Real-time index for predicting successful golf putting motion using multichannel EEG.

Area of Science:

• Neuroscience
• Sports Science
• Motor Control

Background:

• Goal-directed sport performance relies on complex internal cognitive and motor processes.
• Understanding internal factors like estimation, strategy, and decision-making is crucial for performance improvement.
• Cortical activity, somatosensory information, attention, and motor control are key internal elements in sports skills.

Purpose of the Study:

• To identify neurophysiological criteria for predicting golf putt success.
• To investigate the relationship between brain activity patterns and putting accuracy in skilled golfers.
• To explore the potential for a real-time prediction system for golf putting.

Main Methods:

• Recruited five skilled right-handed golfers for the study.
• Utilized power spectral analysis of electroencephalography (EEG) data, comparing pre-movement and movement periods.
• Classified successful and unsuccessful putts based on EEG signals from specific cortical areas (Fz, Pz, Cz, C3, C4).

Main Results:

• Identified specific EEG patterns indicative of successful putts: high alpha power at C4, theta power at Fz, and theta and high alpha power at Pz.
• These brain activity patterns can be calculated as indices for predicting golf putt success.
• Proposed a real-time monitoring system with a graphical user interface (GUI) for preliminary application.

Conclusions:

• Specific patterns of alpha and theta brainwave activity can predict golf putt success.
• The findings support the development of a real-time golf putting prediction system.
• Future work aims to integrate this system into a biofeedback mechanism to enhance putting accuracy, requiring larger sample sizes for validation.