SpiSOP (abrev. for Spindles Slow Oscillation and Power-spectral-density) 
is an open source tool supporting detection and reporting of spindle or slow oscillation events, 
their co-occurance or respective matching non-events and power (density) of specific spectra 
or frequency bands in pre-scored (sleep stages) EEG and MEG data 
as well as simple automatic EMG artifact detection. 
Most detection methods and annotations reported in sleep EEG research are covered
and thus can be replicated by minor adaptions in the standard parameters. 
SpiSOP was designed to process large data quanta at once and multiple datasets in parallel. 
Analysis is according to wished channels, their various combinations, 
specified dynamic sleep stages, various detection thresholds and further parameters. 
Frequency peaks in the power band of slow oscillations, spindles or any other band of interest 
are automatically determined and visually confirmed or adapted by user. 
SpiSOP also contains a data browser to sleep (re)score 
and view sleep EEG data and previously detected events, 
as well as aids in scoring and detection decisions. 
It comes as a standalone commandline tool for Windows, Linux and Mac, 
or can be integrated as toolbox in Matlab. But the functionality does not stop there...

The SpiSOP and FieldTrip software is free but copyrighted software, distributed
under the terms of the GNU General Public Licence as published by
the Free Software Foundation (either version 2, or at your option
any later version). See the file COPYING.txt for more details.

The functions in the SpiSOP toolbox are copyrighted by their respective authors:
  Frederik D. Weber, Germany, Tübingen, spisop@frederikweber.de

The SpiSOP software is a toolbox, i.e. a library with functions.
The release includes functions from other toolboxes that are covered
under their respective licenses. See /fieldtrip_fw and /fieldtrip_fw/external for details.

For a documentation of the toolbox see the www.spisop.org.

Thanks to the implementers and developers and funding organisations and persons of FieldTrip and the code used therein, it's a wonderful toolbox.
Thanks to the developers and researches of the algorithms and methods for spindle and slow oscillation detection.
Thanks to the people that helped in the process.