Classification Of 41 Hand And Wrist Movements Via Surface Electromyogram Using Deep Neural Network
Objective
The objective of this study is to develop a highly accurate and robust deep neural network-based classification system for distinguishing and classifying 41 distinct hand and wrist movements using surface electromyogram (EMG) signals.
Abstract
In this groundbreaking study, the primary aim is to construct a cutting-edge deep neural network (DNN) classification system, renowned for its precision and resilience, specifically tailored for the discernment and categorization of an extensive repertoire comprising 41 unique hand and wrist movements. The methodology hinges on harnessing surface electromyogram (ENG) signals, capitalizing on the intricate patterns of electrical muscle activity, to empower this neural network with the capacity to differentiate and classify these diverse gestures. This research transcends the conventional limitations in hand and wrist movement analysis, promising a profound impact on fields ranging from rehabilitative medicine to human-computer interaction. By pushing the boundaries of machine learning and electromyography, this study seeks to elevate the accuracy and reliability of gesture recognition systems, thereby fostering more natural and intuitive interactions between humans and technology.
Keywords: Deep Neural Network, surface electromyogram (ENG) signals, 41 Hand and Wrist Movements.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is an Image/pixel?
· About image formats
· Introduction to Image Processing
· How digital image is formed
· Importing the image via image acquisition tools
· Analyzing and manipulation of image.
· Phases of image processing:
o Acquisition
o Image enhancement
o Image restoration
o Color image processing
o Image compression
o Morphological processing
o Segmentation etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Paper Publishing
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