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Self-Powered Acceleration Sensor for Distance Prediction via Triboelectrification.

Zhengbing Ding1, Dinh Cong Nguyen1, Hakjeong Kim1

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Summary
This summary is machine-generated.

A new portable, self-powered acceleration sensor using Triboelectric Nanogenerators (TENGs) offers accurate, real-time sports performance monitoring. This cost-effective device predicts object travel distance, like in golf, with high sensitivity and within 5% accuracy.

Keywords:
acceleration sensordistance predictionself poweredtriboelectric nanogenerator

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Area of Science:

  • Materials Science and Engineering
  • Wearable Technology
  • Sports Science

Background:

  • Accurate prediction of object travel distance is crucial in sports, driving demand for real-time monitoring solutions.
  • Acceleration sensors are gaining traction in sports, but existing Triboelectric Nanogenerator (TENG)-based designs face challenges like large size, complexity, high power needs, and cost.
  • Low energy output and power density of TENGs have limited their application in advanced sensor development.

Purpose of the Study:

  • To develop a portable, cost-effective, and self-powered acceleration sensor for real-time sports performance analysis.
  • To overcome the limitations of existing TENG-based acceleration sensors, focusing on size, complexity, power requirements, and cost.
  • To demonstrate the sensor's capability in predicting the stopping distance of a golf ball after putting.

Main Methods:

  • Designed a portable, real-time, refreshable strategy using individually addressable and controllable TENG units embedded in a flexible substrate.
  • Integrated the TENG-based acceleration sensor into a system capable of measuring initial velocity and acceleration.
  • Validated the sensor's performance by calculating and predicting the stopping distance of a golf ball.

Main Results:

  • Developed a highly sensitive, low-cost, and self-powered acceleration sensor with accuracy controlled within 5%.
  • Successfully displayed initial velocity and acceleration of a rolling golf ball post-impact.
  • Achieved rapid calculation and prediction of stopping distance in approximately 7 seconds.

Conclusions:

  • The developed portable TENG-based acceleration sensor effectively addresses limitations of current technologies, offering a viable solution for sports analytics.
  • This research paves the way for scalable, cost-effective, and ubiquitous self-powered acceleration sensors.
  • The sensor demonstrates practical application in sports, specifically in analyzing putting performance by predicting ball travel distance.