, ethosuximide, gabapentin, lacosamide, lamotrigine, levetiracetam, nitrazepam, oxcarbazepine, perampanel, piracetam, phenobarbital, phenytoin, pregabalin, primidone, rufinamide, sodium valproate, stiripentol, tiagabine, topiramate, vigabatrin, zonisamide, and combinations thereof.

9. The method of claim 1 , further comprising determining, by the system, a quantification of the brain-periphery temporal association; wherein providing the estimate of risk of a future physiological event is based on the quantification of the brain-periphery temporal association.

10. The method of claim 9 , further comprising:

determining, by the system, an estimate of the timing of a future physiological event based on the quantification of the brain-periphery temporal association; and

providing an indication of the estimate of the timing of the future physiological event.

11. The method of claim 1 , further comprising:

determining, by the system, an estimate of the timing of a future physiological event based on the brain-periphery temporal association; and

providing an indication of the estimate of the timing of the future physiological event.

12. The method of claim 1 , wherein the periphery statistical distribution is independent of behavioral state.

13. The method of claim 1 , wherein the brain activity data is electroencephalography (EEG) data.

14. The method of claim 1 , wherein the periphery data is selected from cardiac data, muscle movement data, nerve activity data, pupil dilation data, and body movement data.

15. The method of claim 1 , wherein the periphery data is cardiac data, and wherein the cardiac data is selected from electrocardiogram (ECG) data, blood pressure data, and photoplethysmography (PPG) data.

16. The method of claim 1 , wherein the periphery data is ECG data, and wherein the physiological event is selected from the onset of acquired epilepsy, an epileptic seizure, and SUDEP.

17. The method of claim 1 , wherein the peripheral activity data was obtained from a peripheral activity measurement device that is integrated with or communicatively coupled to a smartphone, a tablet computer, a watch body, a watch band, or a wearable patch.

18. The method of claim 1 , further comprising displaying, on a display device, an output indicative of the estimate of risk of the physiological event.