Identifying single motor units from EMG data

I need to identify single motor units from EMG data and have been unable to find anything on the NI web site that could help. I have identified a third party program, Spike 2 from Cambridge Electronic Design (CED), that is able to do the job however I have already go a large investment in NI hardware and software and do not want to have to buy all the CED hardware. I was wondering if anyone knew if it were possible to control the spike 2 program from inside LabVIEW (in close to real time), or if there was a LabVIEW based solution that I have been unable to find.

Sorry for the confusion.
This post is regarding template matching/detection of events from a nosy analogue signal. It is a medical application, not a motor/servo application. The term �motor unit� refers to the action potentials found in electrical recordings taken from muscles (EMG). By identifying the occurrence of these events we can determine properties of the nerves controlling these muscles. However identifying these events is very difficult as the recorded signals are noisy and the shapes of these units change over time. Many researchers have attempted to design computer-based solutions to this problem but is has only been with recent improvements in computer power that a solely software based solution for real time pattern matching has been possibl
e. Although this application is specific to medical research (and electrical recordings of nervous system activity in particular) the number of research laboratories around the world attempting to perform such analysis is large enough that I though a LabVIEW base solution may exist.
Barring a LabVIEW based solution I was wondering if anyone knew if it were possible for the data to be acquired in LabVIEW then directed to Spike2 (the most common program used for this application) in almost real-time. I know I can record data in LabVIEW and save it as a text file then open it up in Spike2 but I do not know if I can stream the data into Spike2 online. Online processing of the data is necessary to determine the progress of the experiments.

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