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Review
. 2021 May 28:15:638369.
doi: 10.3389/fnins.2021.638369. eCollection 2021.

A Review of Neurofeedback Training for Improving Sport Performance From the Perspective of User Experience

Anmin Gong  1 , Feng Gu  1 , Wenya Nan  2 , Yi Qu  1 , Changhao Jiang  3 , Yunfa Fu  4
Affiliations
Review

A Review of Neurofeedback Training for Improving Sport Performance From the Perspective of User Experience

Anmin Gong et al. Front Neurosci. .

Abstract

Neurofeedback training (NFT) is a non-invasive, safe, and effective method of regulating the nerve state of the brain. Presently, NFT is widely used to prevent and rehabilitate brain diseases and improve an individual's external performance. Among the various NFT methods, NFT to improve sport performance (SP-NFT) has become an important research and application focus worldwide. Several studies have shown that the method is effective in improving brain function and motor control performance. However, appropriate reviews and prospective directions for this technology are lacking. This paper proposes an SP-NFT classification method based on user experience, classifies and discusses various SP-NFT research schemes reported in the existing literature, and reviews the technical principles, application scenarios, and usage characteristics of different SP-NFT schemes. Several key issues in SP-NFT development, including the factors involved in neural mechanisms, scheme selection, learning basis, and experimental implementation, are discussed. Finally, directions for the future development of SP-NFT, including SP-NFT based on other electroencephalograph characteristics, SP-NFT integrated with other technologies, and SP-NFT commercialization, are suggested. These discussions are expected to provide some valuable ideas to researchers in related fields.

Keywords: brain nerve regulation; electroencephalograph; neurofeedback training; sport performance; user experience.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Principle block diagram of electroencephalograph (EEG) neurofeedback training (NFT) system. A typical NFT system usually consists of four stages: (1) signal acquisition, (2) feature extraction, (3) feature conversion, and (4) feedback learning.
FIGURE 2
FIGURE 2
Different types of SP–NFT schemes. (A) Simulated training scheme in which participants recall the actual sport process. The feedback feature is the EEG characteristics when athletes recall the best sport performance. (B) Attention-focusing training scheme, during which participants remain highly focused. The feedback feature is inhibition theta or enhancement SMR. (C) Relaxation training scheme, during which participants maintain a relaxed mind. The feedback feature is increasing theta or inhibition alpha. (D) Monitoring-guided training scheme, in which participants directly perform sport behavior at an optimal arousal level 9.
See this image and copyright information in PMC

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