Combination of accelation signals from two devices I have $x_A$, $y_A$, and $z_A$ acceleration signals collected from a smartphone and I call it: set $A$ and I also  have $x_B$, $y_B$, and $z_B$ same acceleration signals from smartwatch: let's call this set $B$. I need to combine them together to obtain set $C$, but since I don't have good knowledge in signal processing I am not sure if it is this logically correct to combine them and take the average of them, or any other way should I follow to have one set of signals instead of having two separate sets?

How to select the set if it is possible? The signals are raw data.
May be you can find variance of acceleration along x,y, and z direction in SET A and in set B separately and choose the the device which has least variance.



As this Wikipedia page suggests, you can combine the two by weighting by their respective variances.

So, to get $x_C$ simply:
$$
x_C = \frac{1}{\sigma_1^{-2} + \sigma_2^{-2}} \left(  \frac{x_A}{\sigma_1^2} + \frac{x_B}{\sigma_2^2}\right)
$$

Putting some numbers on this, suppose $\sigma^2_1 = 1$ and $\sigma^2_2 = 0.5$, then 
$$
\sigma_3^2 = \frac{1}{\sigma_1^{-2} + \sigma_2^{-2}} = \frac{1}{1 + 2} = \frac{1}{3}
$$
which is a lower variance than either of the individual measurements.

Use the same process to find $y_C$ and $z_C$.