Physiological Signal Sensing & Analysis: How Heartbeats and Muscles Tell a Story in Sports Science
Movement analysis is about how the body moves.
But there is another type of data that tells us what is happening inside the body—physiological signals.
Electromyography (EMG): Understanding When Muscles Activate
Two of the most common physiological signals are electromyography (EMG) and electrocardiography (ECG).
EMG records the electrical signals generated when muscles contract. It can help reveal which muscles activate first during a movement, which muscles contribute less, and whether muscle activation occurs at the right time.
This can be useful for evaluating movement efficiency and helping prevent sports injuries.
What Can EMG Analysis Reveal?
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Whether one side of the body is overcompensating, potentially increasing injury risk over time
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Whether the core muscles are effectively contributing during a swing
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Whether muscle activation patterns change abnormally under fatigue
Electrocardiography (ECG): Reflecting Physical Load and Recovery
ECG records changes in the electrical activity of the heart and can reflect an athlete’s current physiological load and recovery status.
What Questions Can Physiological Signals Answer in Sports Science?
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Which muscles are primarily responsible for generating force during a movement?
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Does the timing of muscle activation follow an ideal kinetic-chain sequence?
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Is the athlete’s current physiological load approaching a fatigue threshold?
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Has the athlete recovered sufficiently for the next training session?
How Physiological Signals Complement Movement Data
Movement data alone can tell us whether a movement was performed effectively. Physiological signals alone can tell us about the body’s current condition.
But when these two types of data are analyzed together, coaches can gain a very different perspective.
For example, if an athlete’s swing speed decreases, is the problem caused by a technical movement issue, or has the athlete’s body already entered a state of fatigue?
These two causes require completely different training adjustments.
From Subjective Feelings to Objective Validation
These two types of signals have something in common: they are invisible, yet constantly present forms of body language.
In the past, coaches could only rely on an athlete saying, “I feel more tired today,” to assess their condition.
Today, physiological signal sensing provides an opportunity to validate these subjective feelings more objectively.
Conclusion
When movement data meets physiological signals, we are no longer looking only at “Was this a good swing?”
We can also ask:
“What was the athlete’s physical condition when this swing happened?”
Physiological signal sensing and analysis allow Sports Science and AI Baseball to look beyond movement and better understand the state of the body itself.