diplomsko delo
Maja Budna (Author), Gregor Geršak (Mentor), Valentina Stanić (Co-mentor)

Abstract

Diplomska naloga se osredotoča na razvoj sistema, ki združuje elektroencefalografijo (EEG) z aktuatorjem - robotsko roko. EEG je metoda merjenja možganske aktivnosti preko elektrod in se pogosto uporablja na področju interakcije med možgani in računalnikom. Poleg sestave in krmiljenja robotske roke je naš projekt obsegal tudi prenos podatkov med EEG merilno napravo in aktuatorjem ter analizo EEG signalov. Sistem smo zasnovali tako, da se robotska roka ob visoki pozornosti uporabnika stisne v pest, ob nizki pa se sprosti v odprto dlan. Rezultati prikazujejo delujoč sistem, ki s pomočjo merjenja EEG signalov upravlja mehansko roko. Sistem je uporaben za nadaljnje raziskave na področju protetike ter interakcije med možgani in računalnikom. Potencialna izboljšava točnosti sistema je zmanjšanje šuma, ki je posledica občutljivosti EEG signalov na mišično aktivnost.

Keywords

EEG signali;možganski valovi;mikrokrmilniki;robotske roke;interakcija med človekom in računalnikom;zaznavanje pozornosti;3D tiskanje;univerzitetni študij;Elektrotehnika;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FE - Faculty of Electrical Engineering
Publisher: [M. Budna]
UDC: 007.52:616.831-073.7(043.2)(0.034.2)
COBISS: 200154371 Link will open in a new window
Views: 88
Downloads: 26
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Other data

Secondary language: English
Secondary title: EEG controlled robotic hand
Secondary abstract: The thesis focuses on the development of a system that combines electroencephalography (EEG) with an actuator – a robotic arm. EEG is a method of measuring brain activity via electrodes and is often used in the field of brain-computer interaction. In addition to assembling and controlling the robotic arm, the project also involved the transfer of data between the EEG measuring device and the actuator, as well as the analysis of EEG signals. We designed the system so that the robotic arm clenches into a fist when the user is highly focused and relaxes into an open palm when the attention is low. The results demonstrate a functioning system that uses EEG signal to control a mechanical arm. The system is useful for further research in the fields of prosthetics and brain-computer interaction. A potential improvement in system accuracy involves reducing the noise caused by the sensitivity of EEG signals to muscle activity.
Secondary keywords: EEG signals;brain waves;microcontroller;robotic arm;Human-Computer Interaction;attention detection;3D printing;
Type (COBISS): Bachelor thesis/paper
Study programme: 1000313
Thesis comment: Univ. v Ljubljani, Fak. za elektrotehniko
Pages: 1 spletni vir (1 datoteka PDF (XX, 45 str.))
ID: 24473682