act_patterns

A demo and incomplete <code>musclesyneRgies</code> object containing time info and three activation patterns
extracted from one wild type mouse walking on a treadmill.

datasets

Provides a framework to factorise electromyography (EMG) data.
Tools are provided for raw data pre-processing, non negative matrix factorisation,
classification of factorised data and plotting of obtained outcomes.
In particular, reading from ASCII files is supported, along with wide-used
filtering approaches to process EMG data. All steps include one or more sensible
defaults that aim at simplifying the workflow. Yet, all functions are largely
tunable at need. Example data sets are included.

Alessandro Santuz

musclesyneRgies

Extract Muscle Synergies from Electromyography

act_patterns function

A data frame of four columns:
<dl>
<dt><code>time</code></dt>
<dd>Normalised time in points.</dd><dt><code>Syn1</code></dt>
<dd>Activation pattern of synergy 1</dd><dt><code>Syn2</code></dt>
<dd>Activation pattern 2</dd><dt><code>Syn3</code></dt>
<dd>Activation pattern of synergy 3</dd>
</dl>

Format

All activation patterns of one synergy example (30 cycles) — act_patterns

A data frame of four columns:
<dl>
<dt><code>time</code></dt>
<dd>Normalised time in points.</dd>

<dt><code>Syn1</code></dt>
<dd>Activation pattern of synergy 1</dd>

<dt><code>Syn2</code></dt>
<dd>Activation pattern 2</dd>

<dt><code>Syn3</code></dt>
<dd>Activation pattern of synergy 3</dd>


</dl>

act_patterns: All activation patterns of one synergy example (30 cycles)

Description

Usage

Arguments

Format