Prediction


Prediction/forecast/prophecy means the ability to use previous data in order to anticipate what could happen in the future.

In order for insulin to be dosed -precisely -sensor readings need to be  accurate as much as possible. and this is subject to extensive researches done by various companies aiming to enhance :

1-sensor performance/ consistency

2-sensor stability

3-cutting of possible interference  through using special mediators of selected characteristics

4-keeping the sensor its place during the whole wearing period by wiring the enzyme by the aid of specific polymers

5- glucose concentration must be kept in certain limit to avoid misleading readings -a special membrane is used to control diffusion  backward and forward.

6-CLS (closed loop control) is one way of controlling insulin pumping based on output sensing ,where outcome feedback is considered before any amendment is needed.

ex. dryer machine is nice /clear example where wetness of clothes  is considered before any required/extra action :

if clothes are less wet ; less drying time  is needed while if more wet ; more drying time is  needed ..etc

i.e clothes drying is sensed through a special sensor;  the the signal is sent back to the control before any further action (just a simple example,matter is more complex !) however :

1- "feedback signal shroud be evaluated -mathematically- within the processor to avoid frequent/unneeded adjustment  which may  cause oscillation/breaking of the whole system

2-this  process should be on continuous interval to avoid any accidental change -esp.. in dynamic system.

6-Prediction is the most important part of CGM ,

by the way " retrospective data analysis and proper prediction algorithm are two features were added to  CGM sensor output; in order to compensate for sub optimal accuracy  resulting from lag time ...for example !"

any prediction -in order to be reasonable :

1-  it must take into account  previous data and history so patterns and trends can be extracted/extrapolated  from them by careful mining and systemic analysis. (machine learning is  a must , advanced insulin pumps where a partial closed loop system is implemented , selected time must elapse before turning in auto mode "CLS" so the machine could learn better about each individual) ;

"Remember that each person reacts differently to each triggering action  ,even the same person differs in his response from time to time "

2-if prediction is an independent output ,that means many dependent/variables inputs -if included-will make it closer to reality and away from false estimation so more inputs means more precise prediction .

See below simplified example :

1- imagine that one employee stays in his office from 8 am to 5 pm from Monday up to Thursday ,according to this data assuming it for year ,we say that he may be present there on 1st of July if its working day- in the next year will be 90 % lets say..

2- however if we know that guy takes vacation on  June /or July or august ,we will be less certain of his presence in that date..

3-however imagine we got more data of this employee that in the previous 6 yrs he took vacation on July,:4 times -one on june and one on august  now, we become quasi certain that we may not  find him on that day (our prediction becomes more precise as we got more data !

4- now,imagine his dad is sick and about to a  undergo surgery on 30 of June   ; so that employee is most unlikely to be found in 1st of july (prediction becomes much more certain) !


5-more data means more certainty !!!!


To sum up, 

more than 40 factors affect blood glucose -in addition to various types of lag time -discussed later- so its so important to figure them out once applicable -otherwise our prediction will be non logic and misleading in many cases...