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Visar resultat 1 - 5 av 21 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Developing a portable, customizable, single-channel EEG device for homecare and validating it against a commercial EEG device

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Máté Károly Tóth; [2023]
    Nyckelord :Electroencephalography EEG ; Portable EEG; Single-channel EEG; Commercial EEG; Brain-machine interface; Prototype development; Elektroencefalografi EEG ; Bärbar EEG; Enkanaligt EEG; Kommersiellt EEG; Hjärna-maskin-gränssnitt; Prototyputveckling;

    Sammanfattning : There are several commercial electroencephalography (EEG) devices on the market; however, affordable devices are not versatile for diverse research applications. The purpose of this project was to investigate how to develop a low-cost, portable, single-channel EEG system for a research institute that could be used for neurofeedback-related applications in homecare. LÄS MER

  3. 2. Using machine learning to analyse EEG brain signals for inner speech detection

    Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Lisa Jonsson; [2022]
    Nyckelord :Machine learning; Convolutional neural network; Inner speech; Brain computer interface; Electroencephalography;

    Sammanfattning : Research on brain-computer interfaces (BCIs) has been around for decades and recently the inner speech paradigm was picked up in the area. The realization of a functioning BCI could improve the life quality of many people, especially persons affected by Locked-In-Syndrome or similar illnesses. LÄS MER

  4. 3. Closed-Loop EEG BCI: VR and Electrical Stimulation to treat Neuropathic Pain

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Shreya Kohli; [2021]
    Nyckelord :;

    Sammanfattning : Chronic pain is a life-threatening disease affecting over 20% of theU.S. adult population as of 2016. It impacts the physical as well as emotional components of a human being significantly affecting a person’s quality of life. LÄS MER

  5. 4. Acceleration of Machine-Learning Pipeline Using Parallel Computing

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

    Författare :Xavante Erickson; [2021]
    Nyckelord :acceleration; ray; accelerator; numpy; machine-learning; machine; learning; optimization; parallelization; speedup; profiling;

    Sammanfattning : Researchers from Lund have conducted research on classifying images in three different categories, faces, landmarks and objects from EEG data [1]. The researchers used SVMs (Support Vector Machine) to classify between the three different categories [2, 3]. LÄS MER

  7. 5. NSGA-II DESIGN FOR FEATURE SELECTION IN EEG CLASSIFICATION RELATED TO MOTOR IMAGERY

    Kandidat-uppsats, Mälardalens högskola/Akademin för innovation, design och teknik

    Författare :Robin Johansson; [2020]
    Nyckelord :;

    Sammanfattning : Feature selection is an important step regarding Electroencephalogram (EEG) classification, for a Brain-Computer Interface (BCI) systems, related to Motor Imagery (MI), due to large amount of features, and few samples. This makes the classification process computationally expensive, and limits the BCI systems real-time applicability. LÄS MER