Metadata-Version: 2.1
Name: dimep
Version: 0.2
Summary: Measures ipsilateral MEPs
Home-page: https://github.com/translationalneurosurgery/tool-dimep
Author: Robert Guggenberger
Author-email: robert.guggenberger@uni-tuebingen.de
License: MIT
Download-URL: https://github.com/translationalneurosurgery/tool-dimep
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
Requires-Dist: scipy
Requires-Dist: numpy


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# Detection of Ipsilateral Motor Evoked Potentials

**DiMEP** stands for **D**etection of **i**psilateral **M**otor **E**voked **P**otentials and was developed by [Robert Guggenberger](https://www.robert-guggenberger.de) at the [Institute of Neuromodulation and Neurotechnology of the University Hospital Tübingen](https://www.medizin.uni-tuebingen.de/go/neuromodulation).


Installation
------------

Install the stabel release from PyPI with `pip install dimep` and the most recent development  tip with `pip install git+https://github.com/translationalneurosurgery/tool-dimep.git`.

Usage
-----

Access the algorithms with

``` python

   from dimep.api import <algorithm>

```
and subsequently call them, e.g. with

``` python

   from dimep.api import lewis
   lewis(trace=trace, tms_sampleidx= 500, fs = 1000)
   # where the trace is the single-channel EMG recording
   # tms_sampleidx marks the onset of the TMS pulse
   # and fs is the sampling rate.
```

Documentation
-------------

Read the documentation on [readthedocs](https://tool-dimep.readthedocs.io/en/latest/?badge=latest).


