Filter Design - Step Response I'm  looking for a tool\method which allows me to design a filter without involving the frequency response at all.
Specifically, I'm trying to design a simple FIR smoothing filter for an emmbedded system which reads different analog sensors. My sampling rate is 1kHz and I'd like to generate an FIR filter with 0-overshoot and a smoothing effect (e.g. in attached pic).


The different tools I found (including MATLAB) all involved a design around a LP filter, which means I have to analyze the frequency response of my system.

Any relevant tools\methods out there?
For linear filters, binomial filters, which can be considered as FIR approximation to Gaussians, are very simple. Their coefficients are given by:
$$ h_k=\frac{ \binom{n}{k}}{2^n} \,.$$
For instance, you can get $H_3 = [ \frac{1}{4},\frac{1}{2},\frac{1}{4}]$, or $H_5 = [ \frac{1}{16},\frac{1}{4},\frac{3}{8},\frac{1}{4},\frac{1}{16}]$. Since their coefficients are positive, they do not overshoot.

Here are graphs for $n = 5,17,25,31$:



Savitzky-Golay filters, performing polynomial interpolation, are interesting too, but tend to   overshoot with higher degrees. 

Do not fool yourself though: as long as the filters are linear, there is a notion of frequency very close behind.