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Updated: Oct 2, 2025

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

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Published on: April 13, 2016

Impact Position Estimation for Baseball Batting with a Force-Irrelevant Vibration Feature.

Wei-Han Chen^1,2, Yang-Chih Feng^3,4, Ming-Chia Yeh^1,5

¹Graduate Institute of Sports Equipment Technology, University of Taipei, Taipei 111036, Taiwan.

Sensors (Basel, Switzerland)

|February 26, 2022

Summary

This study introduces a new force-irrelevant method for estimating baseball impact position using vibration sensor data. Ratios of bat eigenfrequencies reliably predict impact location, regardless of swing intensity.

Keywords:

batting performance bending modes of vibration node of vibration sweet spot

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Area of Science:

Sports Science
Mechanical Engineering
Biomechanics

Background:

Accurate baseball impact position estimation is crucial for performance analysis.
Existing methods may be confounded by variations in impact force.
Novel force-independent techniques are needed for reliable measurement.

Purpose of the Study:

To develop and validate a novel method for estimating baseball impact position.
To identify vibration signal features that are independent of impact intensity (force-irrelevant).
To assess the efficacy of these features in both static and dynamic batting experiments.

Main Methods:

A piezoelectric vibration sensor was attached to a wooden bat's knob.
Vibration signals were recorded from controlled impacts at 40 positions and 3 intensities (static experiment).
Vibration signals were also collected during actual batting by three players (dynamic experiment).

Main Results:

Peak signal amplitude and eigenfrequency peaks correlated with impact intensity.
Ratios of the first three eigenfrequency peaks remained consistent across intensities.
This force-irrelevant feature was observed in both static and dynamic experiments.

Conclusions:

The ratios of peaks at the first three eigenfrequencies are a reliable, force-irrelevant feature for impact position estimation.
This method offers a robust approach to analyzing baseball impacts.
The findings have implications for sports technology and performance analytics.