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Design of mechanism for pronation and supination of the upper limb prostheses
Rebenda, David ; Košťál, David (referee) ; Paloušek, David (advisor)
The goal of of this work is to propose a mechanism for pronation and supination of the upper limb prosthesis and its subsequent implementation of functional prototype. The teoretical part summarizes the basic types of forearm amputation and the effect of restricting rotation of the forearm. It also describes the basic distribution of upper limb prostheses and drive types. Construction design includ complete technical documentation is made in Autodesk Inventor Professional 2013 and Rhinoceros 5.0 SR8. The prototype is made of aluminium and ABS plastic.
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Active prostetic hand
Brenner, Maximilian ; Sekora, Jiří (referee) ; Harabiš, Vratislav (advisor)
BACKGROUND: Based on mainly vascular diseases and traumatic injuries, around 40,000 upper limb amputations are performed annually worldwide. The affected persons are strongly impaired in their physical abilities by such an intervention. Through myoelectric prostheses, affected persons are able to recover some of their abilities. METHODS: In order to control such prostheses, a system is to be developed by which electromyographic (EMG) measurements on the upper extremities can be carried out. The data obtained in this way should then be processed to recognize different gestures. These EMG measurements are to be performed by means of a suitable microcontroller and afterwards processed and classified by adequate software. Finally, a model or prototype of a hand is to be created, which is controlled by means of the acquired data. RESULTS: The signals from the upper extremities were picked up by four MyoWare sensors and transmitted to a computer via an Arduino Uno microcontroller. The Signals were processed in quantized time windows using Matlab. By means of a neural network, the gestures were recognized and displayed both graphically and by a prosthesis. The achieved recognition rate was up to 87% across all gestures. CONCLUSION: With an increasing number of gestures to be detected, the functionality of a neural network exceeds that of any fuzzy logic concerning classification accuracy. The recognition rates fluctuated between the individual gestures. This indicates that further fine tuning is needed to better train the classification software. However, it demonstrated that relatively cheap hardware can be used to create a control system for upper extremity prostheses.
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Possibilities of prosthetic upper limb fitting in cycling
Doležalová, Hana ; Čichoň, Rostislav (advisor) ; Půlpán, Rudolf (referee)
Bachelor thesis give an overview of possible solutions in upper limbs prosthetic fitting which is suitable for cycling. And provide enough information on modifications that should be performed on a bicycle so that it can be used by humans with upper extremity prostheses. It can be an essential guide for anyone looking for a solution that would allow a person with an amputated upper limb again sit on the bike. Keywords: amputation, upper limb prosthesis, prosthetic fitting, cycling
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Active prostetic hand
Brenner, Maximilian ; Sekora, Jiří (referee) ; Harabiš, Vratislav (advisor)
BACKGROUND: Based on mainly vascular diseases and traumatic injuries, around 40,000 upper limb amputations are performed annually worldwide. The affected persons are strongly impaired in their physical abilities by such an intervention. Through myoelectric prostheses, affected persons are able to recover some of their abilities. METHODS: In order to control such prostheses, a system is to be developed by which electromyographic (EMG) measurements on the upper extremities can be carried out. The data obtained in this way should then be processed to recognize different gestures. These EMG measurements are to be performed by means of a suitable microcontroller and afterwards processed and classified by adequate software. Finally, a model or prototype of a hand is to be created, which is controlled by means of the acquired data. RESULTS: The signals from the upper extremities were picked up by four MyoWare sensors and transmitted to a computer via an Arduino Uno microcontroller. The Signals were processed in quantized time windows using Matlab. By means of a neural network, the gestures were recognized and displayed both graphically and by a prosthesis. The achieved recognition rate was up to 87% across all gestures. CONCLUSION: With an increasing number of gestures to be detected, the functionality of a neural network exceeds that of any fuzzy logic concerning classification accuracy. The recognition rates fluctuated between the individual gestures. This indicates that further fine tuning is needed to better train the classification software. However, it demonstrated that relatively cheap hardware can be used to create a control system for upper extremity prostheses.
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Possibilities of prosthetic upper limb fitting in cycling
Doležalová, Hana ; Čichoň, Rostislav (advisor) ; Půlpán, Rudolf (referee)
Bachelor thesis give an overview of possible solutions in upper limbs prosthetic fitting which is suitable for cycling. And provide enough information on modifications that should be performed on a bicycle so that it can be used by humans with upper extremity prostheses. It can be an essential guide for anyone looking for a solution that would allow a person with an amputated upper limb again sit on the bike. Keywords: amputation, upper limb prosthesis, prosthetic fitting, cycling
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Design of mechanism for pronation and supination of the upper limb prostheses
Rebenda, David ; Košťál, David (referee) ; Paloušek, David (advisor)
The goal of of this work is to propose a mechanism for pronation and supination of the upper limb prosthesis and its subsequent implementation of functional prototype. The teoretical part summarizes the basic types of forearm amputation and the effect of restricting rotation of the forearm. It also describes the basic distribution of upper limb prostheses and drive types. Construction design includ complete technical documentation is made in Autodesk Inventor Professional 2013 and Rhinoceros 5.0 SR8. The prototype is made of aluminium and ABS plastic.
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