The Multi Layer Perceptron is working much better now. We found that randomizing the order in which the EMG points go into the text file that is read actually have a large impact on the accuracy of the code. Our randomizing process was in Excel, where we numbered all of the data in another column 1 through 5. The data was then reorganized by that new number so that the data was shuffled. This process was repeated for several more columns. At the end of this, the data was put back into MLP, and this resulted in a much lower guess error. It went from 80% to 8%. This is a large accomplishment and means that we can successfully classify data and we can also successfully create more data to increase the accuracy of the MLP.Challenges we have come across were the high error rate of the Multi Layer Perceptron which we had initially. Another issue is that the data that we are using is fake data based off of the limited amount of real data that we have, so the high success rate may be a result of the fact that the data is easier to guess when it is artificially created rather than when it is constructed. When we gather more data, we shall see.
At this point in time, we now have the Multi Layer Perceptron working, so our next steps will be to gather more data and preferably to not rely on point generation. We will try and use multiple EMG Spikershields at the same time in order to gather more accurate, real time, data. Another thing that we would like to do is to streamline the entire process that we have, as at the moment every step is separate and time consuming, and it is all split up between different programs and software. If we could get all of the steps to happen at once, that would be a large improvement over what we currently have.
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