The goal was to create precise hardware that would be able to measure signal of myopotentials from defined area of forearm for the computer analysis without external noise and with right amplification. The second goal was to program an algorithm which could classify specific gestures of hand based on an analy17sis of myopotencial signals. The computer software was programmed in C# programming language. Signal processing and drawing to user interface was in real time. The one of five possible gestures that user made was analysed by using fuzzy logic and designed system of scaling. It was developed fuzzy classification which is able to recognize gestures with high accuracy.
Measurement system for classification of hand's gesture
Proto A.Penultimo
;
2018
Abstract
The goal was to create precise hardware that would be able to measure signal of myopotentials from defined area of forearm for the computer analysis without external noise and with right amplification. The second goal was to program an algorithm which could classify specific gestures of hand based on an analy17sis of myopotencial signals. The computer software was programmed in C# programming language. Signal processing and drawing to user interface was in real time. The one of five possible gestures that user made was analysed by using fuzzy logic and designed system of scaling. It was developed fuzzy classification which is able to recognize gestures with high accuracy.| File | Dimensione | Formato | |
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05_2018_Measurement_System_for_Classification_of_Hands_Gesture.pdf
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