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UM E-Theses Collection (澳門大學電子學位論文庫)

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Title

Neurofeedback training for improving physical balance in healthy young adults : a pilot study

English Abstract

NEUROFEEDBACK TRAINING FOR IMPROVING PHYSICAL BALANCE IN HEALTHY YOUNG ADULTS: A PILOT STUDY By Qu Xiaoting Thesis Supervisor: Dr. Feng Wan Master of Science in Electrical and Computer Engineering Balance ability is closely associated with human’s physical capability in various aspects from sports performance in athletes, reduced motor functional control in elder people, and the falls in the patients with neurologic disease such as stroke. The subsystems made up the postural control system include the central nervous system (CNS) and musculoskeletal system. Generally, physical exercise program focused on the musculoskeletal system is the mostly used approach for balance improvement, however, sometime it’s dangerous for individuals to perform such exercises as treatment methods. A novel solution to balance improvement problem focused on CNS is neurofeedback training. Neurofeedback training (NFT) is an operant conditioning procedure in which participants learn to self-regulate the brain activity and in doing so their behavioral performance may be potentially improved. Previous study have already used a specific NFT protocol successfully help the patients with their balance problem which included increasing 15-18 Hz and decreasing 4-7 Hz simultaneously. However, no such researches apply the NFT protocol on healthy young people. In this project, we followed an existing NFT protocol to investigate the effects on physical balance of young healthy adults. The whole project started from the balance evaluation method and the Wii Balance Board was used to acquire center of pressure information used for balance assessment. Neurofeedback training experiments were conducted with a total number of 36 subjects. Experiments results consisted of three parts. Firstly, the balance performance as the achievement of NFT, unfortunately, even some parameters showed significant difference between pre and posttests, it turned out the NFT is not the effect factors for this result. When it comes to EEG analysis, we can find out that the training parameter beta amplitude to theta amplitude ratio (BTR) has significant positive trend over sessions which were consistent with our training goal. However, it seemed this change only caused by the theta band without the beta band, which is not expected as the purpose set. EEG from non-training locations were also analyzed and the results were similar as in training location. Finally, mental strategies are investigated. Even though no clear conclusion can be drawn, we can find out that NFT researches related to beta and theta frequency band were usually related to attention training, mental strategies requiring attention will perform better in this kind of NFT.

Issue date

2015.

Author

Qu, Xiao Ting

Faculty

Faculty of Science and Technology

Department

Department of Electrical and Computer Engineering

Degree

M.Sc.

Subject

Biofeedback training

Supervisor

Wan, Feng

Files In This Item

Full-text (Intranet only)

Location
1/F Zone C
Library URL
991000777279706306