Introduction
Using forearm electromyography (EMG) signals as control input to control the prostheteic hands in LabVIEW in real-time. In other words, when the subject is moving index finger, prosthetic hand is also moving its index finger.
LabVIEW is powerful for real-time signal processing and controlling application. I first pre-process the recorded forearm EMG singals (muscle cell signals) in LabVIEW by removing the bias, and applying bandpass filters to obtain the signals with the frequency of interest.
Then extract several signal features such as Root Mean Square, Mean Frequency, Mean Absolute Value, Waveform Length, and Cross-correlation.
Develop a classification model using artificial neural network (ANN) with multilayer perceptrons (MLPs) and pre-trained the model offline.
After that, I create device connection, configure the device, and then start data streaming for signal acquisition. Real-time analysis is performed with the accuracy around 80%. Here I also created a simple user interface.
Feel free to contact me for more details.