GitHub - PrithivirajManiram/Robotic-EXoskeleton-for-Arm-Rehabilitation-REXAR-: Rehabilitation of people afflicted with elbow joint ailments is quite challenging. Studies reveal that rehabilitation through robotic devices exhibits promising results, in particular exoskeleton robots. In this work, 1 degree of freedom active upper-limb exoskeleton robot with artificial intelligence aided myoelectric control system has been developed for elbow joint rehabilitation. The raw surface electromyogram (sEMG) signals from seventeen different subjects for five different elbow joint angles were acquired using the Myo armband. Time-domain statistical features such as waveform length, root mean square, variance, and a number of zero crossings were extracted and the most advantageous feature was investigated for Artificial Neural Network (ANN) – a backpropagation neural network with Levenberg-Marquardt training algorithm and Support Vector Machine (SVM) – with Gaussian kernel. The results show that waveform length consumes the least amount of computation time. With waveform length as an input feature, ANN and SVM exhibited an average overall classification accuracy of 91.33% and 91.03% respectively. Moreover, SVM consumed 36% more time than ANN or classification.

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Rehabilitation of people afflicted with elbow joint ailments is quite challenging. Studies reveal that rehabilitation through robotic devices exhibits promising results, in particular exoskeleton robots. In this work, 1 degree of freedom active upper-limb exoskeleton robot with artificial intelligence aided myoelectric control system has been de…

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Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
EXO-IEE Transaction format (1).pdf		EXO-IEE Transaction format (1).pdf
Exoskeleton with support.SLDASM		Exoskeleton with support.SLDASM
Exoskeleton.SLDASM		Exoskeleton.SLDASM
Feature_Extraction.m		Feature_Extraction.m
README.md		README.md
emgWaveformLen.m		emgWaveformLen.m
emg_record.m		emg_record.m
emgvariance.m		emgvariance.m
zero_crossing.m		zero_crossing.m

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The ANN and SVM are developed using MATLAB . The coding files (.m files) have been uploaded You will be needing the Myo_Interface and Arduino_interface library for the code to work The exoskeleton is designed using SolidWorks