Article 2 (Part 1 of 2) | Feb. 18, 2016
Understanding the inner mechanisms of the mind and body to find the essence of fine skills and methods for enhancing sports performance (Part 1)
Using ICT to comprehensively understand mental and physical reactions
The key to understanding the processes of the implicit brain functions are the various reactions seen from outside the human body. The approach of this research is to comprehensively collect and analyze these reactions by combining data mining and hypothesis verification.
Using ICT to comprehensively understand the reactions of the brain and body
—In the first of this series, we interviewed Makio Kashino of the Sports Brain Science Project about the nature of his research, and his thoughts and motivation for research. Please tell us about the particular approach of your research.
Kashino: The goal of our research is to elucidate the implicit brain functions related to sports by fully utilizing ICT, and develop methods to enhance athletic performance based on the knowledge gained from that, within a five-year timeframe from the time we started our research in 2014.
There are three steps to our research. The first is to comprehensively understand what goes on in the brain and body of individual athletes and teams during sports activities. We measure cardiac action potential*1, muscle action potential*2, breathing, brain waves, acceleration speed of each body part, eye movements, etc. and comprehensively understand these data, not as individual components, but as a whole. And by analyzing their relationships, we are able to infer to a certain extent the condition of the brain. As I have previously mentioned, by looking at these outward physical reactions, we are able to infer the unconscious activities of the brain, i.e., the processes of the “implicit brain functions.”
Moreover, we use non-restrictive and non-invasive*3 ways to perform measurements so as not to impede the athlete’s movements while obtaining these data. In other words, we try to grasp what is currently happening, as they occur. Because if you use various sensors for measurement that interfere with the athlete’s movements, you won’t be able to obtain true data.
For this, what you need are advanced wearable sensors that can be attached to the body to obtain various kinds of biometric data. In other words, our research is also aimed at developing new methods for carrying out sports measurements.
We would like to determine the differences in the brain based on skill level
—So, first, to elucidate the processes of implicit brain functions, what you do is use advanced wearable sensors to measure, from different angles, the activities of the brain and the autonomous nerve movements that are generated by those activities. Wouldn’t that involve a massive amount of diverse big data?
Kashino: That’s right. And, the second step is to determine the essence of how to improve performance based on the comprehensive data obtained. For example, we would like to look at how the brain activity patterns during sports differ among amateur, intermediate, and advanced players. Further, among advanced players, we would also like to look at the differences between Japan’s and the world’s top players.
Of course, there are differences, such as in body shape, muscle strength, and cardiopulmonary functions, but those are not the only differences. We believe there are conclusive differences also in the way they move their bodies and how their brains function. If we can elucidate those differences, I think we will be able to improve an athlete’s performance by adjusting brain and body movements in a way that will approximate those of skillful players.
What becomes useful here are machine-learning technologies that have recently produced good results in analyzing data from actual environments. Recently, as you may know, machine learning has been used in various fields, such as in analysis of use purchase behavior and stock price prediction.
First of all is to gather data. Next is to use machine-learning technologies to discover the fundamental factors for improving sports performance, that is, the essence of fine skills. We are combining data-driven methods, wherein we “let data speak for itself,” with laboratory-based hypothesis-testing methods to elucidate the brain functions behind excellent performance in sports.
*1 Cardiac action potential
Cardiac muscle action potential in accordance with the beating of the heart; depicted and recorded as a graph in an electrocardiogram
*2 Muscle action potential
Action potential generated by individual muscle fibers in accordance with muscle movement
*3 Non-invasive method
A method that does not cause trauma to the body; a method for measurement or surgery that does not involve sticking needles to the skin or inserting instruments into the body
（Japanese text written by Madoka Tainaka）
Next: Article 2 (Part 2 of 2)
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