I can give you a quick (well detailed so hopefully quick) description via an example.
When you take and pull out frequencies using current, we are looking for the ones that had the most change from the prior measured frequency.
When you take and pull out frequencies using angle, we are looking for the same, but using phase angle.
When you take and pull out frequencies using angle+current, we literally add the two measurements together and pull the frequencies from the combined metrics.
It may sound similar, but it is very different. Let me highlight using an example:
Let's say we have the following 3 frequencies and corresponding measurements (remember the values we evaluate are the change from prior measurement, while the raw data is recorded in the biofeedback file).
1000 Hz with a current measurement difference of 10, and an angle measurement difference of 20.
2000 Hz with a current measurement difference of 20, and an angle measurement difference of 10.
3000 Hz with a current measurement difference of 15, and an angle measurement difference of 16.
If I pull the top frequency from all 3 for current, I will get back 2000 Hz. It has the highest measurement difference for current.
If I pull the top frequency from all 3 for angle, I will get back 1000 Hz.
If I pull the top frequency from angle+current, I get back 3000 Hz. While 3000 Hz had neither the highest current or angle measurement, combined it outranks the other two.
This is why you will find that angle+current has the both the ability to pull duplicate frequencies from the other two analysis methods, but also has the ability to pull frequencies that are unique -- culling frequencies that responded well in both categories, but not necessarily enough to make the top 10 using the other two methods of analysis.
While John's method is indeed a nice way to make one frequency program out of two methods, I still find there is value in saving 10 frequencies per method into individual frequency programs so I can track which frequency came from what.
Loading 3 frequency programs into a application is easy enough and remove duplicates takes care of reducing the results to unique sets.
Others will find much value in John's method to combine them together into one frequency program, and I'm sure other methods will be invented as well to manage the data.
For more details, please check the link: