Publication: Real-time index for predicting successful golf putting motion using multichannel EEG
Issued Date
2012-12-14
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ISSN
1557170X
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2-s2.0-84870841995
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Mahidol University
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SCOPUS
Bibliographic Citation
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. (2012), 4796-4799
Suggested Citation
Piyachat Muangjaroen, Yodchanan Wongsawat Real-time index for predicting successful golf putting motion using multichannel EEG. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. (2012), 4796-4799. doi:10.1109/EMBC.2012.6347039 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/13997
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Title
Real-time index for predicting successful golf putting motion using multichannel EEG
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Abstract
A skill in goal-directed sport performance is an ability involving with many factors of both external and internal concernment. External factors are still developed while internal factors are challenged topic to understand for improving the performance. Internal concernment is explained an effective performance as estimation, solving strategy, planning and decision on the brain. These conjunctions are relevant to somatosensory information, focus attention and fine motor control of cortical activity. Five skilled right-handed golfers were recruited to be subjected of studying the criteria on how to predict golf putt success. Each of their putts was calculated in power spectral analysis by comparing to the pre-movement period. Successful and unsuccessful putt were classified by focusing on the frontal-midline(Fz), parietal-midline(Pz), central midline(Cz), left central(C3) and right central(C4) which supported by few consistency studies that they are related to a primary sensory motor area, focus attention and working memory processing. Results were shown that high alpha power on C4, theta power on Fz, theta power and high alpha power on Pz can be calculated to use as index of predicting golf putt success. Real-time monitoring system with friendly GUI was proposed in this study as promising preliminary study. Expected goal in the future is to apply this real-time golf putting prediction system into a biofeedback system to increase the golf putting's accuracy. However, it still needs more subjects to increase credibility and accuracy of the prediction. © 2012 IEEE.