Marchovian decision for quantify self.

We are talking about the  Partially Observable Markov Decision Processes (POMDP) use by the MIT to check and test the “health” of the drones during missions.

But the fact is equally applicable to quantify self decision making for human health.  Each node represents a probability distribution, or the likelihood of a given outcome. And the simplification of the process into

a) Vehicle-level planning such as a vehicle’s location at any given time.

b) Health planning, such as the condition of a vehicle’s propellers, cameras, and fuel levels.

is equally applied to human´s health measuring heart activity, fluids (circulation-urine), respiration (O2, CO2), pain, activity, sleep, water and diet (glucosae, proteins & ions) and probably part of this measurements can be reduce.

In the near future our e-PHA (electronic personal health assistant) in the Fog will take care of indicating the most healthy way of life according our phisical conditions. And the Markov model will be the mathematical model  that according to the medical dictionary :

makes it possible to study complex systems by establishing a state of the system and then effecting a transition to a new state, such a transition being dependent only on the values of the current state, and not dependent on the previous history of the system up to that point.


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