@inproceedings{509dd6e5ad7d48368b97fd9b6764a79f,
title = "Effect of Neurofeedback Based on Imaginary Movement in Parkinson's Disease",
abstract = "Parkinson's disease (PD) is a common neurodegenerative disease with characteristic bioelectrical abnormalities. Neurofeedback (NF) is effective in alleviating the symptoms of PD. To improve the efficiency of NF training, we proposed an NF scheme based on imaginary movement strategies. In this study, 14 PD patients were recruited and randomly divided into EEG and sham groups. All participants completed 5 NF training sessions within 2 weeks. The clinical scale results showed that NF training effectively improved motor and non-motor symptoms. Gamma oscillations in the occipital and temporal lobes were significantly increased in the EEG group, which may be due to SMR-y cross-frequency coupling and the effect of NF training on the modulation of ECG characteristics, resulting in the relief of motor and non-motor symptoms of PD. This preliminary study confirmed that NF based on imaginary movement has a significant effect on the clinical signs of PD patients, providing ideas for future non-invasive treatment.",
keywords = "electroencephalogram, imaginary movement, neurofeedback, Parkinson's disease, phase-amplitude coupling",
author = "Xingyu Han and Zhongyan Shi and Guangying Pei and Boyan Fang and Tianyi Yan",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 17th International Conference on Complex Medical Engineering, CME 2023 ; Conference date: 03-11-2023 Through 05-11-2023",
year = "2023",
doi = "10.1109/CME60059.2023.10565497",
language = "English",
series = "2023 17th International Conference on Complex Medical Engineering, CME 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "83--87",
booktitle = "2023 17th International Conference on Complex Medical Engineering, CME 2023",
address = "United States",
}
