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Analysis of EMG Signal for Prosthetic hand based on Fuzzy Logic Technique
Ollé, Tamás ; Kolářová, Jana (oponent) ; Pathak, Pawan Kumar (vedoucí práce)
The human hand is an important limb essential for movement, grasping, perception , as well as being a vital part of the human body for sensation and communication. It is a classic example of how a complex mechanism can be implemented, capable of realizing very tedious and useful tasks using a very effective combination of mechanisms, sensing, actuation and control functions. Electrmyogram (EMG) was originally developed for the detection and further correction of muscular disorder. Further applications were soon evident, most importantly in epilepsy, and finally it became popular due to the introduction of prosthetics, specifically body powered prosthesis. EMG recording is used for studying the functional state of the muscle undr various motions when it undegoes stress and tension. The goal of this project is to develop electromyogram (EMG) classification methods that shall help in applications like real-time system. First Phase of this project was Data Acquisition. Real time data using PC based EMG Monitoring System (BIOPAC) was recorded and a complete data set of different subjects was obtained. This EMG data was converted from ASCII file to a readable form for MATLAB. Second Phase of this project was Feature Extraction. Five traditional parametric features, namely Integrated EMG (IEMG), Variance (VAR), Zero Crossings (ZC), Slope Sign Changes (SSC) and Waveform Length (WL) were extracted. Third phase of this project was Classification of EMG patterns using fuzzy logic techniques. The results were quite promising.
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Řízení robotické ruky pomocí virtuální reality
Sláma, Pavel ; Bílek, Michal (oponent) ; Vyroubal, Petr (vedoucí práce)
Tato bakalářská práce se zabývá možností řešení řízení robotické ruky pomocí virtuální reality. K realizaci je využita protetická ruka z projektu InMoov. Práce popisuje základní výrobní principy 3D tisku a zabývá se materiály vhodnými pro konstrukci zvolené robotické ruky. Popisuje funkci a způsob řízení servomotorů, ovládání za využití platformy Arduino komunikující s počítačem za softwarové podpory prostředí MyRobotLab. Pro snímání pohybu je použit ovladač pro virtuální realitu Leap Motion.
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Active Prosthetic Hand
Svoboda, Michal
The aim of this thesis is to propose and produce prototype of active hand prosthesis. Prototype is based on myoelectric prosthesis principle, therefore it is meant to be controlled by EMG signals. In this specific case signals will be scanned from healthy arm. Arduino UNO development kit was chosen as the main controller. For measuring EMG muscle activity Shield EKG/EMG Olimax was selected.
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Řízení robotické ruky pomocí virtuální reality
Sláma, Pavel ; Bílek, Michal (oponent) ; Vyroubal, Petr (vedoucí práce)
Tato bakalářská práce se zabývá možností řešení řízení robotické ruky pomocí virtuální reality. K realizaci je využita protetická ruka z projektu InMoov. Práce popisuje základní výrobní principy 3D tisku a zabývá se materiály vhodnými pro konstrukci zvolené robotické ruky. Popisuje funkci a způsob řízení servomotorů, ovládání za využití platformy Arduino komunikující s počítačem za softwarové podpory prostředí MyRobotLab. Pro snímání pohybu je použit ovladač pro virtuální realitu Leap Motion.
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Analysis of EMG Signal for Prosthetic hand based on Fuzzy Logic Technique
Ollé, Tamás ; Kolářová, Jana (oponent) ; Pathak, Pawan Kumar (vedoucí práce)
The human hand is an important limb essential for movement, grasping, perception , as well as being a vital part of the human body for sensation and communication. It is a classic example of how a complex mechanism can be implemented, capable of realizing very tedious and useful tasks using a very effective combination of mechanisms, sensing, actuation and control functions. Electrmyogram (EMG) was originally developed for the detection and further correction of muscular disorder. Further applications were soon evident, most importantly in epilepsy, and finally it became popular due to the introduction of prosthetics, specifically body powered prosthesis. EMG recording is used for studying the functional state of the muscle undr various motions when it undegoes stress and tension. The goal of this project is to develop electromyogram (EMG) classification methods that shall help in applications like real-time system. First Phase of this project was Data Acquisition. Real time data using PC based EMG Monitoring System (BIOPAC) was recorded and a complete data set of different subjects was obtained. This EMG data was converted from ASCII file to a readable form for MATLAB. Second Phase of this project was Feature Extraction. Five traditional parametric features, namely Integrated EMG (IEMG), Variance (VAR), Zero Crossings (ZC), Slope Sign Changes (SSC) and Waveform Length (WL) were extracted. Third phase of this project was Classification of EMG patterns using fuzzy logic techniques. The results were quite promising.
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