We gladly accept contributions of papers, software, and signals related to EMG decomposition. We also want to hear your ideas about how this website can better serve the needs of the decomposition community.

We are not able to accept automatic uploads at this time. If you would like to contribute something, please contact


PDFs of papers and reports related to EMG decomposition are welcome.


Each signal should be accompanied, if possible, by a WFDB header file that describes the signal and specifies the data format. Information should include gender, age, muscle, experimental condition, level of contraction, electrode configuration, amplifier filter settings, and other relevant remarks. It should also include the name or laboratory of the contributor, the date and time on which the signal was recorded, and an identifier that uniquely identifies the signal in the contributor's data base. Neither the header file, the file names, or the data file itself may contain any information that would personally identify an individual human subject. Signals from patients with neuromuscular disorders will be accepted to illustrate technical issues related to decomposition. However, it is not the purpose of this website to serve as a definitive database of disorders or a source of diagnostic advice.

Signals can also be accompanied by an annotation file that lists the discharge times of the MUAPs in the signal. This should be a text file with one line for each discharge. Each line should contain the time of the discharge in seconds from the start of the signal (in floating point format) and a MUAP identifier (an integer between 1 and N, where N is the number of MUAP trains in the signal).

Contributors are responsible for making sure that their contributions are in accordance with the policies of their local Institutional Review Board. (more info)


Investigators are encouraged to contribute software related to EMG decomposition and analysis. We suggest that programs be written in Matlab because it is widely known and used in the scientific community, platform independent, relatively easy to learn, maintain, and expand, and fast enough for many applications. The Matlab environment also offers many advantages to the user, including the convenience of manipulating and plotting decomposition results using the command line interface.



Veterans Affairs Palo Alto Rehabilitation Research and Development Center
National Institute of Neurological Disorders and Stroke