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Hardware Powered Ultra Low Latency (HarPULL) Brain-State Dependent TMS Technologyстатья
- Авторы: Fedosov Nikita, Nekrasova Julia, Makarova Milana, Shevtsov Oleg, Medvedeva Daria, Ossadtchi Alexei
- Сборник: 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine (CSGB)
- Год издания: 2023
- Место издания: IEEE
- DOI: 10.1109/csgb60362.2023.10329831
- Аннотация: The paper introduces a novel hardware-software complex for the low latency real time phase-dependent transcranial magnetic stimulation (TMS) neurofeedback. The software with key elements implemented on the board of the EEG-recording device accurately tracks the sensorimotor rhythm phase with minimal time-delay and immediately sends the trigger to the TMS-device. An accurate phase estimation is achieved by proper Kalman filter-based state-space modeling of brain rhythm. Our experiments demonstrate the system's viability and its almost instant reaction on the target brain event occurrence. Our results potentially make neurofeedback, cortical mapping, therapeutic TMS-interventions and other applications more reliable and efficient.
- Добавил в систему: Некрасова Юлия Юрьевна