MyoRun

This week, and including last week, I worked on narrowing down the feature extraction and classification pipeline to be used for classifying EMG signals in our project. After discussing with Tarana to understand the expected data input to the SVM classifier, I created a 1×15 matrix for the feature vector to which included the max value for each electrode, five binary signals about whether or not a particular electrode fired during the recorded signal, and the peak frequency from the…

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This week I dove into applying different data dimensionality reduction and classification methods to our data. First, with the primary data that we have collected, I created a visualization of the peaks of the recorded signal data in order to see if there might be any obvious trends in the correlation between movements and the peak of their signals. This graph shows the max value for the voltage recorded by each electrode for each sample of each movement from the…

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This week for capstone I spent the majority of my time organizing the classification algorithm approach to our EMG data. A major decision factor going into this classification of the data depends on how the data is recorded. I found that if the data is recorded in a continuous stream of repeated actions, the best approach is to use wavelet transform on the data in order to identify a basis function and the scaled and shifted versions of it. This…

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This week the data collection process was bolstered and thanks to Tarana’s hard work in coordinating the hardware system of the EMG, we were able to collect data recorded from more than a single electrode. Last week’s milestone was collecting data from a single electrode and visualizing the signal from different recorded movements over time. This week, toward the end of the week we got data collected for all the movement collected from five electrodes on the forearm. This upcoming…

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This week substantial time was spent working on the written draft of the Project Report. It was important that we made the report as thorough as possible in order to create a good starting point for our final report. This week I began work with the data collected from a single EMG electrode for wrist flexion and extension data. Two sample trials can be seen in the image below.  The data collection portion of our project is a little behind…

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This week I spent time furthering specifics for the data collection experimental procedure of our project. Additionally, I have been exploring common data processing techniques for classifying EMG data, specifically useful feature extraction techniques such as Wavelet Transform. I will also be presenting during the Design Review Presentation for our team next week, so I have been working on the slides and preparing the presentation. Our project is currently on track and the next step is to collect the EMG…

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This week I spent time doing a thorough literature review of various EMG papers. I learned more about the EMG experimentation set up process in order to design our own experiment to collect EMG forearm data. Reading through EMG papers I found common classification algorithms and successful features extracted to improve EMG movement classification.  I shared with the team my primary experimental set up for data collection. After initial discussion, we decided on initial electrode placement for when we perform…

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