Microsmooth

##Introduction

A lightweight and fast signal smoothing library for the Arduino platform.

This library provides implementations of signal processing algorithms like:

• Simple Moving Average (SMA)
• Cumulative Moving Average (CMA)
• Exponential Moving Average (EMA)
• Savitzky Golay Filter (SGA)
• Ramer Douglas Peucker Algorithm (RDP)
• Kolmogorov Zurbenko Algorithm (KZA)

##Installation

Use the standard process for Arduino libraries. The following steps are involved:

• Create a folder libraries in your Sketchbook
• Git clone, or download and extract, this library in that folder. So, your sketchbook should have the following structure -> /libraries/microsmooth/microsmooth.[cpp|h] and additional files.
• In your sketch, add #include <microsmooth.h> and compile.

##Usage

The library can be used as shown below:

• First, initialize the library: uint16_t *history = ms_init(SMA); where SMA can be replaced with any of the three alphabet codes given above.
• Then, input your analog signal value using analogRead() or pulseIn into an int variable, referred here as channel_value.
• Pass the variable into the filter initialized in the first step: int processed_value = sma_filter(channel_value, history);
• Repeat for input channel for a time domain signal.
• When done, deinit library with: ms_deinit(history); (This releases the memory being utilized)

The filters all have the same interface:

<Three digit code>_filter(channel_value, history)

where <Three digit code> can be sma, cma, ema, rdp, sga, kza.

##Code Sample

A simple code sample for using any of the filters in the library is available here.

##Performance Analysis

The best performing filter at present is EMA with alpha parameter 0.10.

The ranking strategy for the filters is discussed in this paper.